america’s biotech and life science clusters...further, we created a unique biotechnology and life...

America’s Biotech and Life Science Clusters

San Diego’s Position and Economic Contributions

by Ross DeVol, Perry Wong, Junghoon Ki, Armen Bedroussian and Rob Koepp

June 2004

The Milken Institute would like to give special thanks to key members of the Deloitte team. The authors would like to express their gratitude to Mari-Anne Kehler for her vision in forging a collaborative relationship between our organizations and in making the idea for this study become a reality. We would also like to thank Andrew Bird and Stuart Sechriest for their support in coordinating our efforts within the Deloitte organization, recommendations on stakeholders to be interviewed for the study and in outreach efforts to the San Diego community. We greatly appreciate the efforts of Teresa Young and Kim Snover of Deloitte’s San Diego office for arranging the interviews and participating in many of them. Teresa Young’s valuable insights, offered after reviewing a draft of the study, added a unique long-term cluster participant’s perspective. We would like to thank Anthony Buzzelli for his efforts in helping coordinate with the Deloitte National Life Sciences team. We appreciate all the feedback from Deloitte staff, too numerous to list. Additionally, we would like to thank Joe Panetta and April Bailey of BIOCOM, and Susan Atkins of Susan E. Atkins & Associates for their guidance and recommendations of key people to be interviewed.

Rob Koepp and the entire Milken Institute project team extend their sincere gratitude to all of the San Diego cluster members who agreed to be interviewed for this project. Their insights added context to the quantitative assessments and allowed us to get behind the numbers. They are listed below in alphabetical order:

Howard Birndorf, CEO, NanogenMike Borer, CEO, Xcel PharmaceuticalsWain Fishburn, Partner, Cooley GodwardDelbert Glanz, Executive Vice President, The Salk Institute for Biological StudiesLisa Haile, Partner, Gray Cary Ware & FreidenrichEdw ard Holmes, Vice Chancellor for Health Sciences; Dean, University of California,

San Diego School of MedicineDavid Kabakoff, CEO, SalmedixArnold LaGuardia, Executive Vice President, The Scripps Research InstituteCatherine Mackey, Senior Vice President, Pfizer Global Research and DevelopmentConnie Matsui, Executive Vice President, Biogen IDECSteve Mento, CEO, Idun PharmaceuticalsRichard Murphy, President, The Salk Institute for Biological StudiesGail Naughton, Dean, College of Business Administration, San Diego State University Henry Nordhoff, CEO, Gen-ProbeJoe Panetta, CEO, BIOCOMDuane Roth, CEO, Alliance PharmaceuticalIvor Royston, Managing Member, Forward VenturesTeresa Young, Partner, Deloitte

Copyright 2004 Milken Institute

Acknowledgements

Acknowledgements ................................................................................................... i

Executive Summary .................................................................................................. 1

History ................................................................................................................... 10

The Biotechnology Innovation Pipeline Index ..................................................... 27

R & D Assets ..................................................................................................... 28

Metro Findings ......................................................................................... 30

Methodology ............................................................................................ 34

Risk Capital & Entrepreneurial Infrastructure .............................................. 35

Metro Findings ......................................................................................... 37

Methodology ............................................................................................ 40

Human Capital Capacity ................................................................................. 41

Metro Findings ......................................................................................... 44

Technology & Science Workforce ................................................................... 49

Metro Findings ......................................................................................... 51

Methodology ............................................................................................ 55

Current Impact Assessment ................................................................................... 56

Size and Performance .............................................................................. 57

Diversity .................................................................................................... 57

Composite Index ...................................................................................... 58

Metro Findings ......................................................................................... 59

Methodology ............................................................................................ 70

Overall Composite Index ........................................................................................ 74

Metro Findings ......................................................................................... 74

Methodology ............................................................................................ 78

Multiplier Impacts .................................................................................................. 79

Metro Findings ......................................................................................... 80

Methodology ............................................................................................ 82

Conclusion ............................................................................................................... 83

Appendix ................................................................................................................. 86

About the Authors .................................................................................................. 99

About Deloitte & Milken Institute ....................................................................... 101

Table of Contents

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Executive SummaryChemistry and physics were the sciences that propelled technological advances in the first half of the 20th century. Advances in engineering and electronics led to the computer and information technology revolution in the second half of the 20th century, but progress in microbiology and genomics hold the promise to make biotechnology the dominant economic force of the first half of the 21st century. The electronic and computer breakthroughs will allow massive amounts of genetic information to be decoded and processed. We are likely to see a fusing of information technology and biotechnology into a highly effective means of disease prevention, detection and finding cures. As a science and industry, biotechnology will mature and create enormous changes in our lives and benefit the entire human race.

Numerous proteins are already used as therapeutics, the result of recombinant DNA technology. Biotechnology companies have, through their partnership with pharmaceutical firms, improved the quality of human life and extended the lifespan of many individuals. The industry has discovered antibodies for cancer, arthritis and tissue transplant, growth hormones, and clot-busting enzymes.

In addition to the race for discovering biotechnology-derived therapeutics, there is a different kind of race underway: the one that will determine where the primary geographic locations of this industry reside. The economic outcomes of where these biotechnology clusters form and grow are likely to be immense.

The 21st century biotechnology cluster race has many regional entries in the U.S. and around the world. Within the U.S., California has several metropolitan areas that are among the leaders as the race commences including Oakland, San Francisco, San Jose, Los Angeles, Orange County, and San Diego. The East Coast has Boston, Philadelphia, Washington, D.C., and Raleigh-Durham among the leading aspirants. Seattle and Austin appear to be two other top geographic contenders.

What is a cluster? Industry clusters are geographic concentrations of sometimes competing, sometimes collaborating firms, and their related supplier network. They are agglomerations of interrelated industries that foster wealth creation in a region, principally through the export of goods and services beyond their borders. A cluster represents an entire value chain of a broadly defined industry sector from suppliers to end products, including its related suppliers and specialized infrastructure.

Supplier networks are instrumental to the success of clusters and fostering sustained agglomeration processes. Clusters are interconnected by the flow of goods and services. This flow is stronger than the one linking them to the rest of the local economy. Cluster members usually include governmental and nongovernmental entities such as public/private partnerships, trade associations, universities,

Executive Summary

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think tanks and vocational training programs, venture capitalists, patent attorneys, and even accounting and auditing firms in the case of biotechnology.

Because knowledge is generated, transmitted, and shared more efficiently in close proximity, economic activity based on new knowledge has a high propensity to cluster in a geographic area. A region with a top biotechnology cluster will have more innovations, less of which will escape to other regions, or at least, they will do so at a slower rate. Regions excel to the extent that the firms and talent in them can innovate successfully by being there, rather than elsewhere. This is particularly poignant for an industry such as biotechnology whose survival is based upon continuous innovation streams.

In this study, we compare and contrast the San Diego biotechnology and life sciences cluster with 11 other clusters identified above, review its formation and historical evolution and highlight the industry’s economic contributions to the region. These 12 clusters were selected by reviewing previous studies and performing statistical evaluations for which metropolitan areas possessed the greatest specialization and concentration of the biotech industry in the United States.

To appropriately determine the density of a biotechnology cluster, we utilized the smaller geographic area represented by metropolitan statistical areas (MSAs). Many previous studies based their findings upon larger consolidated metropolitan statistical areas (CMSAs). Our organizing principle for this study was to measure which biotech clusters were the densest, but at the same time had sufficient scale.

To compare the relative strength of each metro’s biotech assets, we scaled out each component measure by population, employment or gross metro product (GMP), such as the San Diego metro’s academic R&D dollars (to biotech) per capita. After such adjustments, we compared the relative scores of the 12 metros and ranked them. Many previous studies based their findings upon absolute measures. By converting them to relative measures, a more accurate representation of the richness and depth of the clusters is revealed. For a more complete discussion of this topic, please see the methodology portion of the biotech research and development section on page 34.

Further, we created a unique biotechnology and life sciences data set and most importantly, provided employment estimates through 2002. Previous studies’ most current employment information went through 1997. In biotechnology, 1997 is ancient history. Our data set allowed an investigation of recent growth performance.

Biotechnology Innovation PipelineThe term “biotechnology innovation pipeline” refers to the support infrastructure and outcome measures that reflect the ability of an area to capitalize on its strengths in biotech knowledge and creativity. A rich innovation pipeline plays a pivotal role in a region’s biotech and life science industry gestation, commercialization, competitiveness and ability to sustain long-term growth. It also constitutes an important socio-economic asset to regional, state and national economies.


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Executive Summary

This study includes measures of research and development (R&D), risk capital and entrepreneurship infrastructure, biotech and life science human capital, and biotechnology and life science workforce. We begin with the biotech research and development (R&D) assets that can be commercialized for future metro biotech growth. R&D assets are vital for biotech more so than any other industrial sector, primarily because biotech, especially in its early stages, is intensely dependent on basic research.

San Diego has particular strength in biotechnology research and development assets. Many San Diego-based biotech and life science firms are devoted to R&D, either basic or applied, and they are seeking more R&D funds and support. The Scripps Research Institute, Salk Institute for Biomedical Studies, Burnham Institute and the University of California, San Diego (UCSD) provide a rich R&D knowledge base for the region. San Diego’s composite score for biotech research and development inputs is 79.7 (out of a perfect score of 100) before rebasing the top score to 100 for comparison purposes, which positions the metro as top ranked among the 12 selected metros with a rebased score of 100. The research and development composite is comprised of nine indicators.

San Diego’s relative advantages in the composite score come from its attractiveness to public R&D funding such as National Science Foundation (NSF) for basic biotech research and National Institutes of Health (NIH) for advanced research. San Diego also benefits from commercial opportunities for biotech research. San Diego’s superior rankings in the relative biotech Small Business Technology Transfer (STTR) awards and biotech Small Business Innovation Research (SBIR) statistics confirm regional effectiveness in commercializing R&D efforts and new ventures. Boston ranked 2nd with a composite score 78.9 (or a rebased score of 99) and Seattle, 3rd, followed by Raleigh-Durham-Chapel Hill, 4th among the 12 competing metros.

MSA RankCompositeScore MSA Rank

CompositeScore MSA Rank

CompositeScore

San Diego 1 100.0 San Jose 1 100.0 Raleigh-Durham-Chapel Hill 1 100.0Boston 2 99.0 San Francisco 2 98.9 Boston 2 90.2Seattle-Bellevue-Everett 3 96.4 San Diego 3 97.4 Oakland 3 80.0Raleigh-Durham-Chapel Hill 4 91.9 Raleigh-Durham-Chapel Hill 4 95.4 San Diego 4 79.7Philadelphia 5 84.9 Boston MA-NH 5 89.9 San Jose 5 78.7Washington, D.C. 6 80.3 Seattle-Bellevue-Everett 6 85.1 Philadelphia 6 74.3San Jose 7 75.3 Washington, D.C. 7 80.9 Washington, D.C. 7 74.0Los Angeles-Long Beach 8 75.3 Philadelphia 8 77.3 Seattle-Bellevue-Everett 8 73.7San Francisco 9 71.1 Orange County 9 76.0 Austin-San Marcos 9 66.6Oakland 10 66.7 Los Angeles-Long Beach 10 63.6 Los Angeles-Long Beach 10 63.8Orange County 11 54.0 Oakland 11 56.9 San Francisco 11 59.9Austin-San Marcos 12 52.0 Austin-San Marcos 12 53.1 Orange County 12 51.7



CompositeScore

Raleigh-Durham-Chapel Hill 1 100.0 San Diego 1 100.0 San Diego 1 100.0Boston 2 99.2 Boston NECMA 2 80.3 Boston NECMA 2 95.1San Jose 3 95.6 San Jose 3 78.1 Raleigh-Durham-Chapel Hill 3 92.5Oakland 4 93.9 Raleigh-Durham-Chapel Hill 4 69.4 San Jose 4 87.8San Diego 5 91.7 Seattle-Bellevue-Everett 5 68.4 Seattle-Bellevue-Everett 5 83.8Washington, D.C. 6 86.3 Washington, D.C. 6 64.8 Washington, D.C. 6 79.4Seattle-Bellevue-Everett 7 78.3 Oakland 7 64.2 Philadelphia 7 76.5Philadelphia 8 77.7 San Francisco 8 63.6 San Francisco 8 75.8San Francisco 9 76.1 Philadelphia 9 58.5 Oakland 9 74.3Los Angeles-Long Beach 10 70.8 Los Angeles-Long Beach 10 50.0 Los Angeles-Long Beach 10 66.5Orange County 11 67.7 Orange County 11 29.2 Orange County 11 54.1Austin-San Marcos 12 42.2 Austin-San Marcos 12 27.8 Austin-San Marcos 12 47.8

4. Biotech Workforce5. Current Impact

(Biotech)Overall

Composite

Milken Institute's 2004 Biotech IndexBy Category and Overall Composite

1. R&D Inputs 2. Risk Capital 3. Human Capital

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Entrepreneurial capacity and performance are major players in the new economic milieu in which creativity and innovative dynamics determine the competitive advantage of a firm and an industry. Risk capital and entrepreneurs are pivotal because new ideas are best equipped with new firms or spin-offs. The Index’s Biotech Risk Capital and Entrepreneurial Infrastructure measure consists of 10 components, each of them portraying essential business climate aspects for biotech start-ups and biotech entrepreneurial activities.

San Diego’s biotech risk capital and entrepreneurial infrastructure score is 88.6 (out of a perfect score of 100) before rebasing the top score to 100 for comparison purposes. Its rebased score is 97.4, which places it 3rd among the 12 selected metros. Northern California metros San Jose and San Francisco, ranked 1st and 2nd, respectively. San Diego’s strongest achievement among the indicators for Biotech Risk Capital and Entrepreneurial Infrastructure were biotech venture capital dollars per $100,000 of GMP, biotech patents per population, biotech patent citations per population, and Deloitte’s Technology Fast 500 companies in life sciences.

Though there are many economic factors expediting the formation of these biotechnology clusters and sustaining them, the fundamental building blocks are pools of talent, human capital and their respective capacity to fulfill the technical and operational requirements. Location still matters only if it has vast capacity to attract talent that yield a tremendous amount of intellectual property (IP). The Biotech Human Capital Capacity Index consists of 12 components examining stocks and flows of biotechnology-related human capital that give us an estimate of the capacity to create IP.

San Diego ranked 4th with a composite score of 74.7 (or 79.7 after rebasing the top scoring metro to 100) on biotech human capital. The region’s placement was distant from the top ranked Raleigh-Durham and Boston, but it outranked life science heavyweights such as Philadelphia and Washington, D.C. Among the 12 components, San Diego had four important components that ranked in the top three places. They include per capita measurements of biotech postdoctoral fellowships, biotech scientists and biotech bachelor’s degrees awarded, and the percent of biotech bachelor’s degrees among all bachelor’s degrees granted in San Diego. San Diego distinguishes itself from many other biotech centers by having a disproportionate share of locally produced PhD holders who go into industry as opposed to academic research, a key advantage for commercialization success.

Sustaining a biotech cluster requires a workforce with industry-specific skills within a location where operations take place. This pooling of specialized technology and science workforce can be a critical factor for the industry to expand and firms to grow. The Biotech Workforce Composite Index consists of six occupational components.

In the composite measurement of the region’s biotech workforce, San Diego scored relatively high, ranking 5th among the 12 metropolitan areas studied with an unadjusted score of 85.3 or a rebased score of 91.7. Its position is very respectable, but nevertheless exposes the weaker side of the region’s biotech cluster in specific workforce categories and life science in general. In the measurement of


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workforce, San Diego fell behind Raleigh-Durham-Chapel Hill (1st), Boston (2nd), San Jose (3rd) and Oakland (4th). On the other hand, the top five metros’ scores were very close to one another.

Current Impact AssessmentWhile the innovation pipeline addresses the capacity and infrastructure for success, the current impact assessment focuses on the relative economic outcome of the biotechnology and life sciences industry. By measuring economic outcomes, we are able to assess the effectiveness of policymakers, participants and other stakeholders in transforming its assets into economic prosperity for it residents.

The current impact assessment measures the absolute and relative importance of employment size and growth, taking into account those metros that offer a more diverse set of life science industries. Specifically, the current impact index is comprised of seven unique components:

• Employment Level in 2002, • Location Quotient1 (LQ) in terms of employment in 2002, • Relative Employment Growth from 1997–2002, • Number of Establishments in 2001, • Number of Location Quotients Greater than 2.0, • Number of Location Quotients Less than 0.5, and finally, • Number of Life Science Industries Growing Faster than the U.S. from 1997–2002.

The first four components address the issues of size and performance, while the latter three measure diversity. The Current Impact Composite Index (comprised of these seven components) summarizes and creates a relative snapshot of the current economic impact or outcome.

Within the biotech composite, San Diego scored 100 (1st) on three of the seven measures and is at 78 or better on the rest. Its strengths include not only relative employment size and growth within the overall biotech industry, but also a high concentration mix of biotech-related industries as explained by the diversity measures. While the region’s biotech activity is funneled primarily through its R&D (North American Industrial Classification Code-NAICS 5417102), San Diego has displayed significant growth in its biotech production process, thus creating a diverse set of biotech-related industries. San Diego employs 14,500 biotech workers. Only Boston had a larger biotechnology employment base with 18,700 workers. Boston ranked 2nd on the overall composite index, followed by Raleigh-Durham in 3rd and San Jose in 4th place. Although San Diego scored 100 (1st) in only two categories within the life sciences, it still managed to rank 2nd overall with a life science composite index score of 92. Limited activity in pharmaceutical

Executive Summary

1The Location Quotient (LQ) equals % employment in metro divided by % employment in the U.S. If LQ>1.0, the industry is more concentrated in the metro area than in the U.S. average.

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manufacturing coupled with underperformance in the medical devices industry relative to metros like Boston, San Jose and Orange County are the primary reasons that San Diego slipped in comparison to its biotech ranking on the current impact composite index. On the other hand, San Diego scored highest on two out of the three diversity measures, suggesting that although the region may not have the largest absolute share of national employment in life sciences, it certainly ranks among the highest when adjusting for its total employment base.

In order to gain a more complete picture of the spatial dimensions of the San Diego biotechnology and life sciences cluster, it is beneficial to map its organizations and employment centers. Most firms are located in La Jolla and the area east of Interstate 5 in the city of San Diego near La Jolla. This area is called the Golden Triangle by cluster participants and is bounded by Interstate 5, Highway 52 and Highway 805. These firms are within a five-mile radius of one another from the center. The Golden Triangle represents perhaps the densest concentration of biotech research, firm and overall employment in the nation. Ivor Royston of Forward Ventures supports this stating, “…We have the highest concentration of biotech companies per unit mile, whatever the denominator ...” [e.g. employment, per capita, population].

Overall Composite IndexThe overall composite index includes the four components discussed within the innovation pipeline and current impact assessment sections. The individual components are R&D inputs, risk capital, human capital, biotech workforce and current impact. San Diego ranked 1st in the nation in the biotech overall composite index. Much of this can be attributed to its relative 1st-place ranking within the R&D and current impact indices. Boston is a close 2nd with a relative score of 95.1, followed by Raleigh-Durham and San Jose with scores of 92.5 and 87.8, respectively.

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Boston(95.1)

San Diego(100.0)

Austin(47.8)

Philadelphia(76.5)

Seattle (83.8)

Los Angeles(66.5)

Oakland (74.3)

Orange County(54.1)

San Jose (87.8)

SanFrancisco(75.8)

WashingtonD.C. (79.4)

Raleigh(92.5)

Milken Institute Biotech-Poles2004


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The rankings in the Overall Composite Index shift when the biotech current impact index is replaced with the life science current impact index (keeping all other components constant.) Those metros highly engaged in pharmaceuticals’ and medical devices’ manufacturing activity, in addition to their biotech presence, rise accordingly. San Diego ranked 2nd on the overall life science composite index. With Boston’s high concentration of pharmaceutical industries, that metro moved up to 1st-place for life science. Boston is also well equipped with respect to the manufacturing of medical devices. San Jose and Raleigh-Durham finished 3rd and 4th, respectively, on the overall life science composite index.

Multiplier ImpactsTo better understand the importance of the biotech/life science industry in San Diego we must analyze its impact on the overall economy. Multiplicative values known as “multipliers” allow us to do this by quantifying how employment and output in biotech/life science industry ripple through other regional economic sectors. In addition to providing numerical data on an industry’s regional impact, economic multipliers also bring to light region-wide interdependencies and inter-industry relationships.

Within the concept of multiplier impacts, three key forces are at play. In addition to the direct impact of industry employment, wages and output, the biotech and life sciences industry impacts many supplier industries such as legal, financial and advertising services. The indirect impact represents the number of jobs, wages or amount of output generated from all supplier industries necessary to support employment and output in biotech and life sciences. The higher employment and wages in these supplier industries ripple throughout the local economy leading to higher purchases of goods and services, which, in turn, cause higher income available to be spent in the local economy, known as the induced impact.

Altogether, the life science industry in San Diego MSA is responsible for 55,600 jobs, or nearly 5 percent of all nonagricultural employment in the region. Of those, 21,000 are accounted for directly, while 12,600 and 21,000 are generated through the indirect and induced effects, respectively. For every job within the life sciences in San Diego, an additional 1.7 jobs are created in all other sectors (see graphs below).

Executive Summary

Total Impact

60

50

40

30

20

10

0

Employment (Ths.)

Sources: Milken Institute, BEA.

Total Impact of San Diego Life ScienceDirect, Indirect and Induced Impacts - Employment, 2002

DirectIndirectInduced

Total Impact

7

6

5

4

3

2

1

0

Output (Billions of $U.S.)


Total Impact of San Diego Life ScienceDirect, Indirect and Induced Impacts - Output, 2002


Total = 55.6

21.0

12.6

21.0

Total = $5.8 Billion

22

.843

2.8

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Similarly, the life science industry in San Diego MSA is responsible for $5.8 billion, or 5.3 percent of gross metro product in the region. $2.8 billion is registered directly, while $843 million and $2.2 billion are generated through the indirect and induced impacts, respectively. For each dollar of output produced in the life sciences sector in San Diego, an additional $1.10 of output is generated beyond it.

Conclusions and Policy IssuesBased upon our evaluation criteria, San Diego ranks as the top biotechnology cluster in the country, edging past 2nd-place Boston. If the benchmarking criteria were adjusted somewhat, Boston might surpass it. In many respects the two are virtually tied for 1st place. Many in the industry view San Francisco as holding a top spot, but that perception is based upon looking at the entire San Francisco Bay Area and absolute measures of performance.

Raleigh-Durham is a rising biotech cluster as denoted by its 1st-place finish in both the human capital and biotech workforce categories (and its overall 3rd place in biotech) although the metro’s smaller size must be taken into account. San Jose is the top scoring Bay Area metro biotech cluster at 4th and grew faster over the last five years than San Diego. When extending the analysis to life science clusters, including medical devices and pharmaceuticals, Boston moved past San Diego to 1st overall. Boston’s top position in medical devices and strength in pharmaceuticals give it more diversity. San Jose moves to 3rd in life sciences, courtesy of its 3rd place in medical devices just behind Orange County. Raleigh-Durham slips to 4th in life sciences.

As a national leader in biotechnology and life sciences, San Diego has enormous opportunities and challenges in preserving or enhancing its position. Stakeholders must shepherd their talents and resources to address the following issues:

• Despite its strength in overall R&D, San Diego should acquire a greater share of funding distributed to research universities. UCSD is a great resource, but lack of scale could present it with challenges in the future.

• More indigenous or local venture capital firms are needed to exploit the inventiveness of entrepreneurs in the area. San Diego must reduce its dependence upon VCs flying to the community by air. BIOCOM President Joe Panetta acknowledges that attracting more venture capital firms to San Diego is one of its strategic initiatives.

• San Diego has been very successful at recruiting some of the best research talent from around the country, and even the world. Nevertheless, it must continue to increase home grown talent through UCSD and California State University, San Diego.

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Executive Summary

• More local human capital in biotechnology should be created because the high cost of living, especially housing, will make it more difficult to recruit young talent from other parts of the country.

• San Diego needs to create more profitable biotechnology firms. Most are still operating in a negative cash-flow position.

• San Diego must create a few larger biotech anchor firms to add more stability to the ecosystem.

• A larger presence of pharmaceutical firms would create a deeper and richer management pool that the larger life science cluster could draw upon.

• San Diego could enhance its future position as a biotech center by demonstrating an ability to manufacture more products locally as opposed to being heavily research-based.

These observations should be understood in the context of San Diego as among the elite biotech clusters in the world. Innovative and collaborative approaches for maintaining growth must continue to be pursued. Pooling resources to retain and create biotechnology jobs, would enable the San Diego cluster to be an even greater economic force in the region. BIOCOM, UCSD CONNECT, San Diego Regional Economic Development Corporation, and other trade groups and associations are vital support systems for progress.

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HistoryIntroductionSan Diego’s recognition as a life science industry cluster is relatively new. The founding of Hybritech, one of America’s pioneer biotech companies, in the Torrey Pines Mesa area in 1978 signified the first readily identifiable step that the region took toward becoming one of the world’s pre-eminent biotech hubs. In the wake of that company’s growth and multifarious impacts, by the 1990s, San Diego went from being best known as a sleepy Navy town to a thriving center for life science discovery and commercialization. The founders and others who played important roles in Hybritech’s creation and development still contribute—though in capacities of greater experience and influence—to the ongoing evolution of the cluster.

Yet the arrival of a cluster’s “seeding company” represents as much an end as it does a beginning: the economic reward attained after preliminary work helped prepare the area for industrial development. The significance of Hybritech (which in fact is no longer an ongoing concern in the region) is transcended in a multitude of ways by additional efforts that were made before, during, and after the company’s origination and growth. An intricate tapestry of cause and effect, one which spans over 100 years, needs to be appreciated.

Early BeginningsWhat is known today as the Scripps Institution of Oceanography (SIO) represents the first instance of organized life science-related research in the San Diego region. Originally founded in 1903 as the Marine Biological Association of San Diego, the association was institutionalized as a research center of the University of California (UC) in 1912. At that time it also adopted the Scripps name to recognize the benefaction of Ellen Browning and Edward W. Scripps, whose wealth acquired in another knowledge-intensive activity—newspaper publishing—made such support possible. Today the Institution directly employs around 1,300 people (nearly 600 of whom are scientists or graduate students), with annual expenditures exceeding $140 million.2

As one of the world’s oldest and largest marine science research laboratories, SIO has long stood as an example of the region’s scientific capabilities. The San Diego area’s best recognized life science research body that carries the Scripps name however is the Scripps Research Institute (TSRI), founded in 1955 as the Scripps Clinic and Research Foundation, an offshoot of the Scripps Clinic hospital. TSRI was chief among the early catalysts for biomedical research activity in the region. Subsequently, the core of today’s biotech community has essentially evolved having radiated outward from TSRI’s base along the ocean bluffs of San Diego’s Torrey Pines Mesa area of La Jolla (see map).

2 Scripps Institution of Oceanography web site: www.sio.ucsd.edu.

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History

The Scripps Research Institute solidified a position as one of the world’s leading centers of biomedical research in 1961 with the recruitment of the immunologist Frank Dixon and a team of four colleagues from the University of Pittsburgh. Specializing in the causes of autoimmune disease, the pioneering work of Dixon and his team effectively put TSRI, in particular its Department of Experimental Pathology, at the forefront of bio-science research.

In 1960 the city of San Diego gifted 27 acres of ocean-facing property on the Torrey Pines bluff to Jonas Salk, discoverer of the polio vaccine, for establishing his Salk Institute for Biological Studies. By that time, in addition to the Scripps Institution of Oceanography and biomedical Research Institute, the divisional operations of General Dynamics involved in nuclear research, a private company known as General Atomics, had located to the San Diego region as well. Similar to the attractive force for talent exerted by the Scripps Research Institute, Jonas Salk brought to his center some of the world’s foremost biological research scientists, including Francis Crick, one of the discoverers of the “double helix” structure of deoxyribonucleic acid (DNA). Thus, almost two decades before the launch of San Diego’s first biotech company, the area was already well populated with advanced research sites and truly world-class human capital.

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Noticeably lacking in this early research base, however, was a full-fledged research university. Although the Scripps Institution of Oceanography functioned as a University of California research lab, it did not operate as a university branch campus. The closest nearby universities involved in biomedical research up until then were the Los Angeles area campuses of UCLA, the University of Southern California, and the California Institute of Technology—all located more than 100 miles north.

This gaping lack of a nearby research university was resolved in 1961 with the establishment of the San Diego campus of the University of California. Situated on the Torrey Pines Mesa in close proximity to the SIO, TSRI, and the Salk Institute sites, from its inception, UCSD strongly orientated toward the medical sciences and engineering. The leaders of the Scripps Institution and General Atomics had in fact been instrumental in lobbying the U.C. system and San Diego government bureaucracies to allow the campus’ establishment. The presence of U.C. San Diego was envisioned by its founders to constitute the “MIT of the West.” Its research and teaching activities since then have added tremendously to the intellectual diversity, depth and stature of the region (see sidebar).

By the 1970s, this nascent cluster of life science-related research institutions was being augmented by proactive economic development policies and the appearance of new research organizations. Later prominent arrivals to the enclave include the Burnham Institute, the Sidney Kimmel Cancer Center, the Neurosciences Institute, and the La Jolla Institute for Allergies and Immunology.

The Appearance of BiotechnologyIt was back in 1919 that the Hungarian engineer, economist, and government minister Károly Ereky brought forth the term “biotechnology” (in the original German: “biotechnologie”) and its defining conceptualization of products made “from raw materials with the aid of living

UCSD: Indicators of Bio-Science Strengths

Since its founding in 1961, U.C. San Diego has risen to become one of the world’s leading universities for life science research. The following illustrates various dimensions of its leadership position.

Nobel Laureates. Ten UCSD faculty have been awarded the Nobel Prize. Current faculty members who won awards relevant to the life sciences are Francis Crick (prize awarded in 1962 for discovery of the double helix structure of DNA), George Palade (1974, structural and functional organization of the cell), and Renato Dulbecco (1975, tumor viruses).

National Medal of Science. Considered the nation’s highest scientific honor, eight UCSD faculty have been recipients, including Nobel Laureate George Palade (1986) and Yuan-Chen Fung (2000), professor emeritus of bioengineering.

MacArthur Foundation Awards. Popularly known as the “Genius Awards,” 11 UCSD faculty have been recipients, including Russell Lande in biology.

National Academy of Sciences. UCSD ranks 7th in the nation in the number of faculty elected to the NAS, America’s premier society for the scientific community. (The top 10, in descending order, are: Harvard, U.C. Berkeley, Stanford, MIT, Yale, CalTech, UCSD, Princeton, Chicago, and Cornell.)

Nature Magazine. The leading scholarly journal of the life sciences, Nature, in its “Yearbook of Science and Technology” has ranked UCSD as “one of the 10 most powerful research universities in the United States.”

Cited Research. The Institute for Scientific Information has ranked UCSD 5th in the world in terms of the most cited molecular biology and genetic research papers. UCSD pharmacology professor Michael Karin ranks 1st worldwide.

Source: U.C. San Diego.

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History

organisms.”3 Much of the promise of biotechnology did not begin to be realized until about one-half century later, however, when exciting new discoveries and applications in molecular biology came on the scene.

Despite San Diego’s already strong position in biomedical research capabilities, by the early 1970s, it was the region’s Northern California counterpart, the San Francisco Bay Area, which took the lead in crucial early biotechnology breakthroughs. Most notably, in 1972, Stanford biochemist Paul Berg managed effectively to paste together two strands of DNA to form a hybrid molecule. By the next year, his Stanford colleagues Stanley Cohen and Annie Chang along with U.C. San Francisco’s Herbert Boyer devised a way to produce the world’s first recombinant DNA organism. The teams’ process recombined DNA in desired configurations that, when inserted into the DNA of reproductive bacteria, brought to life what are essentially molecular manufacturing plants. These cornerstone developments in genetic engineering provided the basis for the biotechnology and biopharmaceutical industries of today.

San Diego, however, was not far behind the epoch-making advances occurring in laboratories of Stanford and U.C. San Francisco. In fact, San Diego’s start with new biotech discoveries and commercialization—in a way very similar to its start in the previous decade with semiconductor research and manufacturing—grew as an outcropping of the talent and financial capital that had been accumulating in the greater San Francisco area.

In the case of the formation of San Diego’s first full-fledged biotech company, Hybritech, its two co-founders had been lured away in 1977 from research positions at Stanford to do work at U.C. San Diego on what was then one of the most promising fields in biomedical research: monoclonal antibodies. Monoclonal antibodies—genetically engineered proteins that were touted as “magic bullets” because of their potential to attack cancer without destroying healthy cells—were discovered in 1975 by a team of scientists working at Cambridge’s Laboratory of Molecular Biology in England. The scientists, César Milstein and Georges Köhler, went on to earn a Nobel Prize for their work. Yet owing to severe government mismanagement of the laboratory’s intellectual property and lack of channels for technology transfer, nothing was done in Britain to develop the invention commercially.4 In contrast, within less than a year of their arrival at UCSD’s cancer center, the former Stanford research team of Royston and Birndorf had decided to find a means to set up a company based on their own advances in monoclonal antibody production techniques.

Royston and Birndorf named their company after the field of hybridoma technology, a process of fusing an antibody-producing cell with a tumor cell to produce a hybrid that then can be repeatedly

3 Fári, M. G., R. Bud, P. U. Kralovánszky. 2001. “The History of the Term Biotechnology: Károly Ereky and His Contribution,” presentation at the Fourth Congress of Redbio – Encuentro Latinoamericano de Biotecnologia Vegetal, Goiânia, Brazil, June 4-8.

4 Koepp, Rob. 2002. Clusters of Creativity: Enduring Lessons on Innovation and Entrepreneurship from Silicon Valley and Europe’s Silicon Fen (Chichester: John Wiley & Sons), 167.

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cloned to generate customized, consistently identical “monoclonal” antibodies. They incorporated Hybritech on September 14, 1978. By the following month, they were flush with almost twice the amount of capital financing than they had originally sought. The money, the founders’ knowledge of their field and its experts, and helpful guidance from their venture capital investor, allowed Hybritech to recruit top talent to its modest subleased lab and office space located in what was then the recently opened La Jolla Cancer Research Foundation (today known as the Burnham Institute).

One of the most surprising aspects of Hybritech’s early and subsequent success was the sheer modesty of the company’s original purpose. The company came together without an elaborate business plan and no substantial business experience held by the founders. Royston and Birndorf entertained the hope that whatever revenue came from their venture might eventually be enough to support the very expensive primary research required for developing monoclonal antibodies that could cure cancer. But specific plans for Hybritech, which co-founder Birndorf thought of as “a very nice little business,” were themselves of minor scale (see below). Everything about the environment in which the company operated was fairly humble as well; from Hybritech’s subleased work area to its location in a region that at the time boasted an image of sleepy tranquility. In the late 1970s, the San Diego metropolitan area’s best known regional assets were still its weather, military bases and defense industry manufacturers.

Hybritech: The View from Employee No. 1Howard Birndorf did not come to San Diego with the intention to participate in the founding of a biotech company, let alone what would become the seeding firm of the area’s thriving life science industry cluster of today. Yet from the opportunity to pursue his scientific interests in a laboratory at U.C. San Diego, he found the area afforded him more than just possibilities with lab bench science, but with starting up commercial enterprise. Since becoming the first full-time employee at San Diego’s first biotech company, Birndorf, who now serves as the CEO of the San Diego biotech company Nanogen, has gone on to play an influential role in the establishment of numerous biotech firms and industry-related organizations. The following comments come from his reflections on what brought him to San Diego; how Hybritech was initially formed, funded, and operated; and the significance of the industrial cluster that emerged in its wake.

Arrival in San DiegoI grew up in Michigan and I did my graduate work there, at Wayne State University, and then worked full time as a research scientist at the Michigan Cancer Foundation. I decided that I wanted to leave the winters and move to California. I moved to the Bay Area and got a job as a research associate at Stanford University in the division of oncology. During my tenure there I met another

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History

researcher, Ivor Royston, who was an M.D. He and I hit it off and we did sort of skunk work experiments, looking at new technology called hybridomas, which was a way to immortalize an antibody-producing cell line. He finished up his Stanford fellowship and was offered a position at UCSD as an assistant professor. He asked me to move down here to start and run his laboratory, so what brought me to San Diego initially was this job opportunity at the university.

Technological InnovationWhile we were doing work in the lab on these hybridomas, both Ivor and I recognized the commercial possibilities associated with selling antibodies that were uniform and standardized. I would like to say that we had the big vision, but initially it was a much smaller vision. The vision was based on how we bought antibodies all the time for our research and antibodies back then were made in animals. The animals were injected with immunizers and then their blood would be harvested and the antibodies isolated and purified and sold. Each batch was different. Each time you did it produced different immunogenicity and whatnot and you had to test each batch, etc. Our initial thought was, “Well, wouldn’t it be a nice business if we set up a company that would sell research antibodies and each antibody would be the same forever?” So anybody doing research with a particular antibody that we sold would know that every time they bought it from us it would be exactly the same. They wouldn’t have to adjust their experiments for the different properties of the antibody.

Writing the Business PlanWe thought, well, this would be a very nice little business. So we went out and bought a book called How to Start Your Own Business. Both Ivor and I read the book and we wrote—I think it was a six-page business plan; he wrote certain sections and I wrote certain sections. We put it together. Ivor was an M.D. oncologist, I was a biochemist molecular biologist working in the lab;neither one of us had ever had any business experience. I mean, I always worked through high school and college and whatnot but [not in business management]. So we wrote this business plan. In retrospect it was quite naïve, but it covered the fundamental principals of equity participation and we developed a budget of what it would take to get through the first year. The amount we came up with was $178,000. We actually took this little business plan around, I took it around to friends of my family who had money; personal friends that I knew that could afford something like this, but it was way too technical and too complicated for them. They had no clue as to what we were talking about and they were quite hesitant to get involved in something they didn’t know anything about.

Securing Venture CapitalSo we came up with the idea, let’s go talk to the venture guys that started Genentech [America’s first biotech company, based in South San Francisco on Herbert Boyer’s developments in gene splicing]. Through a personal contact we were able to get a meeting with Brook Byers, who was the junior partner at the firm, Kleiner Perkins. Brook came down with his partner Tom Perkins. We showed them the lab, we had a small little lab at the university and they

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liked the idea. We took them to the airport and we sat in the bar at the airport and we finalized the deal. There were two things they did. One is, they said, we know guys like you typically underestimate how much money you need, so we’re going to give you more than you asked for, we’re going to give you $300,000 instead of the $178,000. The second thing they told us is that neither one of us would be the president of our firm because we had no business background. With those terms we agreed. Since Ivor had never intended to leave the university we decided he was going to be a consultant to the company and would go on the board of directors. I elected to go and start the company as a full-time employee. Kleiner Perkins brought in a number of consultants and we broadened our concept from that of a research antibody company to a diagnostic/therapeutics company. We incorporated in September and we closed the financing on October 18, 1978.

Starting OperationsI left the University in October of ’78 to become the first employee of Hybritech as vice president. My last day at the university was on Friday and on Monday I went and rented a lab with an office over at what was then called the La Jolla Cancer Research Foundation. I had an empty lab and an office with a desk a chair and a telephone. I started ordering supplies and started interviewing people to hire. One of the first was a research scientist, a Ph.D., named Gary David, who was very proficient on the antibody side. Then one of the things Kleiner Perkins did was find a former McKinsey consultant who had worked at Baxter Travenol who had gotten excited about this whole monoclonal antibody thing and was in the process of trying to do a start-up that would have been a competitor to Hybritech. His name was Ted Green. They managed to convince him to join us rather than do his own startup. Ted came down and started as president. Brook was chairman. That was the initiation of Hybritech. By the end of that year we had gotten in all of our equipment, we had done our first experiments, and we actually had our first proof of principle antibody production going.

Protecting Intellectual PropertyWe founded Hybritech on a technology that was not patented. Gary David and Ted Greene were kicking around how you might use antibodies in the assay and came up with this idea of this sandwich assay which we could patent. We filed the patent sometime mid-year ’79. Today it would be highly unusual to start a company based on an unpatented technology where others could come in and compete with you. I think that one of the things that really did make Hybritech successful that was within a year we had filed a major patent, which protected the idea of using two monoclonals in a sandwich assay. It was upheld through several intensive court battles. Going through the court system really nobody thought the patent would be upheld, but it was. It prevented others from doing what we were doing.

The Cluster’s Strength: “Falling Off A Log”I think that the fact that there’s venture capital, management talent, and entrepreneurial attitude here in San Diego, coupled with the fact that you have these major research


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institutions within three square miles supports the whole reason that this cluster is here. Additionally, the networking here through the programs such as [UCSD’s] Connect and BIOCOM have created a situation where starting a company is like falling off a log. The network is so in place for not just the money, but the facilities and the legal support, both corporate and patent, the lab supplies, you name it. Everything is here, easily available and even if somebody has no clue as to what that is, there are so many people here that do know now and can help somebody who wants to do it. You’ve got serial entrepreneurs—Hybritech for some reason spawned a dozen or two-dozen serial entrepreneurs. The university Connect program bridged academia and industry.

Source: Howard Birndorf, Interview, April 16, 2004.

Yet succeeding far beyond what originally had been expected of it, Hybritech came to represent the most noticeable first step in economically elevating the region far beyond being merely a pleasant location for conducting not-for-profit biomedical research. In the wake of Hybritech, has come both a deepening and a broadening of the area’s commercial and R&D assets. Today it is accepted in a way unheard of some 25 years ago, that San Diego presents a suitable base for ambitious life science companies. The region now has what can be considered an interlocked and multilayered cluster that offers a uniquely entrepreneurial and creative dynamic generated by rivalrous and related firms and multiple sources of support.

One indication of Hybritech’s lasting impact on the cluster is the number of companies that can be traced back to former Hybritech employees. As of the 25th anniversary of Hybritech’s founding, the San Diego Union Tribune counted more than 50 firms (listed on following page) that could be considered the progeny of San Diego’s original biotech firm.

History

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1983 1. Gen-Probe

1985 2. IDEC Pharmaceuticals3. Clonetics 4. Pacific Rim Bioscience

1986 5. Gensia 6. Immune Response 7. Cortex

1987 8. Ligand Pharmaceuticals 9. Amylin Pharmaceuticals 10. Viagene 11. Lipotech 12. Corvas 13. Cytel 14. Pyxis 15. Vical

1988 16. Biosite

1989 17. Epimmune 18. Medmetric

1990 19. Dura Pharmaceuticals 20. Genesys

1991 21. Nanogen

1992 22. Sequana Therapeutics 23. Somafix 24. Cypros 25. Novadex 26. Applied Genetics

1993 27. Gyphen 28. Cyphergen

1994 29. Combichem 30. Digirad 31. Chromagen 32. Novatrix

1995 33. Collateral Therapeutics 34. Maxia Pharmaceuticals 35. Triangle

Pharmaceuticals 36. GenQuest

37. First Dental Health 38. Urogen 39. Nereus Pharmaceuticals

1996 40. Metabasis Therapeutics 41. Women First Healthcare

1997 42. Tandem Medical

1998 43. CancerVax 44. Genicon

2000 45. GenStar Therapeutics 46. Favrille 47. Ambit Biosciences

2002 48. Corautus Genetics 49. Verus 50. TargeGen 51. Kemia

2003 52. Somaxon 53. AnalgesX5

Expanding Cluster Assets and CapabilitiesAs stated at the beginning of this chapter, the birth of the San Diego life science cluster’s seeding technology enterprise represented both an end and a beginning: a cumulative payoff for concerted efforts to make the region an attractive base for biomedical research, as well as the start of an entrepreneurial and highly innovative industrial base that helped take the region beyond its economic dependence on tourism and defense spending.

Within five years of Hybritech’s founding, spinoff companies were being formed (the first, Gen-Probe, was co-founded by Hybritech employee number one, Birndorf, himself). Over time, the fortunes of the firm would vary. In 1986, Hybritech lost its independence with a $480 million acquisition by the pharmaceutical giant, Eli Lilly. The style of Hybritech’s pre-acquisition management team

5 Crabtree, Penni. 2003. “A Magical Place: Hybritech Launched San Diego’s Biotech Industry,” San Diego Union-Tribune, September 14, 2003: H-1.


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did not blend well with Lily’s more staid administrative practices. The remainder of Hybritech’s first-generation leadership eventually went on to pursue other endeavors. Though this signaled the final decline and later disappearance of Hybritech’s San Diego operations, the turn of events also immensely strengthened the cluster as the release of accumulated experience and wealth amassed by Hybritech alumni went into seeding a plethora of new enterprises and initiatives.

Chapters that follow in this report delve into the statistical data and economics behind the life science industry that since then has taken root in San Diego. Before exploring the numbers behind what makes the cluster what it is today, this chapter concludes by offering a brief glimpse into the thoughts of people who have made and are making the cluster so dynamic.

What follows is but a minute sampling of the experiences and observations related by the many cluster leaders who shared their valuable knowledge and insights with Milken Institute researchers. Containing brief synopses of their stories organized according to the roles they respectively played either in San Diego’s life science research community, the commercial life science industry, or the cluster’s support industry, the following pages give a direct feel for how the cluster has evolved and matured. A sentiment repeated by many of the leaders spoken to was that in San Diego’s knowledge-based cluster, it is people—more than the technology or institutions that give the region its infrastructure and wellsprings of capital—who are most crucial to the region’s success. The sampling of comments from cluster leaders that follows is intended to help round out an appreciation of the relevance of the science and economics of the area by putting contributing factors into a more human-based perspective. The background stories and comments also offer a sense of how the cluster has evolved in recent years and in what directions it might be headed.

Research Community LeadersRichard Murphy, president of the Salk Institute, has been in San Diego since 2000, having previously run McGill University’s Montreal Neurological Institute. The purpose of Murphy’s current organization, which relies heavily on funding from the National Institutes of Health (NIH), is to conduct basic biological research. This is a goal that has remained unchanged since its founding by Jonas Salk. Yet the operation has expanded greatly since then, integrating into the business of the area and adopting a particular management style to fit the institute’s evolving nature.

By its own estimates, the Salk Institute generates $100 million a year for the local economy. Its scientists have been involved in the founding of nearly 20 companies and developed 250 active patents that are being licensed to biotech or pharmaceutical companies. Although Salk researchers are prohibited from engaging in contracted research, they are given the freedom to integrate themselves closely with the commercial applications of their work. As Murphy explained: “We allow our faculty—and this is in accordance with NIH rules—to work one day a week off-site. (Don’t ask me how we know they only spend one day!) I think we’re very supportive of getting the technology that we generate, out into the marketplace and into the hands of people who can develop it for

History

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others to use and hopefully to create products. I mean, that’s part of the mandate of NIH. So we’re very comfortable with that.”6

As the head of an Institute that is defined by its leading-edge thinkers, Murphy (himself a renowned scientist) practices a style of management known as “Covert Leadership.” He characterizes the benefits of this approach in the following terms: “The one thing you don’t want to do is you don’t want to compete with your own scientists for attention or visibility. The way you want to do it is you want to stay in the background and you want to make sure the institute is running well but let the scientists be stars.” He also contends that keeping staff well-informed is key. “They don’t like surprises, and we don’t like surprises. So we have a lot of meetings. Part of it is that we’ve become very strategic. This morning I met with three people to say, ‘Here’s what I’m thinking, are you comfortable with this?’ Not only were they comfortable with it, but one of them came up with a much better modification that makes me look good. So to sit there and have those conversations with very bright people is quite important.”

Edward Holmes, dean of the University of California San Diego’s School of Medicine and vice chancellor for Health Sciences, like Murphy, is relatively new to the San Diego cluster. Holmes took his current position three-and-a-half years ago after serving as dean of Duke Medical School and, prior to that, dean for research at Stanford Medical School. The Medical School is a later addition to U.C. San Diego, established several years after the campus’ founding. Surprising, given the size of San Diego’s population and the area’s activities in biomedical research, Holmes is in charge of the only medical school in the region.

Yet the dean also sees advantages with the school’s relative smallness, as it “tends to put us in a good position to interact with other people.” With a faculty that only numbers 750, it means the school ranks around 15th in total National Institute of Health (NIH) dollars received. “But,” he is quick to point out, “if you look in research dollars per faculty member, we’re one, two, or three depending on the year.”7

Other statistics that Holmes cites in pointing to the school’s success include ranking number two in the impact of pharmacological research, three in molecular biology, and number one per faculty for membership in the National Academy of Sciences. Within the cluster, over 65 companies have spun out of the School of Medicine. “Another thing that’s special I think in San Diego,” he observes “is it’s a very entrepreneurial community. … UCSD reminds me of what I would have guessed Stanford was 20 years ago.”

All the same, Holmes believes that much more can be done to leverage UCSD’s diverse academic resources. “My sense is there’s an opportunity for us that we haven’t capitalized as much on it as

6 Interview, May 4, 2004.7 Interview, April 14, 2004.


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we might. We have really extraordinary strengths here in computation with the San Diego Super Computing Center and with one of the state’s centers of excellence for information technology, Cal IT2. It has brought tremendous expertise to this community in things like bioinformatics, and in imaging. I think for the future of both biomedical research but also for [information] technology development imaging is very, very important.” Recent progress in combining UCSD’s biological and computational resources is a source of encouragement, however. Holmes notes advances being made in Functional Magnetic Resonance Imaging (FMRI, a noninvasive way to look at biological functions) and Positron Emission Tomography (PET, a means for labeling a compound to trace where it goes in the body).

Life Science Industry LeadersAfter the acquisition of his Connecticut-based gene therapy company in 1993, Henry Nordhoff joined Gen-Probe (the first of the Hybritech spin-offs) as its president and CEO in 1994. At the time of his appointment, Gen-Probe was operated exclusively as a diagnostics company but has since branched out into blood screening. By internal company estimates, it now occupies about 90 percent of the market for screening the U.S. blood supply (donated blood that is checked for viruses such as HIV, hepatitis C, and West Nile). Last year the company earned over $200 million in sales. It employs about 850 people locally and invests heavily in research, with nearly one-third of revenues going toward R&D.

Despite the Gen-Probe’s strong research orientation, Nordhoff himself does not have formal scientific training, but rather learned the craft of the life science industry through previous work experience at the leading pharmaceutical company, Pfizer. Reflecting on his background and how it relates to the cluster overall, the CEO remarks: “I’ve tried to stay out of the science. Let the experts do the science. And I’ll just step back and just use some rationality and judgment and make sure everything hangs together. … I think there are others like me, you know with business type backgrounds; others are scientific. It would be interesting to see if there is a correlation of success between leaders with those different backgrounds. It probably doesn’t exist, it probably just depends on the personality, on the managerial style …”8

Despite his lack of formal scientific training, Nordhoff takes an approach to recruiting and motivating Gen-Probe’s highly skilled workforce in a style reminiscent of the leaders of highly innovative research organizations. As he states: “We try to get the best people we can. We try to empower them as much as we can. … We’re big on communication, and we are big on openness, you know, clarity, transparency, telling the people what we are doing, our strategic plans, and all that. We single out the key managers, a group of about 65 to 80 managers who are below the VP executive level, speak to them, and try to get dialogue from them, tell them what we are doing, ask

8 Interview, April 2004.

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them for comments. We do that every couple of months.” The key to his company’s—as much as the cluster’s—success, Nordhoff asserts, is “people. … The right blend of people, support and opportunity.”

Salmedix’s David Kabakoff first came to the area in 1974 as a research fellow at UCSD, where he conducted his post-doctorate work under Nathan Kaplan, a biochemist renowned for his advances in enzymology and chemotherapy. Kabakoff left the area after completing his post-doctorate but was brought back when recruited to join Hybritech in 1983. By the time he left the firm six years later he was serving as senior vice president of research and development-diagnostics. From there he moved to Corvas International, a biopharmaceutical company, and served as its CEO before later moving to Dura Pharmaceuticals, a specialty pharmaceutical company, that was eventually acquired by Elan Corporation. Cofounding Salmedix, an oncology drug development company, in 2001, Kabakoff now serves as its president, CEO and chairman.

A three-year-old, 36-person company, Salmedix maintains close ties to UCSD. In addition to several licensing agreements, the company’s core science originated at UCSD and one of its founding scientists, Dennis Carson, directs the university’s Moores Cancer Center. Relating his company to the cluster and its evolution, Kabakoff observes: “The company itself is an active member of the local trade association [BIOCOM], the UCSD Connect Program, and if you look at the employee base, I think pretty much every employee here has worked for at least one or more previous San Diego employers, with a few exceptions. We’re located in town, so many of our employees have either worked at the university or, even more of them, at other local companies ... as the community has grown up since the early 1980s, people who have been in one company have moved to another company and then moved to another company. I would say within Salmedix, you have a fairly typical set of connections.”9

Mike Borer, the president and CEO of the specialty pharmaceutical company Xcel Pharmaceutical first came to San Diego in 1977 as an undergraduate at San Diego State University. Majoring in finance, he spent 12 years in public accounting, alternating between Denver, Colorado, and San Diego. He ultimately entered the pharmaceutical business by joining Dura Pharmaceuticals in 1994. After Dura was sold to Elan Pharmaceuticals in 2000, Borer and some of his former Dura colleagues decided to form Xcel.

Having graduated from a local university and moved on from one San Diego company to another, Borer fits something of the typical profile for an executive with long-experience in the cluster. At the same time, with Xcel Pharmaceutics, he is developing a business model that is fairly unique. As he explains: “We are not what I would consider a biotech or true biopharmaceutical company. We have a significant commercial operation and are pursuing late-stage product development, but we have no part in the research, basic research, or early research or even early development within our

9 Interview, April 16 and 21, 2004.


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business model. I think we’re the minority within the pharmaceutical and life sciences side of [this cluster] in that we started as a commercial organization. … Most of the companies in San Diego really have come traditionally through the research and also development side of things, only in some select cases through a focus on commercialization.”10

The presence of a company like Xcel testifies to the recent broadening of the cluster in terms of operational models. Xcel represents the emergence of commercially focused pharmaceutical production, something that had largely passed the cluster by, during its early phase of growth. Another, more frequently commented on, recent development is the growing presence of the operations of large pharmaceutical corporations, “Big Pharma,” which have been establishing an increasingly large and numerous research footprint in San Diego.

One of the best examples of this comes from the purchase by Warner-Lambert of San Diego’s Agouron Pharmaceuticals, which had the distinction of being the first biopharmaceutical company in San Diego to market a therapeutic drug from its own research. Warner-Lambert bought Agouron in 1999 for $2.1 billion. Within a year-and-a-half, Warner-Lambert was in turn purchased for $90 billion by Pfizer, which inherited its San Diego facilities. As Catherine “Kitty” Mackey, the head of Pfizer’s La Jolla Laboratories, states: “Pfizer had wanted to have an R&D location in California for many years; we’ve been looking for an opportunity to be in California. So this was very much a welcome part of the Warner-Lambert acquisition, the Agouron acquisition. And so when Pfizer became the owner, we invested quite a bit in terms of expanding the facility here and really put down roots and made a commitment to stay.”11

Pfizer La Jolla is now the fourth largest R&D site for the global drug company, currently contributing about two dozen potential medicines to the company’s development pipeline. Although complaints are sometimes heard that the presence of Big Pharma in the cluster necessitates the “selling out” of once promising locally based independent firms, it can also be said that the investments of capital and human resources by the pharmaceutical giants is adding significantly to the stature and capacity of San Diego’s life science industry base. As Mackey points out: “Within the community here, we have a number of different relationships. I just got a list the other day of the various collaborations that Pfizer has with biotechs. … In terms of universities, I wish I could keep track of it because it’s funny, with UCSD there’s so many different touch points. I wish there was a database—UCSD wishes there was too—to keep track of this, but you know the scientists just call each other up and they’re doing all sorts of things.” Mackey also remarks on the value of working closely with Ed Holmes and UCSD School of Medicine, “exploring at this point a number of different ways that we can collaborate.”

10 Interview, April 16, 2004.11 Interview, April 14, 2004.

History

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Support Industry LeadersSince arriving in San Diego in 1977 as an assistant professor of medicine at UCSD, Ivor Royston has made tremendous contributions to the San Diego cluster as a researcher and business innovator. He began his latest enterprise, Forward Ventures—what is today the major life science-dedicated venture capital firm in the San Diego region—in 1990. From starting what he considered a “hobby fund” with himself as general partner and limited partners made up of family and friends, Royston’s firm has since come to manage an institutionally invested series of venture capital funds, the latest being his fifth-generation Forward Ventures V.12

“We are part of the fuel of this biotech industry here,” Royston explains. “Whereas back in the 1970s, there was no venture capital firm here, we had to access venture capital from the Bay Area. But that’s now changed. There are a handful of firms in San Diego that do both IT and biotech. But we’re a specialized biotech investment firm. And what I do now is to use my experience from a quarter of a century of being involved with the biotech industry to help other scientists develop their ideas and transfer of technology out of institutes and universities into companies.”

While acknowledging the importance of the cluster’s capacity to generate cutting-edge science, Royston stresses how having capable people, more than brilliant technology, has built up the cluster. “My experience, which goes all the way back to Hybritech, has brought me in contact with many, many different people. Probably the most important thing I’ve done is tap individuals to take on managerial responsibilities in companies that I’m working on. So, a good example of that would be recruiting David Hale, who was the CEO of Hybritech, to become the CEO of one of my new companies, Cancervax, which just went public. I know from my experience going back to Hybritech that, number one, management is far more important—significantly more important—than technology. Many times I’ve seen technology fail and management teams win by coming up with other technologies to work on. But it doesn’t work so much the other way: I’ve seen companies get ruined by having the wrong management teams.”

When asked to provide one word that describes the San Diego life sciences cluster, people interviewed for this study tended to respond with words that relate to a sense of creative dynamism and shared purpose: for example, words such as “entrepreneurial,” “collegial,” “innovative,” and “interactive.” Among various programs, initiatives, and organizations established to reinforce and build upon the core dynamics of the cluster, BIOCOM represents the cluster’s leading networking and advocacy organization. With more than 450 member companies, BIOCOM claims to be the largest regional life sciences association in the world. As Joe Panetta, president and CEO of BIOCOM, asserted, his organization plays a variety of strategic roles in support of the cluster:

12 Interview, May 3, 2004.


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I think that first and foremost BIOCOM is an organization that brings together the entire industry and the service sector upon which the industry depends to be able to grow and to accomplish its goals. And when I say BIOCOM brings the industry together, we do this in more than one way. The obvious way is we hold different events that allow people to come together and network with each other. That’s fine if you simply want to allow random motion to provide the chance for people to interact with each other. But we’re also very focused on areas like providing advocacy and information to the public, the legislators, and the media and others who need to be informed about what the industry is all about, what the industry is out to accomplish, and what the challenges are. Beyond that we know that we have to build this industry in San Diego through our relationship with the service providers that are here and the ones that we can hopefully attract to San Diego. BIOCOM focuses on bringing new venture capital investment to San Diego, as well as attracting pharmaceutical companies, partnerships, and investment banking. We also focus on creating the opportunities for future jobs by working with the universities and the colleges to insure that curriculum and training programs are being created for the biotech workforce of the future.13

Indicative of the cluster’s success in attracting service providers that support the cluster is the San Diego presence of San Francisco-based Cooley Godward, one of America’s premier technology law firms. After getting involved with a locally based venture capital fund established by Hybritech alumnus Howard “Ted” Greene, the firm decided that activities in San Diego justified a direct presence and so opened an office in 1992.

Joining the firm as a founding partner of its San Diego office was Wain Fishburn, a local attorney who has built up substantial experience with the legal and financing needs of the biotech companies that had been springing up since the 1980s. Speaking of the benefits his office has been able to bring to the cluster, Fishburn remarks that one of the main advantages is “just very deep expertise and experience with, for example, public offerings and venture financing. Also, something that is very unique in the representation of biotech companies, strategic alliance capability. Because one of the things about a biotech company is that it is very much a function of a contract relationship. So you start with the relationship between either Scripps or UCSD or Salk and you bring technology from those research institutes into the company so there’s agreement to come there. Then there’s the agreement with the money coming in, the venture capital financing agreements. Then, as things progress, you’ve got the agreements for the strategic alliances with the pharmaceutical companies. And those are really the ingredients that go into ultimately helping form a successful company.”14

Fishburn sees one of the greatest strengths of the cluster to be its closeness, both from a geographic standpoint and in terms of synergism. “All of us that are in this industry are within a 10-mile radius of our office in the Golden Triangle,” he observed. (See map, previous.) “At the time we opened in 1992, we were the first law firm of any substance to open an office outside of downtown.” Yet the pluses to being close to the center of action around the Torrey Pines Mesa have been readily apparent. Compared to the situation in the Bay Area, where, Fishburn notes, the driving distances between the East Bay, San Francisco, and lower down the Peninsula can be substantial, in San Diego it is “possible for you to call a meeting and have everybody who mattered be in a room within 20

13 Interview, April 14, 2004.14 Interview, April 15, 2004.

History

26

minutes.” He is also hopeful that the intense dynamic that has developed in the central territory of the cluster is managing to spread. “I think what’s interesting in terms of the dynamic of San Diego is we’ve now emerged even further so that the cluster, if you will, has gone from the Golden Triangle and the Torrey Pines Mesa and the Mira Mesa Corridor, and is now reaching up to Carlsbad and Oceanside.”

Teresa Young, partner at Deloitte in San Diego, has been active in the region’s life sciences cluster longer than anyone interviewed for this study. She arrived in 1969 as an undergraduate at UCSD studying chemistry. It was a combination of positive factors that still typify the cluster today that originally brought her to the area: outstanding human capital (UCSD professors Linus Pauling, a Nobel Laureate in chemistry, and biologist Paul Saltman, one of the university’s visionary early leaders, were especially influential), the life science community’s relative smallness and collegiality, and the area’s natural beauty. Despite later growth of the cluster and various issues that have arisen as a result, she believes that the cluster’s ability to attract talent endures. “I see very few people wanting to leave San Diego,” she observed. “I think I’m a good example of that, being here for 35 years. People who came in the ’60s, the ’70s, the ’80s, the ’90s—they don’t want to leave.”15

After obtaining her bachelor’s degree, Young worked in the laboratories of the Salk Institute for several years. Rather than continue in research science and study for a PhD, she opted to go for a master’s in accounting at San Diego State University. From there she joined Deloitte, eventually rising to her current position as partner and co-leader of its Southwest Pacific regional life sciences practice. She noted from her own professional experience within the firm that one of San Diego’s distinguishing features is a heavy concentration of life science research organizations. “When I talk with colleagues in the country who are serving other biotechs, I know that they may be working with one or two research institutes, whereas I may be working with five or six of them.”

Reflecting on the lessons that the San Diego cluster might offer other regions, she acknowledged that although “San Diego does have a very unique set of circumstances,” she nevertheless feels that long-term dedication and commitment to the cluster—features that are universally applicable—also have been crucial. She emphasized that the cluster “really was a long time in the making.” Young also is excited about the particular juncture in its evolution at which the cluster currently finds itself, a period in which all the commitment and dedication that has been given to the region’s development is starting to pay off in greater and greater ways. “I work with a number of companies that have been running R&D for as long as 10 or 15 years,” she observed. “They really are now on the cusp of having commercial products; a few have even just launched. So I’m actually very optimistic about things because now these companies are going to start generating revenue and that is going to attract additional capital as investors see what these companies are doing. In 2005, 2006, and 2007, we’re going to see a lot of success stories.”


15 May 25, 2004.

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The Biotechnology Innovation Pipeline IndexThe term “biotechnology innovation pipeline” refers to the support infrastructure and outcome measures that reflect the ability of an area to capitalize on its strengths in biotech knowledge and creativity. A rich innovation pipeline plays a pivotal role in a region’s biotech and life science industry gestation, commercialization, competitiveness and ability to sustain long-term growth. It also constitutes an important socio-economic asset to regional, state and national economies. This section of the report analyzes the innovation pipelines of key metropolitan areas with a view toward determining their capacities to create and commercialize biotech and life science innovations.

Much of the following analysis is based upon comparing and contrasting San Diego to other top biotech clusters that lead in concentrations of biotechnology, life science and related economic assets. In the innovation pipeline analysis section, we offer a brief description of each indicator, explain why these indicators are important, and give a summary of San Diego’s position relative to other top biotech clusters. Even with the focus on top-performing metropolitan areas, all metropolitan areas can benefit from the information generated by the index.

We begin with the biotech research and development (R&D) assets that can be commercialized for future metro and state biotech growth. A metro’s biotech risk capital and entrepreneurship infrastructure determines the success rate of converting biotech basic and advanced research into commercially viable biotech services and life science products. The most important intangible asset to a biotech economy is its biotech and life science human capital. The intensity of the biotechnology and life science workforce demonstrates the depth biotech talent on the ground. By measuring these biotech and life science components we are able to assess the effectiveness of policymakers and other stakeholders in transforming regional biotech assets into regional prosperity.

The Biotechnology Innovation Pipeline Index

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Biotech R&D Assets

Background and RelevanceResearch and development (R&D) assets are widely recognized to be the pipeline of technological innovation, and levels of R&D expenditures are accepted as reliable indicators of innovation capacities of places.16 A region with a better R&D infrastructure has a comparative advantage when it comes to building new industrial clusters, and attracting tech-based firms and an educated workforce.

Internationally, U.S. R&D efforts are remarkable by comparison. In 2000, U.S. R&D expenditures surpassed the total of other G-7 countries, including Japan, Germany, France, United Kingdom, Canada and Italy. Despite the recent slowdown in industry-financed R&D, U.S. total R&D maintained positive growth rates in 2000 and 2001 with steadfast gains in federal R&D expenditures.17

Information technology sectors (e.g. telecommunications, computers and electronic products), which witnessed impressive increases in the late 1990s, experienced declines in R&D investment in 2001 and 2002. Meanwhile, industrial R&D expenditures in the biotech industry increased throughout those periods. Currently, the U.S. biotechnology industry is expanding rapidly, similar to the pace exhibited by the computer technology and telecommunication industries during the last two decades. As R&D inputs have played an important role in creating and maintaining computer and telecommunication clusters, so are they now taking a critical part in building up biotech centers in the U.S.

R&D assets are vital for biotech more so than any other industrial sector, primarily because biotech, especially in its early stages, is intensely dependent on basic research. This type of research takes place at strong academic research institutions and medical research facilities by biotechnological scientists with the substantial support of public funding. Biotech research universities and institutions are the melting pot that combines biological scientists, medical engineers, research funding and new ideas into biological inventions and products.

The biotech industry’s relationship with R&D assets does not diminish as it goes into applied research and commercialization stages. The biotech or biopharmaceutical approval process is both lengthy and costly. It takes, on average, 12-15 years to go from initial—or preclinical—development to commercial approval,18 which requires substantial applied research feedback from biotech

16 DeVol, Ross C., Rob Koepp, John Ki and Frank Fogelbach. 2004. California’s Position in Technology and Science –A Comparative Benchmarking Assessment, Santa Monica: Milken Institute.17 Shackelford, B. 2002. “Slowing R&D Growth Expected in 2002,” InfoBrief, Arlington, VA: National Science Foundation (NSF-03-307). 18 DiLorenzo, F. 2002. Industry Survey: Biotechnology, New York, NY: Standard & Poor’s.


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research institutions, biotech scientists and engineers. Thereafter, biotech commercialization also tends to locate where there are strong R&D support structures such as R&D contracts and funding arrangements.19

In this study, R&D assets consist of nine components that are mostly relevant to the growth of biotech research and the emergence of entrepreneurial vibrancy. The components included are academic R&D to the biotech industry, National Science Foundation (NSF) funding to biotech, the Small Business Technology Transfer (STTR) program, the Small Business Innovation Research (SBIR) program, competitive NSF funding rate for biotech-related proposals and National Institutes of Health (NIH) funding to metros, research institutes and research universities.

Academic R&D demonstrates the importance of university research as well as the capacity of each metro’s university system. Academic R&D focuses on basic rather than applied research, thus it is particularly significant to the biotech industry, which is still in its early commercialization stage. In 2001, academic R&D expenditures on biotech sectors totaled $16 billion in the U.S.

The National Science Foundation (NSF) is a key public investor in the technological progress and intellectually creative people. NSF funding to biotech sectors accounts for about 11 percent of total NSF support to academic and research institutions, or roughly $547.1 million for year 2003. As a result, NSF financial assistance of world-class biotech scientists and biotech research institutions has led to breakthroughs in the field of biotechnology. While the average funding rate for competitive NSF funding proposals in 2003 was 27 percent; it was 26 percent in biotech. Without NSF project funding, the range and quality of biotech research in colleges, universities and research institutes would be very limited.

The Small Business Technology Transfer (STTR) program is aimed at extending the participation of small businesses in federal R&D and encouraging private sector commercialization of technology with federal assistance. The STTR award program plays a pivotal role in small biotech firms and research organizations while helping to strengthen their scientific and innovative capacities.

The Small Business Innovation Research (SBIR) award is a federal program designed to support private sector R&D through a set-aside program allocated for cutting-edge technology at small businesses that has not yet become commercially applicable. SBIR awards are granted based on need and new ideas that have commercialization potential. SBIR awards raise the level of entrepreneurial creativity among small biotech firms and provide them with opportunities to commercialize new knowledge not yet viable.

Although there are several governmental funding sources for biotech research, the National

19 Cortright, J. and H. Mayer. 2002. Signs of Life: The Growth of Biotechnology Centers in the U.S., Washington, DC: The Brookings Institution.


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Institutes of Health (NIH) is the largest single funding agency releasing $17.0 billion to a variety of biotech and medical research centers in 2002. Much of biotech research has been conducted at biotech research institutions and medical schools with the substantial assistance from the NIH.20 According to Dean Holmes, “NIH is probably more relevant to biotech than NSF itself, because NIH is health, while NSF is all of basic science, some of which is health, but a lot of it is physics, mathematics and engineering,” adding “NIH is the major fuel for biotechnology in the country.” NIH plays a pivotal role in igniting biotech research initiatives and elevating biotech discoveries by supporting regions with sufficient research facilities to attract talent and additional funds.

Metro FindingsSan Diego has particular strength in biotechnology research and development assets. Many San Diego-based biotech and life science firms are devoted to R&D, either basic or applied, and they are seeking more R&D funds and support. Borer emphasized the role of biotech R&D companies in driving the San Diego economy, saying, “Most (biotech) companies in San Diego really have come traditionally through R&D and in some select cases commercialization. The number of R&D biotech, bio-development companies is vastly greater in San Diego than the commercial.” And this trend seems to be continuing as David Kabakoff, CEO of Salmedix, put it, “In our community you’re going to see more companies having started in R&D.”

At $102 allocated per resident, San Diego ranks 8th among the 12 metropolitan areas in terms of academic R&D dollars in biotech fields per capita. San Diego is running slightly behind 7th-place Philadelphia’s ($103) and 6th-place Boston’s ($107) positions. San Diego’s lagging position in this component represents its relatively smaller number of research universities and higher dependence upon the University of California at San Diego (UCSD). UCSD garnered almost 93 percent of San Diego’s total academic R&D in the biotech field for year 2001. Raleigh-Durham-Chapel Hill with its strong university system awarded more than $480 per capita placing it at the top of this component, followed by San Francisco ($295).

NSF biotech funding to San Diego amounted to $10.2 per $100,000 Gross Metro Product (GMP) in 2003. In this component, San Diego ranked 2nd, behind top-ranked Raleigh-Durham-Chapel Hill, which earned an indexed $38.3. Oakland’s indexed $10.0 and Washington, D.C.’s $9.6, rank them in 3rd and 4th-place, respectively. Contrary to its weaker academic R&D position, strong NSF funding to biotech is a definite indication of San Diego’s comparative strength in biotech research beyond academic boundaries. Although San Diego possesses relatively weak academic R&D assets, it hosts a variety of biotech businesses and biotech institutes that undertake basic and applied research, and focus on commercialization of the outcomes.

20 Ibid.


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In the case of STTR awards to biotech firms per 100,000 businesses, San Diego ranked 2nd among the 12 metropolitan areas studied. Statistically, San Diego had 21.4 STTR awards to biotech firms per 100,000 businesses in 2000. Despite its 2nd-place ranking, the metro finds itself far behind top-ranking Boston that had nine times more awards in absolute numbers (160 to 17) and was four times larger in relative terms (89.6 to 21.4) than San Diego. San Jose and Seattle ranked 3rd and 4th, respectively, with 14.1 and 9.7 STTR awards per 100,000 businesses. As in the case of STTR awards to biotech per 100,000 businesses, San Diego ranked 2nd again in STTR award dollars to biotech firms per $1m GMP. San Diego’s indexed amount is $25.9 per capita. Boston, as the top-ranking metro in the component, recorded $144.3 per capita, more than five times greater than San Diego. Los Angeles-Long Beach and Washington, D.C. ranked 3rd and 4th, which received $18.2 and $15.6 per capita in STTR awards granted per $1m GMP, respectively. San Diego’s relative strength in STTR awards to biotech firms illustrates that its small-sized biotech businesses are recognized for their scientific and innovative efforts.

San Diego ranked 2nd according to the number of SBIR awards for biotech granted per one million people in the population for the year 2000. San Diego’s indexed statistic was 60, followed by San Jose and Seattle, at 47 and 41 per million people, respectively. Biotech SBIR awards were granted in the Boston area at a rate of 263 biotech SBIR awards per one million people. In absolute terms, the number of Boston’s biotech SBIR awards (139) is more than the total sum of the other 11 comparison metros (94).

San Diego’s competitive NSF funding rate in the biotech field is 39.3 percent. This places the metro 3rd among the 12 comparison metros. The top two metros are Washington, D.C. and Austin-San Marcos, in which the percentage is 42.7 and 41.0 percent, respectively. NSF funding to biotech has vital strategic value in its strong support of basic biotech research projects that the private sector tends to eschew. Higher competitive NSF funding rates implicitly recognize that the regional innovative potential for upcoming biotech development and commercialization is high.

For the year measured, FY 2002, San Diego received $937 million in NIH R&D money, the second highest sum among the 12 selected metros. Averaged out per capita, San Diego received approximately $323 per capita in NIH money for research and development activities. San Diego’s ranking remained 2nd, followed by Boston ($288) and Seattle ($260). Raleigh-Durham-Chapel Hill took the top-ranked position for this component with $499 per capita in NIH funding.

NIH funding to San Diego’s biotech research institutes confirms its dominant position in this critical area. San Diego research institutes were granted $316 millions in NIH funding in 2002, which is the highest amount among the 12 selected metros and 17 percent of total NIH funding to research institutes. San Diego’s major NIH-funded biotech research institutes include the Scripps Research Institute, the Salk Institute for Biological Studies, and the Burnham Institute. Scripps Research


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Institute received $191 million for year 2002, the highest NIH-funded biotech institute nationally. Averaged out per 100 people, San Diego still ranks 1st among the 12 selected metros. San Diego had 12 research institutes awarded NIH institute funding for 745 NIH projects in 2002. San Diego plays a significant role in attracting NIH funding to California. In California, San Diego represents 26 percent of NIH awarded institutes, 61 percent of NIH awarded projects, and 59 percent of NIH funding money to institutes.

Adjusted per $10,000 of GMP, San Diego is granted $17.0 of NIH funding to research universities. This amount positions San Diego 5th among the selected 12 metros. Other top ranked metros are university-oriented Raleigh-Durham-Chapel Hill ($79.3), Philadelphia ($25.5), and San Francisco ($22.9).

San Diego’s composite score for biotech research and development inputs is 79.7 (out of a perfect score of 100) before rebasing the top score to 100 for comparison purposes, which positions the metro as top ranked among the 12 selected metros. As Pfizer Global R&D’s Catherine Mackey implied, San Diego might be the best location for biotech R&D in California, noting, “Pfizer had wanted to have an R&D location in California for many years, looking for an opportunity to be in California. (Finally) we invested here (San Diego) and really put down roots and made a commitment.”

San Diego’s relative advantages in the composite score come from its attractiveness to public R&D funding such as NSF for basic biotech research and NIH for advanced research. San Diego also benefits from commercial opportunities for biotech research. San Diego’s superior rankings in the relative biotech STTR and biotech SBIR statistics confirm regional effectiveness in commercializing R&D efforts and new ventures. Boston ranks 2nd with a composite score 78.9 (or a rebased score of 99) and Seattle, 3rd, followed by Raleigh-Durham-Chapel Hill, 4th among the 12 competing metros.

An important biotechnology R&D measure that is absent from our analysis is industry-performed research and development. Industry figures are not publicly available due to confidentiality concerns. Biotech clusters with key anchor firms are likely to have higher levels of industry-performed R&D. If industry R&D funding data was available, Boston and San Francisco would likely be well positioned. It is possible that Boston might edge past San Diego for 1st in overall biotechnology research and development, and San Francisco’s position would undoubtedly improve, too. Nevertheless, most San Diego-based biotech firms invest considerable R&D money. Henry Nordhoff, CEO of Gen-Probe, acknowledged, “In the year 2000 we spent 48 percent of revenues on R&D and even last year (2003) we spent 32 percent of revenues on R&D. We invested heavily in research and development.”


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AustinOrange

OaklandSan Fran.

L.A.San Jose

D.C.Philadelphia

RaleighSeattle

BostonSan Diego

90

80

70

60

50

40

30

Level

Source: Milken Institute

Biotech Research & Development AssetsTwelve Selected Metropolitan Areas, 2004

20 30 40 50 60 70 80 90 100San Diego's Statistics

1

2

3

4

5

6

7

8

9

10

Biotech Research & Development AssetsSan Diego's Score

Series2 79.7 74.9 63.7 68.2 65.5 73.5 97.8 93 100 64.7

1 2 3 4 5 6 7 8 9 10

NIH Funding to Research Universities (US$ Per $10,000 GMP)

NIH Funding to Institutes (US$ Per 100 Pop.)

NIH Funding to Metro Cities (US$ Per Capita)

Competitive NSF Funding Rate in Biotech Fields (Percent)

SBIR Awards to Biotech Firms (Per Million Pop.)

STTR Awards to Biotech Firms (Per $Million GMP)

Number of STTR Awards to Biotech Firms (Per 100,000 Businesses)

NSF Funding to Biotech (US$ Per $100,000 GMP)

Academic R&D to Biotech (US$ Per Capita)

Biotech R&D Assets Component

San Diego

U.S. Avg.

1 2

102.3

56.562.5

3 4 5 6 7 8 9 10

10.2 21.4 25.9 60.0 39.3% 322.5 10,878 17.0

5.8 N/A N/A N/A 26.0% 60.0 634 10.2

79.7


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MethodologyIn data collection and analysis, we focused on 12 metropolitan areas that showed the greatest specialization and concentration of biotech industry in the U.S. To compare the relative strength of each metro’s biotech research and development asset, we scaled out each component by population, employment or gross metro product (GMP), such as, the San Diego metro’s academic R&D dollar (to biotech) per capita. After such adjustments, we compared the relative scores of the 12 metros and ranked them.

Many previous studies based their findings upon absolute measures of indicators.21 By converting them to relative measures, a more accurate representation of the richness of the clusters is revealed. Additionally, we utilized the smaller geographic area represented by metropolitan statistical areas (MSAs), which appropriately reflects the density of a biotechnology cluster, although a compelling case can be made that the larger consolidated metropolitan statistical area (CMSA) is appropriate when it can be demonstrated that there is a high level of interaction such that they act has a regional network of clusters. Our organizing principle for this study was to measure which biotech clusters were the densest and most tightly compacted, but at the same time have sufficient scale.

The National Science Foundation (NSF), Small Business Administration (SBA), and National Institutes of Health (NIH) were three major sources of data used to compile and analyze the nine components of this section. Academic R&D to biotech, NSF funds to biotech, and competitive NSF fund rates to biotech were collected from NSF data banks. STTR and SBIR statistics were obtained from the office of advocacy, a department of the Small Business Administration. National Institutes of Health’s database was employed to obtain NIH funds to metros, institutes, and research universities in the 12 selected metropolitan areas.

21 Ibid.


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Risk Capital & Entrepreneurial Infrastructure

Background and RelevanceEntrepreneurial capacity and performance are major players in the new economic milieu in which creativity and innovative dynamics determine the competitive advantage of a firm and an industry. Risk capital and entrepreneurs are pivotal because new firms or spin-offs are the best breeding grounds for new ideas.

The Index’s Biotech Risk Capital and Entrepreneurial Infrastructure component consists of 10 sub-components, each portraying essential aspects of the business climate for biotech start-ups and biotech entrepreneurial activities. The Risk Capital and Infrastructure component aims to evaluate the selected metros’ entrepreneurial biotech culture by the numerical analysis of risk capital measures like bio venture capital investment, and patents issued and cited in the field of biotech. Other measures that gauge the effects of biotech entrepreneurship are biotech business starts and Fast 500 companies in the life science field.

Venture capital targets young and fast-growing businesses that demonstrate potential for high return on investment. As an important source of equity funding for start-ups, venture capital has a history of funding new technologies and innovations. These are the most risky investments, but can offer high returns. Venture capitalists supported fledgling semiconductor firms and personal computers, followed by the disk drive industry, biotechnology in the early 1990s, software in the mid-1990s and dot-coms at the end of the decade.22 Leading biotech firms such as Genentech and Amgen are among those who benefited from early-stage venture capital investment.

Venture capital investment in biotech research is evaluated on four features: biotech venture capital investment growth (2000-2003), number of companies receiving venture capital per thousand biotech firms, growth of biotech companies receiving venture capital and biotech venture capital dollars per $100,000 of GMP. All these venture-capital components are important indicators for measuring current venture activities in the metropolitan areas. Although venture capital funding has been in a slump since the technology-stock-driven market bubble in 2000, venture capital still remains a pivotal force for investing in new businesses, especially those that operate knowledge-intensive industries like biotech and other life sciences.

22 DeVol, Ross C., Rob Koepp, John Ki, Frank Fogelbach. 2004. California’s Position in Technology and Science–A Comparative Benchmarking Assessment, Santa Monica: Milken Institute.


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A patent is the grant of a property right to its inventor by the Patent and Trademark Office (PTO), a division of the U.S. Department of Commerce. Patents granted does not ensure the right to make, use, offer for sale, sell or import, but the right to exclude others from making, using, offering for sale, selling or importing the invention. That is, the major purpose of patent issuance is to protect and preserve various forms of individual and company property, both tangible and intangible. The term of a new patent is 20 years from the date on which the application for the patent was filed in the PTO. Though patent issuance does not directly represent regional creativity, it is well linked to a region’s knowledge-intensive economic capacity.

A patent citation is the reference to a patent from subsequent patents, which indicates the technological impact and knowledge spillover of a patent. As Adam Jaffe, professor of economics at Brandeis University and his colleagues put it, a citation of patent X by patent Y means that X represents a piece of former knowledge upon which Y builds.23 High citation counts are often linked with significant inventions, ones that are vital to future inventions. Companies or individuals with highly cited patents may be more advanced than their competitors, with more valuable patent portfolios.

For the purposes of this study, patents and patent citations are limited to the biotech fields. They are then scaled out by population size or biotech employment size of each metropolitan area. When scaled out for a metro’s population or biotech employment, the number of patents issued (or cited) serves as a measure for how innovative and commercially viable the people (or biotech workers) of a metro are.

Business starts data is a clear indicator of a metro’s entrepreneurial dynamics. A metro’s capacity to create jobs reflects its financial availability for new start-ups, business-friendly cultures and abundant entrepreneur pools. A metro’s successful performance in new firm formation also connotes the regional R&D readiness for commercialization. In 2002, averaged out on the basis of 1,000 businesses, the number of business starts is around 21 in the U.S.

The Deloitte Technology Fast 500 list shows North America’s fastest growing technology firms in terms of revenue growth for the last five years (1998–2002). The Technology 500 list identifies innovative, rapidly expanding firms that promise long-term technological and economic impact. Additionally, it indicates the depth of managerial capabilities needed to maintain high rates of growth as firms mature. To be eligible for the Technology Fast 500, a firm must meet a combination of subjective criteria such as revenue requirements.

Among all Technology 500 firms, life sciences shows good progress with a 19 percent share as compared to 18 percent in the Internet field and 16 percent in the communications and networking

23 Jaffe, A., Trajtenberg, M. and Henderson, R. 1993. “Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations,” The Quarterly Journal of Economics, 108(3): pp 577-598.


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sector. The life sciences field rose on the Technology 500 list from 15 percent in 2001 to 16 percent in 2002 to 19 percent for the year 2003. Eighty-four of the life science firms on the Technology Fast 500 list are U.S.-headquartered.

Metro FindingsSan Diego’s biotech community realizes that San Diego offers a good infrastructure to support early stage companies, especially those in the life science field, says Steve Mento, president and CEO of Idun Pharmaceuticals. Entrepreneurship is an obvious landmark of the San Diego biotech business atmosphere. As Mackey remarked, “San Diego distinguishes itself by having a win/win mentality, very entrepreneurial, and very willing to try new things.” Lisa Haile, an attorney with Gray Cary Ware & Freidenrich, a San-Diego based law firm that represents a number of biotech firms in the area, concurred adding that, “What has happened between the past and now is that many companies have been started from the academic research centers and that was not so common at all even a decade ago.” The San Diego biotech and life science community is passionate about making things happen and creative enough to continually innovate.

San Diego ranked 5th among the 12 competitive metros in growth of total venture capital invested, falling 10 percent in 2003 from 2000 levels. This decline was engendered by California’s downhill economy following a high rate of growth in the late 1990s. Washington, D.C. and San Jose were the only two among the 12 that experienced growth in biotech VC for the period. Two other metros leading San Diego are Los Angeles-Long Beach and Boston, both of which recorded 7.6 percent decline in biotech VC between 2000 and 2003.

In San Diego, about 75 out of 1,000 biotech firms received venture capital investment annually for the 2000–2003 period. The figure ranked San Diego 3rd among the 12 metros, after San Jose (136 firms) and Raleigh-Durham-Chapel Hill (97 firms). San Diego’s strong ranking in this component is a clear illustration of how high-risk biotech finance is assisting regional biotech entrepreneurship. Boston and San Francisco ranked 4th and 5th, respectively, following San Diego.

As seen with biotech VC investment component, there was a 13 percent decrease in the number of companies receiving biotech VC investment over 2000–2003. In terms of ranking, San Diego is positioned 7th among the 12 selected metros. Even though San Diego’s descending momentum in biotech VC activities can be partly attributed to depressed VC market conditions in California, other California metros show far better accomplishments among these components. Los Angeles-Long Beach ranked 1st with a 38 percent increase, followed by Orange County with 27 percent growth in the number of companies receiving biotech VC investment, although expanding from an appreciably lower base than San Diego.

With $55 biotech VC investment per $100,000 GMP, San Diego ranked 2nd among the 12 selected metros. That amount is more than nine times larger than the average for the U.S., the world’s biotech leader. San Diego is home to many venture-capital nurtured biotech companies that were


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significantly aided in their initial growth phase. Venture capital investment is one of the major tasks of BIOCOM, according to its president, Joe Panetta. San Jose ranked 1st in this measure with $58 per $100,000 GMP.

Several major players in the San Diego biotech cluster pointed out that while venture capital is available, much of it comes from the East Coast and the San Francisco Bay Area. In other words, there is a limited supply of local, indigenous-based venture capital in the San Diego community. As Henry Nordhoff of Gen-Probe noted in our interview when asked to clarify what he would like to see improve, “There would be more money, more capital available locally with people in San Diego controlling it with informal relationships, knowing others. I’d call up somebody, say, ‘Joe I’ve got this wonderful product, come on over.’” Haile elaborated on this point, “On the weaknesses, I think we still need to see more venture capital coming into San Diego. We’ve got probably about one-quarter of the number of VCs that the Bay Area has and that hurts us.”

San Diego placed 4th on the component measuring the number of biotech patents issued per 100,000 people; a good, but not remarkable sign of regional biotech creativeness. Approximately 24 biotech patents per 100,000 people were issued in San Diego from 1996–1999. The top three metros in this category were San Francisco (38 patents), San Jose (34 patents), and Raleigh-Durham-Chapel Hill (25 patents). Averaged out per 1,000 biotech workers, San Diego’s biotech patents slipped down to 7th. This does not mean that San Diego’s biotech workers are less inventive, but that San Diego has a relatively larger number of biotech workers than other metros.

With 122 biotech patent citations per 1,000,000 people, San Diego ranked 4th among the 12 selected metros. San Francisco had 210 biotech patent citations per 1,000,000 people, which positioned it 1st, followed by Raleigh-Durham-Chapel Hill (138 biotech patents) and Oakland (122 biotech patents). Averaged out per 1,000 biotech employees, San Diego ranked 5th.

In terms of business starts per 1,000 businesses, the San Diego metro ranked 5th out of the 12 selected metros. San Diego’s mediocre rank on this component is attributed to a drop in venture capital funding in the biotech field, the downturn in the business cycle for the California economy as well as rising business costs. The Austin-San Marcos metro took the top position with 57 business starts averaged out per 1,000 businesses.

Eleven percent, or nine of 84 Technology Fast 500 companies in life sciences for 2003 are located in San Diego. Averaged out per 1,000,000 business establishments, the metro placed 1st among the selected 12. Among these, seven firms are in the biotech field, one in pharmaceuticals and the other in medical devices. Technology Fast 500 companies in biotech based in the San Diego metro include firms such as Prometheus Laboratories Inc., Protein Polymer Technologies, Inc., Diversa Corporation, Digirad Corporation, and Carlsbad-located Invitrogen Corporation.


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San Diego’s biotech risk capital and entrepreneurial infrastructure score is 88.6 (out of a perfect score of 100) before rebasing the top score to 100 for comparison purposes, which placed it 3rd among the selected 12 metros. Northern California metros San Jose and San Francisco ranked 1st and 2nd, respectively. San Diego’s strongest achievements among the indicators for Biotech Risk Capital and Entrepreneurial Infrastructure were biotech venture capital dollar per $100,000 of GMP, biotech patents per population, biotech patent citations per population and Technology Fast 500 companies in life sciences.

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Series1 88.6 92.6 88 88.2 98.6 87.7 84.4 89.7 79.6 77.1 100

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Biotech Risk Capital & Entrepreneurial Infrastructure Component

Total Biotech Venture Capital Investment Growth Average (2000 - 2003)

Companies Receiving Biotech VC Investment (Per 1,000 Biotech Firms)

Biotech Patents Issued (Per 100,000 Pop.)

Tech Fast 500 Companies in Life Science (Per Million Businesses)

Number of Business Starts (Per 1,000 Businesses)

Biotech Patent Citations (Per 1,000 Biotech Employees)

Biotech Patent Citations (Per Million Pop.)

Biotech Patents Issued (Per 1,000 Biotech Employees)

Companies Receiving Bioech VC Investment Growth Average (2000-2003)

U.S. Avg.

San Diego 88.6 -10.0% 75.2 -13.3% 55.0 24.1 46.1 23.3 22.6 113.3

1 2 3 4 5 6 7 8 9 10

67.2 -14.0% 27.3 -2.2% 6.0 5.0 49.4 18.0 20.6 10.4

Biotech VC Investment (Per $100,000 GMP)

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121.5

18.3


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MethodologyAs in the previous section, data analysis of this section was carried out with 12 metropolitan areas that show the strongest concentration of biotech in the U.S. In the comparison of the relative strengths of each metro’s biotech entrepreneurial settings, we scaled out each component by population, biotech worker or biotech business, such as the San Diego metro’s biotech patents issued per 1,000 biotech workers. After these adjustments, we compared the relative values using our score and rank systems.

Data used and compiled in this section came from four major sources: PriceWaterhouseCoopers/Venture economics, United States Patent and Trademark Office (USPTO), Dunn & Bradstreet, and Deloitte. Four biotech venture capital-related components came from PriceWaterhouseCoopers/Venture economics, a division of Thompson Financial. USPTO-released statistics were compiled to capture patent-related components. Dunn & Bradstreet provided business starts statistics and Tech Fast 500 companies in life science field originated from “2003 Deloitte Technology Fast 500 list” (http://www.public.deloitte.com/fast500).


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Human Capital Capacity

Background and RelevanceA region’s assets—physical endowments such as a suitable climate, congregation of large populations, geographical advantages such as the proximity to ports and availability of raw materials—have long been recognized as the key determinants to regional economic, industry and commerce development. Although materials and geographical advantages are still considered as key location choice factors, they are less relevant in today’s high-tech economy than decades ago. Modern transportation, communication and production efficiency have minimized costs related to labor and movement of goods.24 Rather, the current emphasis on innovation and creativity to capture the highest value creation throughout the design and production process is recognized as the key for an industry and region to dominate in the global economy.

In today’s highly mobile, increasingly democratized global economy, talented people, particularly those who posses the ability and capacity for scientific and technological innovation and the management of such creative activities, are more in demand than ever before. They are the builders of the economic locomotive that propel a region’s economic growth. The location pattern of economic activities, where material goods, innovation and the management of enterprises mix, often demonstrates a complex interdependence among firms and industries.25 In an industrialized economy, these complex inter-connected production/service relationships were more a function of passing semi-finished products and sharing raw material. In a knowledge and intangible-based economy, the linkages among firms are often talent, human capital, and ideas and innovation.

In the past, such complex relationships among firms were shaped by a single cluster of industries, such as in Detroit for the auto industry and New York City for the finance and equity markets. Today, the spatial distributions among industries and economic activities are no long confined by transportation distance and hence labor pool availability within a singular space. In fact, the evolution of the IT industry in Silicon Valley or the Boston Route 128 perfectly illustrates the dispersion and spin-off of industry sub-sectors that gave birth to many IT mini-clusters around the world.26 The supply chain of making a PC or many electronic products joined various clusters stringing from the Northern California Bay Area to Singapore, Taiwan, Korea, Japan, India and China. Each cluster uniquely and neatly produces and assembles the components that are necessary to the assembly of the final products.

24 DeVol, R., et al. 1999. America’s High-Tech Economy, Santa Monica: Milken Institute.25 James Heilbrun. 1980. Urban Economics and Public Policy.26 Borrus, Michael, Dieter Ernst and Stephan Haggard. 2001. “International Production Network in Asia: Rivalry or Riches?” Routledge.


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Though there are many prevailing economic factors expediting the formation of these clusters, the underlying fundamental that enables these long-chains of clusters to form across multiple regions and countries are pools of talent; human capital—a pool of talented professionals capable of innovation, creation, and capturing the institutional knowledge—and its respective capacity to fulfill the technical and operational requirements. Location still matters only if the region or the location has the capacity to attract talent that yields tremendous amounts of intellectual capital.27

The importance of having highly qualified talent pools as a reservoir of human capital in a region cannot be underestimated. Economic development history and the rise in resource-poor regions in the last quarter century have convincingly proved the importance of human capital to a region’s economic lifeline. Three of the four Asian Tigers—Korea, Singapore and Taiwan—have progressed technologically and are more advanced than their resource-rich neighbors, Thailand, China, Malaysia and Indonesia.

These regions, Korea, Singapore and Taiwan, have one commonality among them in the quest for building regional industries and developing their high-tech economies—they focus on educating, nurturing and actively recruiting talent to build up human capital. It is not a surprise that Korea’s technological advancement outperforms its competitors such as Taiwan and Singapore, if one measures per capita PhDs in science and technology in Korea. The success stories of these countries can almost certainly traced back to their earlier stage economic policy aimed to establishing science and industrial parks that provided suitable research and development space for seasoned scientists and science-entrepreneurs alike.28 Similarly, many credit the success of India’s software industry to the India Institute of Technology which has been and will continue to turn out highly educated and trained software engineers and entrepreneurs each year. These practices and policies all foster and promote talent, enlarge the human capital pool, and finally contribute to the buildup and the enrichment of local and regional intellectual property, which in turn provides a region with a superior competitive edge over other regions.

Though many have tried both from an economics and management point of view to define the relationships between talent, human capital and intellectual capital, they have not captured the essence of the inner working relationship in quantitative fashion. It is even more challenging to define such relationships and why it matters in a singular economic spatial dimension. A better and more definitive description of talent, human capital and intellectual capital in the context of a single spatial economy is perhaps the concept of economies of agglomeration.

Perhaps it is more fruitful and intuitive to start out the description of such complex interlocking relationships in a theoretical framework of external economies of scale. The concentration of industry in a geographical location can be better understood not through the linkages of activities of

27 DeVol, R., Rob Koepp, John Ki, Frank Fogelbach. 2004. California’s Position in Technology and Science. Santa Monica: Milken Institute.28 Saxenian, A. 1999. Reversed Brain Drain.


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firms in a single economic space, but rather by the external economies of scale. When firms—groups of highly talented people—operate on the input side, such economies have generally been known as “external economies of scale” where external refers to the firm. These firms are economies that depend not on the size of the firm, but upon the size of the industry.

As George Stigler explains more clearly, “When one component is made on a small scale it may be unprofitable to employ specialized machines and labor; when the industry grows, the individual firm will cease making this component on a small scale and a new firm will specialize in its production on a large scale. …The progressive specialism of firms is the major source of external economies.29” Clearly, Stigler’s assessment can be applied to the context of research and development in life science or biotechnology production, not only on the firm level, but to the congregation of talent, forming regional human capital or talent pools. Because such an external scale exists, it paves the way for the development of specialization through seemingly random derivatives of a single unit of “talent.” Delegation of various technical, management, and financing aspects of producing goods, or delivery of research and development of new ideas, then become critical for a firm or a group of highly specialized talent. Again, the external economies of agglomeration, i.e., groups of talent or human capital, are the critical building blocks in the formation of regional competitiveness. Individual firms or talent will then share the burden of cost as well as the production efficiency at lower costs across the entire industry, benefiting the entire region. In the world of biotech and other life science research and development, the concept of external economies of scale can be equally applied. Unlike IT product developments which inherently require shorter cycles and do not go through stringent regulatory tests, biotech and other life science products have far longer research and development cycles. Consider the success story of Advance Tissue Sciences. The company was founded in 1988 specializing in tissue substitutes for burn victims. After a long, industrious 10 years, the product was first approved by the FDA in 1997.30

This long research cycle, coupled with the complexity of coordination with multiple disciplinary fields throughout the process of developing artificial tissue, can be a substantial burden to a small startup. A regional science center, backed by resident research-oriented institutions such as the University of California, San Diego and other bio-science and molecular research centers, can extend the benefit of external economies of scale. Then it is not surprising to see that the number of biotech start-ups affiliated with UCSD and the many PhDs who have joined local companies. Some have estimated that 95 percent of PhD-holders from UCSD and San Diego State University went into private industry, whereas, about 85 percent of PhDs nationwide enter academia.31 It is clear that the region, both in industry and academic institutions, has formed a new culture, placing a high value on human capital at work combined with entrepreneurial spirit.

29 George Stigler. 1952. The Theory of Price. Macmillan30 Gail Naughton, Dean, College of Business Administration, San Diego State University.31 Ibid.


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When this agglomeration is possible, individual firms and talent share lower costs than if they were geographically disperse. Hence, chemists, physicists, microbiologists, physicians, computer scientists, and bio-statisticians all cross-pollinate, compete and supplement one another’s research agenda, despite limitations on the scale of operation and budget. In other words, external economies of scale define how firms behave in spatial economies and explain the importance of clustering and agglomeration. Talent, human capital and finally the reservoir of knowledge of a region and how the elements interact can be explained by the importance and organization of human capital and regional intellectual capital. Human and intellectual capital are the DNA of a knowledge-based industry and regional economy. Talent might be a point of origin in a creative process, but the expansion, growth and eventually the domination of an industry and region, rely on the realization and building of the external economies of scale, where knowledge, intellectual capital and assets can be stored and expanded upon through accumulation and regeneration.

Metro FindingsOver the past quarter century, San Diego has become the focus of bioscience and biotechnology development in the world. It is a region, in the words of Gail Naughton, a former biotech executive and dean of San Diego State University’s Business School, that grew from a “lazy government contract town” to becoming “the leaders in biotech, software and telecom...”32 In particular, San Diego’s reputation in growing biotech start-ups has surpassed other leading biotech and bioscience regions along the Northeast pharmaceutical and life science corridor.

The rise of San Diego’s biotech cluster is a new chapter in the region’s history and a testament to the region’s capacity as a strong knowledge-based economy. Certainly, the region’s advancement in and ability to compete head-to-head with other science and technology dominating regions such

OrangeSan Francis.

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PhiladelphiaSan Jose

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Biotech Human Capital CapacityTwelve Selected Metropolitan Areas, 2004

32 Ibid.


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as Boston, Philadelphia, Washington, D.C, Seattle-Bellevue-Everett, and San Jose and Oakland, validates its depth of human capital, technical know-how and entrepreneurial capability.

San Diego ranked 4th among the 12 top biotech metropolitan areas examined in this study with a composite score of 74.7 for biotech human capital capacity. The composite score is a weighted aggregate of twelve components. The metro lags top-ranked Raleigh-Durham-Chapel Hill (93.7) and Boston (84.5), and essentially tied Oakland (74.9), but outranked life science heavyweights such as Philadelphia (69.6) and Washington, D.C (69.3). Whereas regional scores are benchmarked to the highest score (Raleigh-Durham-Chapel Hill, NC, 100), the normalized composite score at 79.1 reveals similar information. What is worth noting in this chart, however, are the small numeric differences among the three California technology concentrated regions: Oakland, San Diego, and San Jose. San Diego has a minor advantage over its sister regions up north.

Boston and Philadelphia, the two combined leading life science clusters in the country and the world, have almost two centuries of tradition and expertise in medical science, pharmaceuticals, medical devices, chemical, biochemical material research and production. The depth of these regions’ human and intellectual capital, and their capacity to generate and attract financial capital, are far superior to either San Diego or Raleigh-Durham-Chapel Hill. Worth mentioning, however, is the fact that San Diego and Raleigh-Durham-Chapel Hill, a pair of “young talents,” took less than one-quarter century to be comparable to and competitive with these life science giants in the one of most regulated, complex and multi-disciplinary fields of science and technology research and production.

A more detailed look at the breakdown of the composite index will further our analysis of how and why San Diego became competitive with Boston, surpassing Philadelphia and Washington, D.C, yet losing to Raleigh-Durham-Chapel Hill—a mirror image of San Diego in its quest for technology and science advancement, especially in biotech and life science. We compiled data for 12 components that identify the dimensions of human capital for each of the 12 regions measured and compared.

The 12 components measuring biotech human capital capacity describe and measure four key competences with regard to the human capital of a region engaged in the biotech industry. These components calculate and benchmark the human capital stock, flow of specialists, and finally general pools of noncore human capital that support the core scientific and development activities.

San Diego’s biotech industry ranks favorably against the other 11 regions selected for comparison in the study. The accompanying table shows the relative positions of the 12 components including the composite index. Of them, San Diego has four important components that are ranked in the top three positions, up against biotech heavyweights Boston, Raleigh-Durham-Chapel Hill, Oakland and San Jose. They are per capita measurements of biotech postdoctoral fellowships awarded, biotech scientists and biotech bachelor degrees awarded, and the percent of biotech bachelor’s


46

degrees among all bachelor’s degrees granted in San Diego.

These top-ranked indicators are very telling. They not only showcase San Diego’s strength in biotech research and development, but illustrate that the region is also gaining more momentum in the development of biotech and biotech related fields.

The region’s talent pool with regards to biotech research and development is highly concentrated. Notably, two indicators stand out and very likely help elevate San Diego’s competitive advantage over many other regions incorporated in our study. In practice, these two indicators can also be used interchangeably or complementary to each other. The first one is the number of postdoctoral fellowships awarded per university, which is 677 in San Diego, ranking it 3rd. The second indicator is the number of biotech scientists per capita. At 2,240 persons, San Diego ranked 3rd (adjusted for the size of population).

Although the number of postdocs awarded trails other leading university towns such as Boston, Raleigh-Durham-Chapel Hill, Los Angeles, and Philadelphia, the concentration of talent in San Diego is far greater than in many of these regions. When the ranking of postdocs is normalized per research university, San Diego’s advantage stands out over other region such as Boston. Its position climbs close to the top. Another indicator, the number of postdocs awarded per 100,000 people in the 25-34 age cohort also confirms the region’s strong standing with its 5th-place ranking.


10 20 30 40 50 60 70 80 90 100San Diego's Statistics

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Biotech Graduate Students (Per 10,000 Pop.)

Biotech PhDs Awarded (Per 100,000 Pop.)

Biotech Postdocs Awarded (Per 100,000 Pop.)

Biotech Postdocs Awarded (Per Research University)

Bachelor's Degrees Granted in Biotech Fields (Percent of Total Bachelor's Degrees)

Number of Biotech PhD Granting Institutions (Per 10 Million Pop.)

Number of Biotech PhD Granting Institutions (Per Million College Enrollees)

Biotech Scientists (Per 100,000 Pop.)

Biotech Engineers (Per 100,000 Pop.)

Recent Master's Degrees Awarded in Biotech (Per 10,000 Civilian Workers)

Recent PhD Degrees Awarded in Biotech (Per 100,000 Civilian Workers)

Biotech Human Capital Component

San Diego

U.S. Avg.

1 2 3 4 5 6 7 8 9 10 11 12

74.7 18.9 18.3 150.7 677.0 8.1 17.2 20.7 77.1 4.8 37.1 5.6

58.6 20.7 15.9 74.0 195.2 5.3 12.1 19.9 34.9 2.5 10.5 1.7

Recent Bachelor's Degrees Awarded in Biotech (Per 10,000 Civilian Workers)

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21.6

9.3

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Perhaps this advantage is best understood in light of the observation by Dean Naughton that, “95 percent of our graduating PhDs go straight into industry with the mindset to stay in industry. … In most universities, greater than 85 percent go straight into academia…” While San Diego does not generate larger numbers of PhD degrees in biotech, ranking 9th, this limitation arises from the small number of institutions in San Diego that can actually grant such a degree. Only when one understands the geographical boundaries and size of the metropolitan area can the dominance of the region in biotech be fully appreciated.

With only five biotech PhD granting institutions, San Diego ranked 5th among the 12 metros for number of PhD granting institutions versus top-ranked Boston with 17 institutions. This limitation also impacted San Diego’s rank on recent PhDs awarded in biotech—9th among the 12 metros. This is a weaker link among key assets in human capital measures. It shows vividly against leading titans such as Boston and Raleigh-Durham-Chapel Hill where the number of PhDs awarded were 1,728 and 1,076, respectively. This weakness is further illustrated by the relatively small number of biotech graduate students per 10,000 people. San Diego ranked 9th out of the 12 metros. San Diego’s strong ranking in the postdoctoral component, yet weaker showing in the number of recent PhD degrees awarded and relatively lower score in the number of graduate students enrolled, strongly indicates that San Diego “imports” many fresh-minted PhDs from other locations. The region relies on them to build the width and depth of its biotech cluster. The high rate of young PhDs with a strong commitment to private industry is probably the most important asset the region has. While most highly trained talent focuses on and furthers theoretical building and other research, San Diego offers alternatives that enable this group of specialists to convert, and subsequently profit from turning theories and models into products.

Interestingly, the San Diego model works almost perfectly from a regional industry building and economic development perspective, attracting talent from other regions to reinforce and compensate for the shortcomings of the local infrastructure (e.g., the limited number of universities in a small geographical boundary). Through this “enrichment process,” San Diego has heightened its capacity to bring in not only the talent and a “denser” human capital pool, but along with them, millions of dollars in research funding.

This concentration of talent aided the region in attracting bioscience and biotech talent from other regions, including neighboring Los Angeles and Orange Counties. It is then not a surprise to see that the largest amount of NIH Biotech R&D funding in 2002 being awarded to a single research entity is in San Diego—The Scripps Research Institute—valued at $191 million. Other NIH funding awarded to the region also shows the depth and width of the metro’s human capital and intellectual capacity. San Diego has 26 percent of California’s research institutes, and captures 61 percent of NIH awarded projects and receives 59 percent of NIH funding.


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Weaving other social and general regional capital into the fast expanding biotech cluster is very important, despite the region’s strong standing in attracting large pools of biotech talent.

San Diego’s successful undergraduate programs comprise another of its top-ranked human capital assets. They enrich the local human capital and lower economic costs as industries build larger external economies of scale. Bachelor’s degrees are important to the region because they give an indication of both the levels of educational attainment and the type of skills that are in demand by the local or regional market. Additionally and increasingly a critical factor, enrollment in local educational institutions in biotech/bioscience is often a strong tell- tale sign of the growth momentum of a locally dominant industry. With a score of 95.4, San Diego ranked 3rd in the number of biotech bachelor’s degrees granted, very high in terms of the percentage of total bachelor’s degree granted (8.13%). Many students enroll in particular academic degree programs with the hope that they can obtain skills and a rewarding career on which they can build their livelihoods. In this regard, San Diego outperformed many other metros among the 12 metros studied. San Diego educational institutions granted 1,083 bachelor degrees, trailing only Boston (2,195), Los Angeles (1,952), and Philadelphia (1,088) where the number of universities is far greater than San Diego’s.

Deloitte’s Teresa Young believes that San Diego’s success in producing undergraduates is a reflection of the cluster’s strength in creating ample private sector opportunities for life scientists. Whereas for other regions that are populated by several universities with graduate programs in the life sciences, the more obvious route for talented undergraduates who want to pursue careers in the life sciences would be to first get a PhD to qualify themselves for progressive responsibilities in research fields. Young (herself a bachelor’s degree holder in chemistry from UCSD who eventually went on to pursue a career in the business side of the life sciences) observes: “In San Diego you have a number of individuals who, because of this whole diversity of what they can do, can just get their undergraduate degree, work in a biotech company and not have to take a PhD—unlike when I got my degree 31 years ago, there weren’t the biotechs and other opportunities outside of pure research.”33

San Diego CaliforniaPercent of

California TotalBiotech Research Institutes 12 47 26%NIH Awarded Research Projects 745 1,213 61%NIH Awarded Research Funding 316.2 ($ Mil.) 537.8 ($ Mil.) 59%Sources: National Institutes of Health (NIH), Milken Institute.

San Diego Biotech Research2003


33 Interview, May 25, 2004.

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Technology & Science Workforce

Background and RelevanceAn economy can go only so far with strong research and development capacity as its only asset. A region’s development and a growing economy also depend on the conversion of theoretical models and ideas into tangible goods and deliverable services to consumers and the marketplace. A region can only capture the full value of research and development through product manufacturing or service rendering. A region’s or firm’s strong research and development attributes do not guarantee yielding superior products and services if it lacks a qualified technology and science workforce that has suitable engineering craftsmanship, specialties in product quality control, marketing, and management skills in various functioning areas of running a business entity and production process.

As mentioned in the previous chapter, a region’s economic advantage lies in its utilization and expansion of external economies of scale. The term “specialism” refers to economic agents in a spatial economy working competitively yet collaboratively while achieving lower sharing costs across the industry as a whole, and enhancing benefits to the region in general. Hence, the most economically successful places are those with firms whose innovation processes are organized in a collaborative framework with research, development and production engaging in dynamic, interactive learning processes.34

A technology and science workforce is a necessary and a natural extension of region’s human capital and intellectual capacity. These two elements, brainpower for innovation, and the technical competence and sophistication for production, are often closely linked. The pharmaceutical industry in the Mid-Atlantic region demonstrates this closely knit relationship. More often than not, research and development centers are in a central location surrounded by multiple manufacturing plants where scientists, engineers and product production teams congregate and communicate to improve production efficiency. This intense feedback loop is common among high-technology-oriented industries.

Sustaining a high-tech cluster such as a biotech cluster needs a workforce with industry-specific skills within a location where operations take place. This pooling of a specialized technology and science workforce is critical for the industry to expand and firms to grow. Science and technology workers are the keys to the creation of economic value in the innovation, product development and mass manufacturing operational processes. These workers do not just access knowledge and apply it to firm-specific objectives, rather and more importantly, they harness new information to generate new knowledge, bringing both inductive and deductive analytical skills to complex problems, creating both new concepts and processes.35 Acquiring new knowledge, experience and

34 DeVol, R., Bedroussian, A., Koepp, R., Wong, P., “Manufacturing Matters: California Performance and Prospect,” Milken Institute, 2002


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technical know-how are often highly dependent upon the types of operation, detailed divisions of labor, extensive work experience, constant interaction with other colleagues working in the same field and the like. In general, these skill sets are heavily industry and product specific and highly regionalized as well.

The quality and availability of a science and technology workforce not only affect the overall long term performance of an industry, but can directly impact it on the firm level as well. The location choice a particular firm faces often depends upon the availability of input and the cost of obtaining such input. Other things being equal, firms move to areas with abundant supply of high-quality low-cost input, assuming the particular firm is small and the local industry structure is competitive, and its relocation would not alter the existing industry setting and structure.36 It is arguably true that the smaller the startup firm, the more critical “the abundant supply of high-quality inputs with low-cost” factor there is. San Diego’s biotech industry structure is very similar or closer to a “competitive environment” in which many small firms exist in a relatively small space. Small firms tend to have smaller operational budgets and limited ability to recruit needed qualified technical workers from long distance or retain technical staff full time. Small startups tend to contract out “noncore” technical tasks or “administrative work” to consultants who are in proximity to the firm’s operating location. A region lacking larger pools of this highly skilled, scientific and technically trained workforce and highly qualified administrative support will not be able to grow, attract and nurture young technology-based startups.

The biotech industry requirements for a science and technology workforce are even more demanding than other technology-oriented industries such as information technology. Given bioscience’s long development cycle, cross-multiple disciplinary fields, tight government regulation, and larger capital investment up front, the requirement for a suitable workforce can only be more demanding. Many have wondered why the biotech industry prospers in San Diego. A seasoned biotech entrepreneur, Howard Birndorf of Nanogen in San Diego, stated that, “The fact of the matter is that because of the intense talent pools here, you start a company and you have people that you can hire. To duplicate that is going to be hard to do for another state. That is probably one of the key ingredients.”37

Young echoed a similar sentiment in observing how her firm has had to develop various types of specialization to serve the needs of the cluster. “Life sciences is a heavily regulated industry,” she remarked. “It demands a number of individuals who have expertise in the areas of clinical trials and FDA approval so they can help companies as they work their way through the whole process of product development and make sure they’re in compliance with various regulatory requirements. We have people with such expertise in our consulting practice. For example, one of the women

35 DeVol,R., Koepp,R., Ki,J., and Fogelbach, F., California’s Position in Technology, and Science Milken Institute, March 200436 James Heilbrun.1980. Urban Economics and Public Policy.37 Howard Birndorf, Nanogen, Interview with Rob Koepp, April 16, 2004


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here has a background as both a nurse and an attorney, and one of her areas of focus is regulator, compliance.”

The answer to why biotech prospers in Sand Diego seems to be simpler than many researchers have tried to come up with, but it is definitely true. Since talent and a well-disciplined science and technology workforce are the fundamental elements in the knowledge-based economy, a region that can train, attract and retain this specialized workforce will be likely to prosper. Regions that do not are likely to experience gradual economic decline. The conversion and commercialization of local products benefits the local economy. Ideas and research yield few benefits with limited scope locally if the most of the economic value is generated elsewhere. It makes no significant difference to a firm where its product is made as long as it captures its profits, but it does make a significant difference to a region and industry as a whole. It is vital that regions keep both the highest production value and the talent that helps produce it to maintain economic vitality in a knowledge-based economy.

Metro FindingsIn the composite measurement of its scientific and technology workforce, San Diego scored relatively high, ranking 5th among the 12 metropolitan areas studied. The position is very respectable, but nonetheless, the rank exposes the weaker side of the region’s biotech cluster in specific workforce categories and life science in general. In the measurement of workforce, San Diego falls behind Raleigh-Durham-Chapel Hill (1st), Boston (2nd), San Jose (3rd) and Oakland (4th). Quantitatively, the statistical differences among the 3rd, 4th and San Diego at 5th place are marginal at best, separated at most by four. On the other hand, the metro ranked favorably against Washington, D.C. (6th), Seattle-Bellevue-Everett (7th) and Philadelphia (8th). However, if we look at this ranking with respect to the human capital capacity composite measurement on which San Diego ranked 4th, we see that San Diego has some catching up to do albeit the gap is not wide.

The discrepancy in ranking between human capital capacity (4th) and workforce (5th) is a function of the smaller scope (not size) of life science in San Diego compared to other top ranked regions. Scope refers to the number of teaching hospitals, the presence of larger pharmaceutical firms and manufacturing of medical devices. Secondly, the region’s relatively weaker manufacturing base, compared to San Jose, Philadelphia and Raleigh-Durham-Chapel Hill contributes to this limitation.

AustinOrange

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BostonRaleigh

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50

40

30

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Biotech WorkforceTwelve Selected Metropolitan Areas, 2004


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San Diego’s limited scope in life science may have a lot to do with the limitation of the industry traditionally in San Diego, lacking a sufficient number of occupational categories such as microbiologists and a wider array of medical scientists. The metro’s limited capability in manufacturing could be influenced by the fact that the biotech industry as a “stand-alone field” is very new and the optimal mix and level of technology and science workforce will develop over time to accommodate further industry expansion in the future. However, a weaker intensity in technology and science workforce could also be due to the business environment by which the metropolitan area is regulated, i.e., government regulations.

San Diego’s score and ranking in each of the six workforce categories appears in the accompanying chart. The science and technology workforce composite index captures measurement of the key components supporting the biotech industry and life science in general.

Similar to the human capital capacity measurement, San Diego’s rankings across all seven categories (including the overall composite measurement) are strong overall, but there are weaknesses in two categories. The intensity of microbiologists and biomedical engineers falls slightly behind as compared to other biotech metros. “Raw” statistics tend to bias towards regions that are centered geographically and academically such as Boston, Philadelphia, Washington, D.C. and Raleigh-Durham-Chapel Hill, unlike San Diego’s with its limited geographical space and boundaries. Additionally, these two indicators (intensity of microbiologists and biomedical engineers) are more traditionally affiliated with basic research institutions such as universities rather than


50 60 70 80 90 100San Diego's Statistics

1

2

3

4

5

6

7

Biotech WorkforceSan Diego's Score

Series1 85.3 90.9 98.8 62.2 93.5 84.1 66.7

1 2 3 4 5 6 7San Diego

U.S. Avg.

1 2 3 4

85.3

68.8

5 6 7

Biotech Workforce Component

Intensity of Life Scientists

Intensity of Biochemists & Biophysicists

Intensity of Microbiologists

Intensity of Biological Scientists

Intensity of Medical Scientists

Intensity of Biomedical Engineers

84.4 11.9 11.6 33.6 45.2 5.6

192.5 77.6 10.5 90.6 90.6 11.3

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applied research centers and biotech start-ups. Hence, this shortcoming, rather than being tied to the deficiency of the biotech cluster in San Diego is indicative and illustrative of the orientation of the biotech industry in there, that is, an economic space specializing in applied research and commercialization of advanced biotechnology products and services.

Despite being one of the two younger biotech/life science clusters in the country (the other being Raleigh-Durham-Chapel Hill), San Diego’s intensity in the four other biotech workforce statistics overcomes the limitations of having a short history in bioscience and biotechnology and very few universities (there is only one medical teaching hospital and only three PhD-granting institutions in San Diego). Against all these odds, the metro’s rapid development over the past decade has attracted both funding and talent from all over the country. As a result, the number of life scientists in San Diego stacks up strongly against Oakland, San Jose, Philadelphia, and Washington, D.C. This is probably one of the lesser known achievements about San Diego.

This heavy recruitment from outside the region has yielded significant economic benefit. The immediate economic return of this practice is a buildup of biotech specific occupations such as biochemists and biophysicists. San Diego shows overwhelming dominance over 11 of the 12 regions slated in the study, only losing to pharmaceutical giant Philadelphia in the nation. The region hosts 960 biochemists and biophysicists as compared to Philadelphia with 1,080 such specialists, surpassing Oakland (820), Raleigh-Durham-Chapel Hill (520) and Boston (520). Given the short time in which it accumulated so many specialists, one would wonder if San Diego might surpass Philadelphia in terms of the number of highly specialized workers/scientists with the metro’s biotech cluster continuing to expand at the current rate.

Since these statistics are not weighted, the biotech-specific workforce is tilted toward those metros with a greater number of research universities and more mature life science, pharmaceutical and biotech clusters such as Boston, San Jose, Oakland, Philadelphia and Washington, D.C. Other categories in which San Diego stands out include the intensity of biological scientists, biomedical engineers and medical scientists, once the statistics are normalized to the scale of the regional workforce. San Diego’s biotechnology research and development intensity exceeds other regions. Other employment categories and business infrastructures are part of the regional workforce capability as well. So far we have focused almost exclusively on the high-end, highly specialized research development categories. The fact is, the region’s biotech firms and research institutions, particularly those that expand over time, need professional staff other than scientists to mind the business and manage daily administrative functions. As part of our study, Institute researchers conducted interviews with educators, venture capitalists, scientists and business leaders from nonprofit trade groups to ascertain their input, opinions and assessment, and suggestions with regard to the local industry and its prospects in the future.


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Thus far, statistics have been very indicative of San Diego’s leading position in incorporating a high-end workforce into the regional biotech industry. Other occupational and employment statistics with regard to professional managers with expertise in biotech product marketing and planning, business development, and various corporate functions for the biotech industry are difficult to define. From some of the interviews, however, we did gain some insight on the issues of cross-functional support within biotech firms, and other corporate and regional biotech industry needs.

The success of San Diego’s technology advancement has always been associated with strong leadership in the region’s educational institutions. This tradition has played a critical role in shaping the expansion and growth of local technology industries. This kinship between the industries and educational institutions is probably the most important intellectual capital as well as workforce capacity in San Diego. Early in the development of the biotech industry when the technology base was weak, educational institutions led the way, but now, as biotech has taken root in the region, these institutions often respond to the industry’s needs.

Universities’ participation can be valuable in building a workforce that caters to industry’s needs, in this case the biotech industry. New programs such as joint PhD-MBA degrees and MS degrees in quality control (QC) cater almost exclusively to the biotech/bioscience field with strong leanings toward the biotech firms in San Diego. More importantly, this PhD-MBA program is not a construction of an academic mission. Rather, it is supported and the curriculum is partially designed by executives from local pharmaceutical and biotech companies, in anticipation of increasing needs or a shortage of competent science/technical business managers in San Diego.38 During the interviews with local business leaders, some thought that the region was weak in supplying specialists in manufacturing. Implicitly, these interviewees drew comparisons between San Diego and the Northeast Pharmaceutical Corridor.

San Diego’s overall ranking among the 11 other biotech leading centers in the country is strong. The metro’s rise in technology dominance is almost an overnight success compared to the development histories of Boston, Philadelphia and Washington, D.C. While there are many achievements worth celebrating, weaknesses remain. The small community—many have lauded its closeness among competitors and collaborators alike—may prove to be a limitation to the region’s future growth. The issue will become more obvious, when San Diego is measured against Raleigh-Durham-Chapel Hill.

Space can be critical to industry development. San Diego’s geographic limitations reduce the probability of building another teaching hospital or large-scale pharmaceutical manufacturing plants, for example. These large institutions, if constructed, would boost the training, experience,

38 Gail Naughton, Interview with Rob Koepp, May 2004.


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scope and sophistication of the metro’s biotech and life science workforce. Raleigh-Durham-Chapel Hill has very few limitations in this regard.

While San Diego enjoys a high ranking among our six key indicators, Raleigh-Durham-Chapel Hill actually surpasses San Diego with more top-ranked positions. Raleigh-Durham-Chapel Hill outranks San Diego in five categories. In many ways, the two metros are similar; both grew out of “boredom” towns and anchored their economic development strategies in high-technology. Both fully utilized state universities and the advantage of having regional super-computing sites at their disposal to leverage industry development. To gain an advantage over the other, both regions must seek policies and strategies to expand and upgrade their scale of life science and biotech operations. From an industry development viewpoint, the metro that can further its external economies of scale will gain the upper hand.

Methodology For the purposes of this analysis, the biotech human capital capacity and workforce components focus on the core assets—bioengineers, biophysicists and the like—and do not include members of supporting industries and occupations or ancillary services. Although this section specified the organizational relationships between “core” biotech assets and supporting industries and occupations, a more detailed description is presented in the current impact section.

Statistics and information that are utilized in the analysis came mainly from public sources. Statistics on degree-granting institutions, and number and types of degrees awarded came from the National Science Foundation (NSF). Occupational and employment data such as number of bioengineers, biochemists or microbiologists came from the Bureau of Labor Statistics (BLS), Department of Commerce. We also utilized information derived from interviews conducted by the Milken Institute.

We present our analytical findings in both level measurements, and adjusted by the size of the regional economy and population base in order to obtain unbiased comparisons. The analysis also focuses on the concentration, density and relative strengths or weaknesses of the 12 metros. The scoring system applied in these two sections is the same as those that are used in other sections of this study. It illustrates relative values among different indices and indicators.


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Current Impact Assessment

Background and RelevanceNow that we have identified and discussed the key components of San Diego’s biotech innovation pipeline, we can assess its relative economic performance to other major biotech centers. While that section addressed the San Diego’s available resources in terms of research and development, venture capital investment, labor force quality and so on, the current impact measures focus on the relative economic outcome within the life science industry. The current impact can be thought of as a cause- and-effect relationship; if a metro is surrounded by research-oriented centers/universities endowed with significant R&D funding and/or VC investment, has a vibrant entrepreneurial orientation, and is able to attract a sophisticated labor pool, then that metro is in a better position to capitalize on its regional assets. This environment would not only generate a larger, more concentrated employment base and higher growth potential within the industry, but it would also stimulate an increase in economic activity within the region. Given the value-added benefits that the biotech industry has to offer, one would expect its economic contribution to be of greater significance than your average industry, both locally and outside the region.

The current impact assessment measures the absolute and relative importance of employment size and growth, as well as diversity within the life science industries. Specifically, the current impact index is comprised of seven unique components. The first four components address the issues of size and performance, while the latter three measure diversity. • Employment Level in 2002, • Location Quotient39 (LQ) in terms of employment in 2002, • Relative Employment Growth from 1997-2002, • Number of Establishments in 2001, • Number of Location Quotients Greater than 2.0, • Number of Location Quotients Less than 0.5, and finally, • Number of Life Science Industries Growing Faster than the U.S. from 1997–2002. The Current Impact Composite Index (comprised of these seven components) summarizes and creates a relative snapshot of the current economic impact or outcome.

39 The Location Quotient (LQ) equals % employment in metro divided by % employment in the U.S. If LQ>1.0, the industry is more concentrated in the metro area than in the U.S. average.


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Size and Performance Size and performance are captured by employment level, employment concentration as measured by LQ, relative employment growth indexed to the U.S., and the number of biotech/life science establishments per 10,000 establishments. The employment level is simply the employment size in a given year, in this case for 2002. The location quotient measures a particular industry’s share of employment in a given metropolitan area relative to that of the national share. Mathematically speaking, if the U.S. is equal to 1.0, and the LQ for a given metro is 2.0, then that would mean that the metro has twice the U.S. average for biotechnology. Similarly, with relative employment growth, the current level of employment in a particular industry is indexed or benchmarked to its base year (1997) within the respective metro and then taken as a proportion of the indexed growth in the U.S. If a metro’s relative indexed growth is 120, then it grew 20 percent above the national average. Conversely, if a metro’s relative indexed growth is 80, then it grew 20 percent less than the national average. Finally, establishments classified under a specific industry are measured per 10,000 total establishments. Thus, within the biotech industry, for instance, if there are 10 biotech establishments in a given metro that has a total of 100,000 establishments, then we can say that for every 10,000 establishments within the metro only one is a biotech establishment.

For the purposes of this study, 12 metropolitan areas known for their biotech presence (including San Diego) were selected for comparison. While this study addresses the biotech industry, it would be inadequate to ignore the pharmaceutical manufacturing industry, since certain components of biotech (e.g., biological processes) are utilized in the development of pharmaceuticals and vice versa. Other studies in the past have failed to make this distinction due to limitations in data availability and oftentimes combine these classifications into a higher aggregate category. To achieve the highest credible results, this study separately addresses the overall life science industry which includes the pharmaceutical and medical devices industries’, in addition to the biotech industry. Consequently, those metros that capture only a minor share of the nation’s biotech industry, yet are surrounded by pharmaceutical and/or medical devices manufacturing, may score relatively low on the biotech measures, but higher in the overall life science category. For further explanation of industry specification, please refer to the methodology section.

DiversityThe second section of the current impact assessment focuses on diversity. Three unique measures were used to determine the level of diversity within the biotech/life sciences sector or industry groupings: • The number of industries within the biotech/life sciences industry group with location

quotients (LQ’s) greater than 2.0 in terms of employment, • The number of industries within the biotech/life sciences industry group with LQ’s less

than 0.5 in terms of employment, and • The number of industries within the biotech/life sciences industry group whose

employment has grown faster than the national average.


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The purpose of the first two components used to measure diversity within the biotech/life science industry, is to credit those metropolitan areas that have at least twice the concentration of the national average, and penalize those that are at most 50 percent or less, below the national average. This methodology allowed us to rule out extremities. For example, a metro with a very high location quotient due to a low overall employment base, could lead to skewed results. The diversity measurements correct for this, so that the metro is attributed the same amount of significance whether it has an LQ of 2.5 or 15, at least within the diversity portion of the overall index.

To further illustrate the purpose of these measurements, let’s take the following example using the biotech industry. Four industries comprise the overall biotech sector: Medicinal and Botanical Manufacturing, In-Vitro Diagnostic Substance Manufacturing, Other Biological Manufacturing, and Biological Research and Development (see Methodology). While a metro may have an extremely high concentration of Biological Research and Development, its employment presence among the manufacturing components of biotech may not be as high. Thus, it may not be fair to say that the metro is a top biotech center in the nation without considering all of the sub-industries that are comprised of biotech. A metro that has a well-balanced mix of biotech manufacturing industries and, in addition, has the research criteria to go along, is more likely to score higher on the diversity scale.

The third and final component used to measure diversity is the number of biotech/life sciences industries whose employment has been growing relatively faster than the U.S. between 1997 and 2002. The purpose of this measure is to reward those metros that have exhibited strong relative growth in recent years versus those that have not. For example, a metro could have a high biotech employment base, and a high biotech employment location quotient, but may not be growing relative to other parts of the nation for one reason or another.

A metro may rank high in terms of employment level and concentration within a particular industry, yet display moderate or little growth relative to other parts of the nation, often leading to several implications. This may suggest that the metro is losing some of its employment to other parts of the county, and/or not effectively capitalizing on its resources or inputs.

Composite IndexThe current impact composite index ties together the seven components used in determining the current impact measures. In arriving at the index, several steps were conducted. First, within each component, each metro was benchmarked to the top metro in that category, creating a normalized scoring system that could be consistently compared across each measure. It also generates a relative sense of dispersion across each metro and eliminates any extreme bias. Second, unique weights are attached to each component when arriving at the composite score. As one would expect, the weights are indicative of each measure’s relative importance and contribution to its overall performance. Since size and performance comprise a primary indicator when measuring economic outcome,


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they deserve greater weight. Finally, if a metro ranked 1st in every category, it would receive a score of 100 and rank 1st in the overall composite.

Metro FindingsWithin the biotech industry, San Diego ranks 2nd in terms of absolute employment size among the metros examined, with 14,500 biotech workers. Only Boston had a higher employment size, with 18,700 workers within the biotech industry. In relative terms, however, San Diego had the highest location quotient. Its concentration of biotech employment is about 5 1/2 times greater than the national average. In other words, given San Diego’s overall employment base, a relatively higher proportion is comprised of biotech and related R&D. Much of this can be attributed to the presence of U.C. San Diego, the Salk Institute, and the Scripps Research Institute, which have generated 112 biomedical companies combined, founded through their faculty and alumni.40 “UCSD has pioneered the Connect Program trying to put potential inventors with entrepreneurs,” explained Henry Nordhoff of Gen-Probe.

San Diego’s research establishments and universities have provided a foundation for giving birth to many commercial biotech companies and attracting others into the region. Haile noted that the combination of lifestyle along with the high quality and number of research institutes, such as the Salk Institute, Burnham Institute and Scripps, attracts top researchers.

Growth in venture capital investment coupled with federally funded R&D has led to the training of highly skilled individuals and development of biotech start-ups, which growth is reflected in gains in employment. In terms of relative employment growth within the biotech industry, San Diego grew 10 percent faster than the nation between 1997 and 2002 and ranked 4th overall in growth. Finally, for every 10,000 establishments in San Diego, 75 are biotech establishments, ranking it 2nd only to San Jose in this category.

40 California Healthcare Institute, 2002 Report on Southern California’s Biomedical R&D Industry.


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The three-dimensional bubble chart below provides a good way to illustrate size and performance.

The vertical y-axis positioning of each bubble corresponds to the concentration, or location quotient, of the biotech industry in each state. Ideally a state’s bubble should be centered above the horizontal line at 1.0, which indicates the U.S. national average concentration (equivalent to a location quotient of 1). The horizontal x-axis positioning of each bubble corresponds to the relative growth of the biotech industry in each state from 1997 to 2002. High-growth states are represented by bubbles positioned to the right of the vertical line at 100 (the average growth in the U.S. for biotech sectors). Finally, the size of the bubble indicates employment size within the metro. If a metro has an LQ above 1.0 and an index growth greater than 100 (e.g., San Diego) then its 2002 concentration of employment is not only higher than the U.S., but its employment has also grown relatively faster than the nation between 1997 and 2002.

Multiple analyses were performed using four different industry classifications: biotech, medical devices, bio-medical (sum of biotech and medical devices), and life science (sum of bio-medical and pharmaceuticals). See the Appendix for detailed tables regarding each component.

Of the 12 metros examined for the biotech industry, only six place above the horizontal line at 1.0 and to the right of the vertical line at 100, suggesting that these metros are most proficient in their regional inputs. Of those six metros, San Diego is the biggest in terms of both absolute and relative size in biotech. When looking at the life science industry as a whole (next page), San Diego still maintains its vibrant position.

Biotech IndustryEmployment - Concentration, Growth, and Size

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Relative Growth 1997-2002 (Index U.S. = 100)

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verage

=1.0)

Philadelphia

Wash.,D.C.

Raleigh-Durham

Austin

San Jose

San Francisco

Boston Seattle

San Diego

Los AngelesOrange Co.

Oakland


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The addition of medical devices and pharmaceuticals to biotech (i.e.,life sciences) improves the relative position of those metros with particular strengths in those industries, while conversely, weakening those that lack those industries. With that said, only four metros remain within the upper right area of the bubble chart (above the horizontal line at 1.0 and to the right of the vertical line), along with some relative shifting among the other metros.

Unlike San Diego, whose position remains strong when looking at biotech alone and life sciences as a whole, some metros do not fare as well when incorporating medical devices and pharmaceuticals into the picture.

Looking first at the metros no longer within that spectrum, Washington, D.C. and San Jose, we see that Washington, D.C has a higher concentration of biological R&D than manufacturing of pharmaceuticals and biological-related products, thus its relative position in life sciences as a whole is not as great as in biotech alone. The same holds true for San Jose. One might think that San Jose’s high-tech manufacturing of medical devices would strengthen its relative position, but because of its lack of manufacturing activity in the pharmaceutical industry, that region does not fare as well in the life science category. That region is also still rebounding from losses it endured during the dot-com bust. Orange County, on the other hand, improves its relative position in the life science bubble chart due the high concentration of medical devices industries there.

BIOCOM, an association of biotech and medical devices companies in the San Diego area, has

Life Science Industry AggregateEmployment - Concentration, Growth, and Size

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verage

=1.0)

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San FranciscoBoston

Seattle

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450 industry members.41 Its purposes include fostering the growth of biomedical innovation by providing its member companies with up-to-date information, advocating relevant public policy issues, and promoting the continuous development of a highly skilled life sciences workforce. BIOCOM has taken the role of advocate for its members, and serves as one of the driving forces responsible for the San Diego region’s remarkable growth and success in the life sciences industry. As Panetta put its, “BIOCOM focuses on bringing new investment to San Diego, venture capital investment, pharmaceutical companies, partnerships, and investment banking, and we focus on creating the opportunities for future jobs by working with the universities and the colleges to ensure that the curriculum and training programs, and the degree programs are being created to ensure that we have the biotech workforce in the future.” The association has grown 500 percent since it was established in 1995.

In San Diego, all four industries that comprise biotech have LQs greater than 2.0, ranking that metro first in that category. Conversely, no biotech industries in San Diego have an LQ of less than 0.5. Thus, the results of the diversity analysis show San Diego’s biotech industry to be the most diverse in the nation. According to Mackey, “One of the great things about San Diego is its size. It’s large enough to be very stimulating in that you’re always making new connections and meeting more people, but it’s small enough that you can maintain those connections.”

In San Diego, three out of the four industries that make up biotech have seen their employment grow faster than the nation, placing the metro 4th in the employment growth category. Oakland, San Francisco, and Washington, D.C. all tied for 1st, and have at least four biotech-related industries growing faster than the U.S.

Life science, on the other hand includes a much broader range of industries; 13 in total (12 at the

MSA Biotech Life Science Biotech Life Science Biotech Life ScienceAustin-San Marcos 1 3 2 7 1 4Boston NECMA 2 7 1 2 0 4Los Angeles-Long Beach 1 3 0 1 0 6Oakland 2 5 1 3 4 8Orange County 0 7 1 1 0 3Philadelphia 1 2 0 1 0 5Raleigh-Durham-Chapel Hill 3 3 0 4 1 5San Diego 4 6 0 1 3 8San Francisco 1 2 2 4 4 8San Jose 2 6 2 6 1 4Seattle-Bellevue-Everett 2 4 1 5 2 6Washington, D.C. 1 1 1 8 4 8

# of Industrieswith LQ >2.0

# of Industrieswith LQ <0.5

# of IndustriesGrowing Faster than US

Diversity MeasuresBy Metro, 2002

41 2002/2003 Membership Directory and Life Science Census, BIOCOM.


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5-digit NAICS level and 1 at the 6-digit NAICS level). Again, the life science category is comprised of biotech, medical devices, and pharmaceuticals. Even within this broader category, San Diego does relatively better than most metros. Metros such as Boston, Philadelphia, and Orange County exhibit more diversity due to broader mix of industries with high concentration and growth levels in employment.

In the overall composite index of the current impact measures (CIM), San Diego ranks 1st in terms of biotech and 2nd in terms of life science. Only Boston scores higher on the life science composite index, while San Jose ranks a respectable 3rd.

Within the biotech composite, San Diego scores 100 on three of the seven measures and is at 78 or better on the rest. Its strengths include not only relative employment size and growth within the overall biotech industry, but also a high concentration mix of biotech-related industries as explained by the diversity measures. While the region’s biotech activity is funneled primarily through its R&D (NAICS 5417102), capturing approximately 71 percent of total biotech employment, San Diego has portrayed significant growth in its biotech production process, thus creating a diverse set of biotech-related industries.

The scoring system creates a sense of where each metro stands relative to the other’s performance. While the characteristics are unique across each metro, the relative employment growth category portrays the least dispersion or standard deviation. Although only six of the 12 metros have been growing relatively faster than the United States, the variation in growth among metros has been incremental. The category of absolute size contains the widest amount of dispersion as one might anticipate.

The table below summarizes the current impact measures in terms of biotech and ranks the metros on a relative scoring system.

BIOTECH Current ImpactEmployment

LevelLQ

(US=1)Rel. Growth(US=100)

Establishmentsper 10,000 est.

# of Ind.LQ>2

# of Ind.LQ<0.5

# of Ind.growing>US

CompositeIndex

MSA 2002 2002 97-02 2001 2002 2002 2002 2002San Diego 78 100 89 80 100 100 80 100Boston NECMA 100 50 72 45 60 50 20 80San Jose 49 85 93 100 60 33 40 78Raleigh-Durham-Chapel Hill 35 80 75 61 80 100 40 69Seattle-Bellevue-Everett 50 59 88 32 60 50 60 68Washington, D.C. 49 28 100 64 40 50 100 65Oakland 33 50 98 47 60 50 100 64San Francisco 37 59 86 48 40 33 100 64Philadelphia 56 37 66 25 40 100 20 58Los Angeles-Long Beach 43 17 78 19 40 100 20 50Orange County 13 15 57 31 20 50 20 29Austin-San Marcos 8 18 50 34 40 33 40 28Addendum:Ventura* 31 175 167 28 60 33 80 111

DiversitySize and Performance

Current Impact Measures (CIM) - Scores for BiotechRanked by Composite Index

See footnote below regarding the Ventura MSA.42

42 Although Ventura was included as an addendum for the sake of recognizing Amgen as one the nation’s leading companies in the biotech industry, it was excluded from the rankings given its relative total employment base. Also note that this study compares MSAs, and not CMSAs, otherwise Ventura MSA would have been incorporated into the larger Los Angeles CMSA.


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In San Diego, the R&D component (driven primarily by Scripps, Salk, and U.C. San Diego) has served as the foundation for luring biotech manufacturing activity into the region and is responsible for many of the university spin-offs. Companies tend to locate in regions where talent exists. Close proximity to universities and research institutes attracts a knowledge-based labor pool and plays a strategic role in determining the locality of new firms. In short, there tends to be strong correlation between the location of R&D activity and the production process. Other instances of close proximity to a research-based university driving the emergence of biomedical firms include Stanford in San Jose, U.C. Irvine in Orange County, University of North Carolina in Raleigh-Durham, U.C. Berkeley in Oakland, and Harvard in Boston.

In terms of life sciences, however, places like Boston, Philadelphia, and Orange County score higher overall. Although perceived as major biotech centers, these metros are awarded proper recognition for specializing in nonbiotech specific industries, namely, medical devices (in the case of Boston, Philadelphia, and Orange County) and pharmaceutical manufacturing (in the case of Boston and Philadelphia). Other metros score higher or lower in the life science category depending upon their area of specialization.

The table below summarizes the current impact measures in terms of life science and ranks the metros based on their relative scores.

Although San Diego scored 100 in only two categories within the life sciences, it still managed to rank 2nd overall, with a life science composite index score of 92. Limited activity within pharmaceutical manufacturing coupled with underperformance in the medical devices’ industry relative to metros like Boston, San Jose and Orange County, is the primary reason that San Diego slipped in comparison to its biotech ranking on the current impact composite index. On the other hand, San Diego scored highest on two out of the three diversity measures, suggesting that although the region may not have the largest absolute share of national employment in life sciences, it certainly ranks among the

LIFE SCIENCE Current ImpactEmployment

LevelLQ



# of Ind.LQ>2

# of Ind.LQ<0.5

# of Ind.growing>US

CompositeIndex

MSA 2002 2002 97-02 2001 2002 2002 2002 2002Boston NECMA 100 66 72 49 100 67 56 100San Diego 49 84 83 77 88 100 100 92San Jose 43 100 72 100 88 29 56 85Philadelphia 64 56 70 35 38 100 67 79Orange County 42 62 71 48 100 100 44 74San Francisco 31 67 85 48 38 40 100 70Los Angeles-Long Beach 55 29 76 28 50 100 78 68Oakland 26 52 88 53 75 50 100 67Seattle-Bellevue-Everett 33 51 80 42 63 33 78 64Raleigh-Durham-Chapel Hill 22 66 74 57 50 40 67 62Washington, D.C. 29 21 100 55 25 22 100 57Austin-San Marcos 8 25 65 35 50 25 56 38Addendum:Ventura 16 118 53 43 63 50 56 71

Size and Performance Diversity

Current Impact Measures (CIM) - Scores for Life ScienceRanked by Composite Index


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highest when adjusting for its total employment base. This adjustment process is captured by the location quotient for each life science industry. The majority of San Diego’s life science industries are either characterized by high location quotients (also referred to as export-based industries) or industries that have an LQ of at least greater than 0.5, which count for some contribution toward local demand. Using this analysis, San Diego has one of the most diverse life science sectors in the nation. Furthermore, when the LQ of a particular industry exceeds 1.0, it suggests that the industry has more than met the needs of local demand and is exporting its benefits beyond the region.

Boston ranked 1st in the life science composite index. Remarkably, Boston’s score of 100 on the absolute employment measure gives the metro a significant edge, especially since Philadelphia, the 2nd closest to Boston in that category, scored 64. The wide spread across metros characterizes Boston’s importance in the life sciences. The fact that Boston has the highest number of industries with LQ’s greater than 2.0, suggests that the metro is not merely diverse in the life sciences, but highly diverse.

Clustering and the Spatial Dimension of San Diego

The following section provides some explanation of what constitutes a cluster and how firms and employment in biotechnology are spatially distributed in San Diego.

Clusters of existing and emerging science-based technologies are critical factors in shaping the economic winners and losers of the first half of the 21st century. Because knowledge is generated, transmitted, and shared more efficiently in close proximity, economic activity based on new knowledge has a high propensity to cluster within a geographic area.43 Biotechnology is reaching maturity phase, but because of rapid discoveries in new biological processes and related areas, and their potential for breakthrough compounds, commercialization in the industry is likely to accelerate. As economic activity is increasingly based more on intangible assets, those regions with vibrant technology and medical-related clusters will experience superior economic growth. In other words, a region with a top biotechnology cluster will have more innovations, less of which will escape to other regions, or at least, they will do so at a slower rate.

The keys to regional viability are now linked to their ability to establish local technology and medical-related clusters that are networked with the global business community. The paradox of the global-based economy is that the enduring competitive advantages lie in location-specific competencies—knowledge, workforce skills, customer and supplier relationships, entrepreneurial infrastructure, management practices, the motivations, and quality-of-place attributes that allow firms to thrive. In essence, thinking locally to succeed globally.44

43 DeVol, Ross C. 2000. Blueprint for a High Tech Cluster, The Case of the Microsystems Industry in the Southwest, Santa Monica: Milken Institute Policy Brief.44 Moss Kanter, Rosabeth. 2000. Thriving Locally in the Global Economy,” World View: Global Strategies for the New Economy, Jeffrey E. Garten, editor. Boston, MA: Harvard Business School Publishing.


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Industry clusters and their associated support infrastructure are a region’s best defense against being arbitraged in a global cost-minimization game, especially in those based upon medical-related agglomerations. Firms, and the clusters to which they belong, can mitigate input-cost disadvantages through global sourcing. Location sustainability is contingent upon making more productive use of inputs, based largely upon innovation competencies. Clusters linked to the outside world offer their regions access to the best practices and latest industry developments.45 Regions excel to the extent that the firms and talent in them can innovate successfully by being there, rather than somewhere else. This is particularly poignant for an industry such as biotechnology whose survival is based upon continuous innovation streams.

To create international comparative advantage in a knowledge-based economy, clustering innovative activity is imperative. The spatial dimensions of economic activity are becoming an interesting field of inquiry—space is central to understanding how an economy works.46 Since the late 1980s, there has been renewed interest in “economic geography” mainly because of new statistical tools. If we really lived in a world of constant returns, we would not see the high level of specialized economic activity within regions that we do. This clustering results from businesses and workers seeking geographic proximity with others engaged in related activities. Increasing returns lead to competitive advantages, as in, the more that is produced, the cheaper it is to make. Such externalities, or what an economist might call agglomeration effects, typically arise from three primary sources: labor-force pooling, supplier networks and technology spillovers.

How do we describe clusters? A common misperception of clusters is that they are based upon a single industry. One single industry might be the core of a cluster, but without its partners, it may not endure for long. Industry clusters are geographic concentrations of sometimes competing, sometimes collaborating firms, and their related supplier-network.47 They are agglomerations of interrelated industries that foster wealth creation in a region, principally through the export of goods and services beyond its borders. Clusters depict regional economic relationships—local industry drivers and regional dynamics—more richly and aptly than do standard industrial methods. An industry cluster differs from the traditional definition of an industry group. It represents an entire value chain of a broadly defined industry sector from suppliers to end products, including its related suppliers and specialized infrastructure. A cluster of interdependent linked firms and institutions represents a collaborative organization form that offers its members advantages in efficiency, effectiveness and flexibility.48

45 Coyle, Diane. 2001. Paradoxes of Prosperity: Why The New Capitalism Benefits All New York, NY: TEXERE.46 Fujita, Mashisa, Paul Krugman, and Anthony J. Venables. The Spatial Economy: Cities, Regions, and International Trade. Cambridge, MA: The MIT Press. 47 Kotkin, Joel and Ross C. DeVol. 2001. “Knowledge-Values Cities in the Digital Age,” Santa Monica: Milken Institute.48 Porter, Michael E. 2000. “Clusters and the New Economics of Competition,” World View: Global Strategies for the New Economy, Jeffrey E. Garten, editor. Boston, MA: Harvard Business School Publishing.


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Supplier networks are instrumental to the success of clusters and fostering sustained agglomeration processes. Clusters are interconnected by the flow of goods and services. This flow is stronger than the one linking them to the rest of the local economy. Cluster members usually include governmental and other nongovernmental entities such as public/private partnerships, trade associations, universities, think tanks and vocational training programs, venture capitalists, patent attorneys, and even accounting and auditing firms in the case of biotechnology. These institutions provide specialized skill training, education, research, and technical support. Cluster members include both high- and low-value activities.49

The key to regional technology sustainability is based upon the diversity of its ecosystem. Locally based innovative technology firms that evolve into dominant players are necessary, but not sufficient for sustaining the system. These newly dominant firms assist regions in developing management capabilities that can be leveraged to quicken the pace of innovation for new entrants. Newly formed entrepreneurial firms can tap into the technology management capabilities resident in the region to rapidly exploit emerging technology market opportunities. Many high-tech regions have developed capabilities for rapid design changes at dominant firms, and more importantly, integrating new regional knowledge into new firm births. The leading biotech clusters in the United States epitomize this model of innovation and sustainability.

While it is clear that discoveries in biotechnology will surely benefit the entire human race, there is a different kind of race underway: the one that will determine where the primary geographic locations of this industry will reside. The economic consequences of where these biotechnology clusters form and grow will likely be immense. San Diego is well positioned to collect the economic, job creation and social benefits of this rapidly growing industry.

In order to gain a more complete picture of the spatial dimensions of the San Diego biotechnology and life sciences cluster, it is beneficial to map its organizations and employment centers. The accompanying map shows the location of each biotechnology, medical device, pharmaceutical and related health division firm within the county of San Diego. From the map it is clear that most firms are located in La Jolla and the area east of Interstate 5 in the city of San Diego near La Jolla. There are more than 90 firms in La Jolla and adjacent it to the east in San Diego. This concentration of firms is called the Golden Triangle by cluster participants. These firms are within a five-mile radius of one another from the center. The next largest concentration of firms is in the Carlsbad/Vista area with more than 30 firms.

49 Porter, Michael E. 1998. On Competition. Boston, MA: Harvard Business Review Book Series.


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The Golden Triangle is the area bounded by Interstate 5, Highway 52 and Highway 805. The map displays how it acquired its name. As firms began spinning out of the La Jolla research institutes, the logical place to locate was to the east where land was available and relatively inexpensive when the cluster started to form. Fishburn noted that, “There were a number of unique things that I think led to the formation of the biotech cluster here. One very unique aspect was the geography of San Diego and … the fact that you can get most places within a relatively small amount of time.” Agouron Pharmaceuticals is one of the major employers in the Golden Triangle with over 1,600 on its payrolls. Other major firms include Biosite Incorporated, BD Parmingen Inc. and Ligand Pharmaceuticals Inc. The mean employment size of biotech firms in the Golden Triangle is slightly less than 200. The table below shows the location of firms by city within the county.


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The following map translates the concentration of biotechnology and other life science firms’ employment by area within the county of San Diego. One of the most striking features of this map relative to the one on firm location is that employment is more heavily based in La Jolla. The large bubble in La Jolla is caused by the high employment at the Scripps, Salk and Burnham Institutes. Coupled with Pfizer R&D activities in La Jolla (more than 2,000 employees) you have a large research employment base. The Golden Triangle represents perhaps the densest concentration of biotech research, firm and overall employment in the nation. Ivor Royston of Forward Ventures support this hypothesis, “…we have the highest concentration of biotech companies per unit mile … whatever the denominator…” [e.g., employment, per capita, population].

This translates into other social patterns within the area as Mackey noted, “One of the great things about San Diego is its size; it’s very small geographically. So we run into people all the time. Once you’re out a little, it’s a very small town in that my neighbor is the head of the Institute of Molecular Medicine at UCSD, the Vice Chancellor lives up the street; Marsha Chandler, Ed Holmes live three blocks down in La Jolla.” Royston goes on to illuminate the unique relationship further, “You go to a restaurant; you see other biotech people. It’s like the entertainment industry in Hollywood. One big family. That’s what so unique about this cluster.” It’s the informal, unplanned interactions where much productive activity takes place in supporting the outcomes of the cluster. The tighter the cluster is physically, the more opportunities for these interactions.

Rank City Number of Firms Employment1 San Diego 105 22,7402 La Jolla 11 6,7393 Vista 11 2,0734 Carlsbad 21 2,0305 Chula Vista 4 1,2906 San Marcos 6 4097 Poway 1 3498 Oceanside 4 3339 Santee 2 24010 National City 2 19011 Solana Beach 2 13012 Fallbrook 1 12513 Escondido 3 11914 Spring Valley 1 8015 El Cajon 1 6816 Del Mar 1 5017 San Ysidro 1 2418 La Mesa 1 5

Total 178 36,994Sources: Dun & Bradstreet (D&B), Milken Institute.*Note: Includes related health care division employment.

San Diego Biotech & Life Science Cluster *Biotech & Life Science Firms and Employment by City, 2003


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MethodologyThe purpose of this section is to clarify in detail the definition of biotech and life science as it pertains to this study. A brief explanation regarding the data estimation and sources used in arriving at the current impact measures is also included.

Defining the Industries

The industry data compiled and used in this study is based on the 2002 North American Classification System (NAICS) as defined by the Office of Management and Budget (OMB) of the federal government.

In measuring the current impact assessment, four similar yet unique industry groups were examined: biotech, medical devices, biomedical, and life science. Although this report primarily analyzes the biotech and life science industries, data was compiled for all four industry groups. Detailed tables and charts are provided in the appendix.

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Below is a list of NAICS-based industry classifications that were used in defining the biotech industry:

Similarly, the medical devices industry is defined using the following NAICS-based industry classifications:

The biomedical industry group is simply the aggregate of the biotech and medical devices industries. This classification provides an additional perspective of analysis and may result in a different set of metro rankings on the current impact measures.

The life science industry group is defined as the aggregate of biomedical and pharmaceutical preparation manufacturing (NAICS–325412). Next is a table that lists the 13 industries that define the life science category.

NAICS Biotech Industry325411 Medicinal and botanical manufacturing325413 In-vitro diagnostic substance manufacturing325414 Other biological product manufacturing5417102 Biological R&D

Defining the Biotech Industry

NAICS Medical Devices Industry339111 Laboratory apparatus and furniture mfg.339112 Surgical and medical instrument manufacturing339113 Surgical appliance and supplies manufacturing339114 Dental equipment and supplies manufacturing339115 Ophthalmic goods manufacturing339116 Dental laboratories334510 Electromedical apparatus manufacturing334517 Irradiation apparatus manufacturing

Defining the Medical Devices Industry


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The life science industry group provides yet another perspective in examining the current impact measures and produces a unique set of outcomes. It rewards those metros that offer more than just biotech. Places like Boston, which are known for the manufacturing of pharmaceutical products, score higher in the life science category.

Data Estimation Techniques

Six of the seven measures used in arriving at the current impact assessment are based on employment data, while one is based on the number of establishments. The employment data was derived using government released ES202 and County Business Pattern data. ES202 metro employment data is available from 2000–2001 at the 4-digit NAICS level from the Bureau of Labor Statistics (BLS). The ES202 reports payroll employment derived from the quarterly tax report submitted to state Employment Development Departments (EDDs) that are subject to unemployment insurance (UI) laws. It has been appropriately re-benchmarked to the former SIC classification system to include history through 1980 by Economy.com. However, in order to obtain a more detailed level of industry classification, specifically, the 5-digit NAICS level data, County Business Pattern (CBP) employment data must be obtained from the U.S. Census Bureau. CBP data, available from 1998–2001, was used to calculate the shares of employment at a more detailed NAICS level, and then applied to the higher NAICS level from ES202 for those years. Since ES202 data at the 4-digit NAICS level is available for 2002, the employment shares from the 2001 CBP are then redistributed using the absolute change in ES202 employment from 2001 to 2002. Similarly, the 1998 CBP employment shares are applied to the 1998 ES202 and then carried back one year to 1997, thus maintaining a realm of consistency and producing detailed historical estimates through 1997.

NAICS Life Science Industry Group325411 Medicinal and botanical manufacturing325412 Pharmaceutical Preparation manufacturing325413 In-vitro diagnostic substance manufacturing325414 Other biological product manufacturing5417102 Biological R&D339111 Laboratory apparatus and furniture mfg.339112 Surgical and medical instrument manufacturing339113 Surgical appliance and supplies manufacturing339114 Dental equipment and supplies manufacturing339115 Ophthalmic goods manufacturing339116 Dental laboratories334510 Electromedical apparatus manufacturing334517 Irradiation apparatus manufacturing

Defining Life Science


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For the Biological R&D industry, represented by the 7-digit NAICS code 5417102, data is publicly available from the 1997 Economic Census. Employment shares from the 2001 CBP and historical trends from the ES202 data set were applied in obtaining more current estimates.

By applying these estimation techniques, detailed metro employment data up to the 5-digit NAICS level (and 7-digit for Biological R&D) is compiled for 1997 to 2002. Twelve (12) metropolitan areas were examined as a basis for relative comparison. The 12 metros examined all engage in some type of biotech/life science activity. Those metros are: Austin-San Marcos, Boston, Los-Angeles-Long Beach, Oakland, Orange County, Philadelphia, Raleigh-Durham-Chapel Hill, San Diego, San Francisco, San Jose, Seattle-Bellevue-Everett, and Washington, D.C. Ventura was accounted for as an addendum, mainly to recognize Amgen as a world leader in the biotech industry. However, since it is the only biotech establishment in Ventura, it would not be justified to include it in the rankings among the other metros.

Finally, establishment data at the detailed 5-digit NAICS level was compiled from the County Business Patterns and then processed into the appropriate categories as described earlier in this section.


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Overall Composite Index

Background and RelevanceThis section provides a brief overview of all components discussed within the innovation pipeline and current impact assessment sections. The individual components are R&D inputs, risk capital, human capital, biotech workforce and current impact. The first four focus on topics such as research and innovation, the availability of financial resources, local talent pool, and occupational strengths. Current impact, as discussed earlier, explains where the metro currently stands in the nation in terms of industry employment, while emphasizing areas of high concentration, growth and diversity.

The overall composite index combines all components and creates an overall ranking of the top biotech and life science centers in the country. While each component is vital in assessing overall metro performance, some components are undoubtedly of higher importance than others and should be given more weight, accordingly. The R&D component is accorded a weight that is 1.5 times greater on the overall composite index since it is difficult to build an industry without the proper R&D infrastructure, making R&D, arguably, the most important component. Without new ideas and innovation, an industry would struggle to compete in the global market and face many local challenges. The presence of R&D serves as a basis for attracting high-knowledge workers, biotech and pharmaceutical companies, and various forms of venture capital investment. Similarly, the current impact index carries a weight that is twice as great on the overall composite. The current impact essentially describes the outcome or impact as a result of the innovation pipeline measures. It receives greater weight since it directly explains a metro’s regional economic performance within a given industry.

Metro FindingsThe following table provides a summary of the main individual components, the overall composite index, along with the metros and their associated scores and rankings. Since two versions of the current impact assessment were constructed, one for biotech and one for life science, there are also two versions of the overall composite index. The first table is the biotech overall composite.


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San Diego ranks 1st in the nation in the biotech overall composite index. Much of this can be attributed to its relative 1st-place ranking within the R&D and current impact indices. Boston is



CompositeScore




CompositeScore

Raleigh-Durham-Chapel Hill 1 100.0 San Diego 1 100.0 San Diego 1 100.0Boston 2 99.2 Boston NECMA 2 80.3 Boston NECMA 2 95.1San Jose 3 95.6 San Jose 3 78.1 Raleigh-Durham-Chapel Hill 3 92.5Oakland 4 93.9 Raleigh-Durham-Chapel Hill 4 69.4 San Jose 4 87.8San Diego 5 91.7 Seattle-Bellevue-Everett 5 68.4 Seattle-Bellevue-Everett 5 83.8Washington, D.C. 6 86.3 Washington, D.C. 6 64.8 Washington, D.C. 6 79.4Seattle-Bellevue-Everett 7 78.3 Oakland 7 64.2 Philadelphia 7 76.5Philadelphia 8 77.7 San Francisco 8 63.6 San Francisco 8 75.8San Francisco 9 76.1 Philadelphia 9 58.5 Oakland 9 74.3Los Angeles-Long Beach 10 70.8 Los Angeles-Long Beach 10 50.0 Los Angeles-Long Beach 10 66.5Orange County 11 67.7 Orange County 11 29.2 Orange County 11 54.1Austin-San Marcos 12 42.2 Austin-San Marcos 12 27.8 Austin-San Marcos 12 47.8

4. Biotech Workforce5. Current Impact

(Biotech)Overall

Composite

Milken Institute's 2004 Biotech IndexBy Category and Overall Composite


60 65 70 75 80 85 90 95 100San Diego's Relative Score

1

2

3

4

5

6

Biotech Composite IndexSan Diego's Relative Score

Series1 100 100 91.7 79.7 97.4 100

1 2 3 4 5 6

Current Impact (Biotech) (San Diego = 1st Place)

Biotech Workforce (San Diego = 5th Place)

Biotech Research & Development Assets (San Diego = 1st Place)

Biotech Human Capital Capacity (San Diego = 4th Place)

Biotech Risk Capital & Entrepreneurial Infrastructure (San Diego = 3rd Place)

Biotech Index (San Diego = 1st Place)

San Diego

U.S. Avg.

1 2 3 4 5 Total100.0 97.4 79.7 91.7 100.0 100.0

78.5 73.9 62.6 73.9 N/A N/A

1

2

3

4

5

Total


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Boston(95.1)

San Diego(100.0)

Austin(47.8)

Philadelphia(76.5)

Seattle (83.8)

Los Angeles(66.5)

Oakland (74.3)

Orange County(54.1)

San Jose (87.8)

SanFrancisco(75.8)


Raleigh(92.5)

Milken Institute Biotech Poles2004


a close 2nd with a relative score of 95.1, followed by Raleigh-Durham and San Jose with scores of 92.5 and 87.8, respectively. San Diego’s relative placement proves that the metro has successfully capitalized on its regional inputs. Its high concentration of biotech employment and research institutions has established a knowledgeable labor force, increased the intensity of human capital and created or lured innovative and successful biotech companies to the region. The following map illustrates our overall composite measure of biotech centers, or as we call them, “Biotech Poles,” for the relative biotech pull that they exert.

Replacing the biotech current impact index in the overall composite with the life science current impact index and keeping the other components constant shifts the rankings in the overall composite index. Again, as stated earlier in the report, it is necessary to distinguish between biotech and life science, since life science includes medical devices and pharmaceutical preparation in addition to biotech. Those metros highly engaged in pharmaceutical and medical devices manufacturing activity, in addition to their biotech presence, rise accordingly.

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The table below is the overall composite index with the life science current impact index, producing a different set of rankings.

San Diego ranks 2nd on the overall life science composite index. With Boston’s high concentration of pharmaceutical industries, the metro moves up to 1st-place as the nation’s top locale for life



CompositeScore




CompositeScore

Raleigh-Durham-Chapel Hill 1 100.0 Boston NECMA 1 100.0 Boston NECMA 1 100.0Boston 2 99.2 San Diego 2 91.6 San Diego 2 95.9San Jose 3 95.6 San Jose 3 85.4 San Jose 3 88.9Oakland 4 93.9 Philadelphia 4 78.6 Raleigh-Durham-Chapel Hill 4 88.8San Diego 5 91.7 Orange County 5 73.9 Philadelphia 5 81.8Washington, D.C. 6 86.3 San Francisco 6 70.0 Seattle-Bellevue-Everett 6 81.1Seattle-Bellevue-Everett 7 78.3 Los Angeles-Long Beach 7 68.2 San Francisco 7 76.7Philadelphia 77.7 Oakland 8 67.1 Washington, D.C. 8 75.8San Francisco 9 76.1 Seattle-Bellevue-Everett 9 63.9 Oakland 9 74.1Los Angeles-Long Beach 10 70.8 Raleigh-Durham-Chapel Hill 10 62.2 Los Angeles-Long Beach 10 71.3Orange County 11 67.7 Washington, D.C. 11 57.1 Orange County 11 67.6Austin-San Marcos 12 42.2 Austin-San Marcos 12 37.8 Austin-San Marcos 12 50.2

4. Biotech Workforce5.Current Impact(Life Science)

OverallComposite

Milken Institute's 2004 Life Science IndexBy Category and Overall Composite


8

60 65 70 75 80 85 90 95 100San Diego's Relative Score

1

2

3

4

5

6

Life Science Composite IndexSan Diego's Relative Score

Series1 95.9 91.6 91.7 79.7 97.4 100

1 2 3 4 5 6

Current Impact (Life Science) (San Diego = 2nd Place)

Biotech Workforce (San Diego = 5th Place)

Biotech Research & Development Assets (San Diego = 1st Place)

Biotech Human Capital Capacity (San Diego = 4th Place)

Biotech Risk Capital & Entrepreneurial Infrastructure (San Diego = 3rd Place)

Life Science Index (San Diego = 2nd Place)

San Diego

U.S. Avg.

1 2 3 4 5 Total

100.0 97.4 79.7 91.7 91.6 95.9

78.5 73.9 62.6 73.9 N/A N/A

1

2

3

4

5

Total


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science. Boston is also well equipped with respect to the manufacturing of medical devices as noted in The Economic Contributions of Health Care to New England50, in another report conducted by the Milken Institute. San Jose and Raleigh-Durham finish 3rd and 4th, respectively, on the life science overall composite index. The Milken Institute’s nationwide mapping of “Life Science Poles” demonstrates life science-driven metro areas on the basis of the overall life composite measure. Life Science Poles capture the spatial intensity of life science-driven sectors.

MethodologyMathematically speaking, where ƒ stands for “is a function of”:

— biotech overall composite index = ƒ (1.5*R&D input index, risk capital index, human capital index, biotech workforce index, 2* biotech current impact index); and

— life science overall composite index = ƒ (1.5*R&D input index, risk capital index, human capital index, biotech workforce index, 2* life science current impact index).

For a detailed methodology on each component and its subcomponents, please see the methodology section pertaining to that component.

50 DeVol, Ross and Rob Koepp. 2003. The Economic Contributions of Health Care to New England, Santa Monica: Milken Institute.


Boston(100.0)

San Diego(95.9)

Austin(50.2)

Philadelphia(81.8)

Seattle (81.1)

Los Angeles(71.3)

Oakland (74.1)

Orange County(67.6)

San Jose (88.9)

SanFrancisco(76.7)


Raleigh(88.8)

Milken Institute Life Science Poles2004

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Multiplier Impacts

Background and RelevanceTo better understand the importance of the biotech/life science industry in San Diego we must analyze its impact on the overall economy. Multiplicative values known as “multipliers” allow us to do this by quantifying how employment and output in biotech/life science industry ripple through other regional economic sectors. In addition to providing numerical data on an industry’s regional impact, economic multipliers also bring to light region-wide interdependencies and inter-industry relationships. It is important to appreciate these relationships because they directly influence how regional economies respond to changes in long-term industry structure and business cycles.

Within the concept of multiplier impacts, three key forces are at play. The first is what is known as the direct impact, which measures how an industry’s employment, wages and output immediately translate into economic stimulus for other sectors of the economy that support the industry (for example, suppliers of legal, financial, and advertising services).

The second multiplier force relates to indirect impact. This represents a further extension of stimulus, the sort given to tertiary economic activity that, although not directly interacting with the studied industry, nevertheless is supported by it through a region’s overarching economic framework. An example of an indirect impact of the biotech industry is the wholesale and retail distribution of drug products in the region. The cumulative employment and wages generated by all of this tightly and extensively interconnected economic activity ripples throughout the regional economy. The wealth created leads to greater purchases of goods and services. This, in turn, produces still more income that becomes available to a region’s residents who recycle their earnings back into their local economies.

The net result of this latter process is known as induced impact. For example, in addition to the consumer spending by chemists, microbiologists, biotech researchers, and pharmacists, spending by restaurant workers, retail clerks, real estate agents, contractors, and many others indirectly dependent upon the industry is also accounted for in this measure. It is through the aggregation of these impacts, also referred to as the total impact, that a given industry contributes to its local economy.

Multiplier Impacts

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Metro FindingsIn 2002, the biotech industry in San Diego employed more than 14,500 workers, producing a gross metro product of $2.7 billion. These figures represent the direct impact of the biotech sector on the regional economy. When the full extent of multiplicative dynamics are accounted for by applying total impact measures, biotech can be recognized as responsible for 38,200 jobs, or 3.1 percent of all nonfarm employment, and $5.7 billion worth of output, or 5.2 percent of all real gross metro product, throughout San Diego.

The additional 23,700 jobs and $2.9 billion in these total impact figures stem from the indirect and induced impacts that biotech brings to the rest of the economy. The indirect impact generates an additional 8,400 jobs and $815.7 million worth of output, while the induced effect adds another 15,300 jobs and $2.1 billion worth of output. Together they contribute to the total impact that the biotech sector brings to the region.

Consequently, the total biotech employment multiplier in San Diego is 2.6 (38,200/14,500). In other words, each job in San Diego’s biotech sector produces an additional 1.6 jobs in other sectors. By the same token, since 1.2 percent of total employment in San Diego is in biotech, the industry ultimately accounts for nearly 3.1 percent of total employment in San Diego when including the multiplier effect (1.2 percent multiplied by 2.6).

Between 1997 and 2002, the biotech industry accounted for 1.5 percent of total nonfarm employment growth in San Diego. When incorporating for the total impacts, biotech growth comprised of 4.1 percent of total growth. With respect to output, biotech was responsible for 3.5 percent of total non-farm growth in output from 1997 to 2002. When adjusting for the total impacts, that growth expanded to 7.4 percent of the total share.

The following table provides a breakdown of the direct, indirect and induced impacts on employment in San Diego by the following industry classifications: biotech, medical devices, biomedical and life science.

Industry Direct Indirect Induced Total MultiplierBiotech 14.5 8.4 15.3 38.2 2.6Medical Devices 5.7 3.2 5.4 14.3 2.5Bio-Medical 20.2 11.5 20.6 52.4 2.6Life Science Total 21.0 12.6 22.0 55.6 2.7Sources: Milken Institute, BEA.

Employment (In Thous.)

Employment Multiplier ImpactsSan Diego, CA MSA


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Similarly, a total output multiplier of 2.1 indicates that for each dollar of output produced in the biotech sector, an additional $1.10 worth of output is generated outside of it.

The employment multiplier, with respect to the life science industry, is nearly equivalent to the one represented by biotech. This suggests that the relative contribution of the biotech and medical devices industries in terms of employment is similar. In absolute terms, however, biotech contributes an additional 23,700 jobs, while medical devices adds another 8,600 jobs.

Altogether, the life science industry in San Diego MSA is responsible for 55,600 jobs, or nearly 5 percent of all nonagricultural employment in the region. Of those, 21,000 are accounted for directly, while 12,600 and 21,000 are generated through the indirect and induced effects, respectively. For every job within the life sciences in San Diego, an additional 1.7 are created in all other sectors (see graphs below).

Similarly, the life science industry in San Diego MSA is responsible for $5.8 billion, or 5.3 percent of gross metro product in the region. $2.8 billion is registered directly, while $843 million and $2.2 billion are generated through the indirect and induced impacts, respectively. For each dollar of output produced in the life sciences sector in San Diego, an additional $1.10 worth of output is generated beyond it.

Industry Direct Indirect Induced Total MultiplierBiotech 2701.0 815.7 2142.0 5658.8 2.1Medical Devices 76.6 20.7 35.8 133.1 1.7Bio-Medical 2777.7 836.4 2177.8 5791.9 2.1Life Science Total 2796.0 842.8 2185.8 5824.6 2.1Sources: Milken Institute, BEA.

San Diego, CA MSA

Output (In US$ Millions)

Output Multiplier Impacts

Total Impact

60

50

40

30

20

10

0

Employment (Ths.)


Total Impact of San Diego Life ScienceDirect, Indirect and Induced Impacts - Employment, 2002


Total Impact

7

6

5

4

3

2

1

0

Output (Billions of $U.S.)


Total Impact of San Diego Life ScienceDirect, Indirect and Induced Impacts - Output, 2002


Total = 55.6

21.0

12.6

21.0

Total = $5.8 Billion

22

.843

2.8

Multiplier Impacts

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MethodologyThe Milken Institute utilized the Regional Input-Output Modeling System (RIMS II) developed by the Bureau of Economic Analysis (BEA) at the U.S. Department of Commerce to conduct its systematic economic multiplier impact analysis. This methodology makes use of the input-output structure of U.S. industries to estimate the total impact one industry has on the wider economy.

The employment and output multipliers from RIMS are applied to the appropriate employment and output estimates from the Bureau of Labor Statistics (BLS) and Economy.com, respectively. The input-output matrix from RIMS provides the necessary coefficients or multipliers needed to estimate the total number of jobs and value of wealth generated in all other sectors through the biotech industry. Thus, the total impact is calculated by applying the multiplier to the direct impact for either employment or output. Further statistical estimation is conducted to derive the difference between the induced and indirect shares.

The BEA multipliers are based on 2000 regional data as defined by the standard industrial classification (SIC) system. Since employment data from the current impact assessment is based on the more current North American Industry Classification (NAICS) system, the SIC-based data was converted into NAICS to maintain consistency throughout the entire report. The U.S. Census provides a mapping of the two classifications utilized in translating SIC to NAICS and vice versa. Furthermore, the Office of Management and Budget contains the official documentation behind the NAICS classification.


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ConclusionBased upon our evaluation criteria, San Diego ranks as the top biotechnology cluster in the country, edging past 2nd-place Boston. If the benchmarking criteria were adjusted somewhat, Boston might surpass it. In many respects the two are virtually tied, but San Diego’s higher current impact assessment, better R&D score and faster growth over the past five years give it a slight advantage. Cambridge-based (Boston MSA) Biogen’s recent acquisition of IDEC might impact these placements in the future.

Many in the industry view San Francisco as holding a top spot, but that perception is based upon looking at the entire San Francisco Bay Area and absolute measures of performance. While the Bay Area has many assets, when you split the San Francisco metro area out separately and scale the biotech indicators by population, employment, or GMP, its relative scores are not as impressive. On the other hand, if industry R&D expenditures by such biotech giants as Genentech and Chiron were publicly available by metro area, San Francisco would undoubtedly have a higher score.

Raleigh-Durham is a rising biotech cluster as denoted by its 1st–place finish in both the human capital and biotech workforce categories (and its overall 3rd place in biotech), although the metro’s smaller size must be taken into account. San Jose is the top scoring Bay Area metro biotech cluster at 4th and grew faster over the last five years than San Diego.

When extending the analysis to life science clusters, including medical devices and pharmaceuticals, Boston moves past San Diego to 1st overall. Boston’s top position in medical devices and strength in pharmaceuticals give it more diversity. San Jose moves to 3rd in life sciences, courtesy of its 3rd place in medical devices just behind Orange County. Raleigh-Durham slips to 4th in life sciences. Philadelphia, courtesy of pharmaceuticals, ranked 5th as a life science cluster based upon our evaluation criteria.

The biotechnology and life science cluster plays a central role as an economic engine of San Diego.

• Altogether, the life science industry in San Diego MSA is responsible for 55,600 jobs, or nearly 5 percent of all nonagricultural employment in the region. Of those, 21,000 are accounted for directly, while 12,600 and 21,000 are generated through the indirect and induced effects, respectively. For every job within the life sciences in San Diego, an additional 1.7 jobs are created in all other sectors.

• Similarly, the life science industry in San Diego MSA is responsible for $5.8 billion, or 5.3 percent of gross metro product in the region. $2.8 billion is registered directly, while $843 million and $2.2 billion are generated through the indirect and induced impacts,

Conclusion

84

respectively. For each dollar of output produced in the life sciences sector in San Diego, an additional $1.10 of output is generated beyond it.

• Between 1997 and 2002, the biotech industry accounted for 1.5 percent of total nonfarm employment growth in San Diego. When incorporating the total impacts, biotech growth comprised of 4.1 percent of total growth. With respect to output, biotech was responsible for 3.5 percent of total non-farm growth in output from 1997 to 2002. When adjusting for the total impacts, it accounted for 7.4 percent of the aggregate growth in output.

As a national leader in biotechnology and life sciences, San Diego faces enormous opportunities and challenges in enhancing or preserving its position. Ensuring that biotechnology continues to contribute a disproportionate share of future job and income growth should be a top priority for its cluster members, citizens and business and community leaders. Stakeholders must shepherd their talents and resources to address the following issues:

• Despite its strength in overall R&D, San Diego should acquire a greater share of funding distributed to research universities. UCSD is a great resource, but lack of scale could present it with challenges in the future.

• While San Diego attracts a high level of venture capital, most of the funds come from outside the region. More indigenous or local venture capital firms are needed to exploit the inventiveness of entrepreneurs in the area. San Diego must reduce its dependence upon VCs flying to the community by air. More local venture capital would improve the entrepreneurial infrastructure of the cluster as well. BIOCOM President Joe Panetta acknowledges that attracting more venture capital firms to San Diego is one of its strategic initiatives.

• San Diego has been very successful at recruiting some of the best research talent from around the country, and even the world. Nevertheless, it must continue to increase home grown talent through UCSD and California State University, San Diego. Encouraging programs are underway such as dual-degree education like the joint MD/ MBA program, the MD/MS in bioengineering program, and joint programs between UCSD and Cal State, San Diego.

• Additionally, more local human capital in biotechnology should be created because the high cost of living, especially housing, and rising congestion-related costs will make it more difficult to recruit young talent from other parts of the country.

• San Diego must create more profitable biotechnology firms. Most are still operating in a negative cash-flow position. This will limit growth of the cluster in the future.


85

• San Diego has many commercial success stories, but as its leading biotech firms begin to reach critical mass, they are acquired. While this can be seen as a source of strength because it allows wealth to circulate back to deployment in starting more firms, it needs a few large biotech anchor firms to add more stability to the ecosystem.

• A larger presence of pharmaceutical firms would create a deeper and richer management pool that the larger life science cluster could draw upon. It would increase the efficiency at which fledgling biotech firms capitalized on their innovative products and services.

• San Diego could enhance its future position as a biotech center by demonstrating an ability to manufacture more products locally as opposed to being heavily research-based. More cross-fertilization efforts would be available.

These observations should be understood in the context of San Diego as among the elite biotech clusters in the world. Innovative and collaborative approaches for maintaining growth must continue to be pursued. Pooling resources to retain and create biotechnology jobs, would enable the San Diego cluster to become an even greater economic force in the region. BIOCOM, UCSD CONNECT, San Diego Regional Economic Development Corporation and other trade groups and associations are vital support systems for progress.

Conclusion

Biotech R&D Assets

BiotechRank MSA

Natural LogScale

RelativeScore

1 Raleigh-Durham-Chapel Hill 6.18 100.02 San Francisco 5.69 92.13 Austin-San Marcos 5.22 84.54 San Jose 5.09 82.55 Seattle-Bellevue-Everett 5.05 81.76 Boston NECMA 4.67 75.67 Philadelphia 4.63 75.08 San Diego 4.63 74.99 Los Angeles-Long Beach 4.34 70.210 Orange County 3.70 60.011 Oakland 3.68 59.612 Washington, D.C. 3.68 59.6

U.S. 4.04 65.3

Per Capita, 2001Academic R&D to Biotech

BiotechRank MSA

Natural LogScale

RelativeScore

1 Raleigh-Durham-Chapel Hill 3.65 100.02 San Diego 2.32 63.73 Oakland 2.31 63.34 Washington, D.C. 2.27 62.15 Seattle-Bellevue-Everett 2.17 59.66 Austin-San Marcos 2.13 58.47 Boston NECMA 2.01 55.08 Philadelphia 1.28 35.29 Orange County 1.17 32.210 Los Angeles-Long Beach 0.93 25.511 San Jose 0.64 17.712 San Francisco 0.04 1.0

U.S. 1.76 48.2

NSF Research Funding to BiotechPer $100,000 GMP, 2003

BiotechRank MSA

Natural LogScale

RelativeScore

1 Boston NECMA 4.49 100.02 San Diego 3.06 68.23 San Jose 2.65 58.94 Seattle-Bellevue-Everett 2.27 50.65 Philadelphia 2.22 49.36 Los Angeles-Long Beach 2.18 48.47 Washington, D.C. 2.16 48.08 Austin-San Marcos 1.83 40.79 Raleigh-Durham-Chapel Hill 1.66 37.010 San Francisco 1.64 36.511 Oakland 1.41 31.412 Orange County 0.87 19.5

U.S. N/A N/A

Number of STTR Awards to BiotechPer 100,000 Businesses, 2000

BiotechRank MSA

Natural LogScale

RelativeScore

1 Boston NECMA 4.97 100.02 San Diego 3.26 65.53 Los Angeles-Long Beach 2.90 58.44 Washington, D.C. 2.75 55.35 San Jose 2.50 50.36 Seattle-Bellevue-Everett 2.35 47.27 Philadelphia 2.26 45.48 Orange County 1.89 38.19 Raleigh-Durham-Chapel Hill 1.82 36.610 Austin-San Marcos 1.38 27.811 San Francisco 1.10 22.012 Oakland 1.02 20.6

U.S. N/A N/A

STTR Award to BiotechPer $Million GMP, 2000

BiotechRank MSA

Natural LogScale

RelativeScore

1 Boston NECMA 5.57 100.02 San Diego 4.10 73.53 San Jose 3.86 69.24 Seattle-Bellevue-Everett 3.72 66.85 Los Angeles-Long Beach 3.41 61.26 Washington, D.C. 3.27 58.67 Philadelphia 3.16 56.68 San Francisco 3.14 56.39 Raleigh-Durham-Chapel Hill 2.82 50.510 Austin-San Marcos 2.76 49.511 Oakland 2.52 45.312 Orange County 1.95 34.9

U.S. N/A N/A

Number of SBIR Awards to Biotech FirmsPer Million Pop., 2000

BiotechRank MSA

Natural LogScale

RelativeScore

1 Washington, D.C. 3.75 100.02 Austin-San Marcos 3.71 98.93 San Diego 3.67 97.84 Philadelphia 3.64 96.95 Orange County 3.50 93.26 Raleigh-Durham-Chapel Hill 3.43 91.57 Oakland 3.37 89.78 Seattle-Bellevue-Everett 3.37 89.79 Los Angeles-Long Beach 3.33 88.810 Boston NECMA 3.25 86.511 San Jose 2.94 78.412 San Francisco 0.00 0.0

U.S. 3.26 86.8

Competitive NSF Funding Rate in Biotech FieldsPercent, 2003

86


Appendix

87

Biotech R&D Assets

BiotechRank MSA

Natural LogScale

RelativeScore

1 Raleigh-Durham-Chapel Hill 6.21 100.02 San Diego 5.78 93.03 Boston NECMA 5.66 91.24 Seattle-Bellevue-Everett 5.56 89.55 San Francisco 5.52 88.96 San Jose 4.99 80.37 Philadelphia 4.95 79.88 Washington, D.C. 4.64 74.79 Oakland 4.31 69.310 Los Angeles-Long Beach 4.19 67.511 Orange County 3.51 56.512 Austin-San Marcos 3.51 56.5

U.S. 4.09 65.9

NIH Funding to Metro CitiesPer Capita, 2002

BiotechRank MSA

Natural LogScale

RelativeScore

1 San Diego 9.29 100.02 Seattle-Bellevue-Everett 9.04 97.33 San Francisco 8.31 89.44 Boston NECMA 8.08 87.05 Washington, D.C. 7.62 82.06 Philadelphia 7.31 78.67 Oakland 7.07 76.18 Los Angeles-Long Beach 6.97 75.09 San Jose 5.44 58.510 Orange County 2.37 25.511 Austin-San Marcos 0.00 0.012 Raleigh-Durham-Chapel Hill 0.00 0.0

U.S. 6.45 69.4

NIH Funding to InstitutesPer 100 Pop., 2002

BiotechRank MSA

Natural LogScale

RelativeScore

1 Raleigh-Durham-Chapel Hill 4.37 100.02 Philadelphia 3.24 74.03 San Francisco 3.13 71.64 Seattle-Bellevue-Everett 3.10 70.95 San Diego 2.83 64.76 San Jose 2.66 60.87 Boston NECMA 2.59 59.18 Los Angeles-Long Beach 2.40 54.99 Orange County 1.55 35.510 Washington, D.C. 1.31 30.011 Austin-San Marcos 0.00 0.012 Oakland 0.00 0.0

U.S. 2.32 53.2

NIH Funding to Research UniversitiesPer $10,000 GMP, 2002

BiotechRank MSA

CompositeScore

RebasedComposite Score

1 San Diego 79.7 100.02 Boston NECMA 78.9 99.03 Seattle-Bellevue-Everett 76.8 96.44 Raleigh-Durham-Chapel Hill 73.2 91.95 Philadelphia 67.6 84.96 Washington, D.C. 63.9 80.37 San Jose 60.0 75.38 Los Angeles-Long Beach 59.9 75.39 San Francisco 56.6 71.110 Oakland 53.2 66.711 Orange County 43.0 54.012 Austin-San Marcos 41.4 52.0

U.S. 62.5 78.5

Biotech R&D AssetsComposite Index, 2004

San Diego CaliforniaPercent of

California TotalBiotech Research Institutes 12 47 26%NIH Awarded Research Projects 745 1,213 61%NIH Awarded Research Funding 316.2 ($ Mil.) 537.8 ($ Mil.) 59%Sources: National Institutes of Health (NIH), Milken Institute.

San Diego Biotech Research2003

Appendix

88

Biotech Risk Capital & Entrepreneurial Infrastructure

BiotechRank MSA

Natural LogScale

RelativeScore

1 Washington, D.C. 5.14 100.02 San Jose 4.95 96.23 Los Angeles-Long Beach 4.87 94.74 Boston NECMA 4.79 93.05 San Diego 4.77 92.66 Orange County 4.73 91.97 San Francisco 4.59 89.28 Raleigh-Durham-Chapel Hill 4.54 88.39 Seattle-Bellevue-Everett 4.44 86.310 Philadelphia 4.32 84.111 Austin-San Marcos 0.32 6.212 Oakland N/A N/A

U.S. 4.61 89.5

Biotech VC Investment GrowthAnnual Average, 2000-2003

BiotechRank MSA

Natural LogScale

RelativeScore

1 San Jose 4.91 100.02 Raleigh-Durham-Chapel Hill 4.57 93.13 San Diego 4.32 88.04 Boston NECMA 4.15 84.55 San Francisco 4.03 82.16 Seattle-Bellevue-Everett 3.98 81.17 Orange County 3.46 70.68 Los Angeles-Long Beach 3.44 70.19 Washington, D.C. 3.38 68.910 Philadelphia 3.15 64.111 Austin-San Marcos 2.10 42.812 Oakland N/A N/A

U.S. 3.31 67.4

Number of Biotech Firms Receiving VCPer 1,000 Biotech Firms, Annual Average, 2000-2003

BiotechRank MSA

Natural LogScale

RelativeScore

1 Los Angeles-Long Beach 5.24 100.02 Orange County 5.22 99.63 San Jose 4.91 93.74 San Francisco 4.91 93.75 Washington, D.C. 4.84 92.46 Boston NECMA 4.71 89.87 San Diego 4.62 88.28 Philadelphia 4.52 86.39 Seattle-Bellevue-Everett 4.52 86.310 Raleigh-Durham-Chapel Hill 4.25 81.111 Austin-San Marcos 2.37 45.312 Oakland N/A N/A

U.S. 4.61 87.9

Increase in Number of Biotech Firms Receiving VCAnnual Average, 2000-2003

BiotechRank MSA

Natural LogScale

RelativeScore

1 San Jose 4.07 100.02 San Diego 4.01 98.63 Raleigh-Durham-Chapel Hill 3.44 84.64 Seattle-Bellevue-Everett 3.32 81.65 Boston NECMA 3.30 81.26 San Francisco 2.98 73.37 Orange County 2.41 59.38 Los Angeles-Long Beach 1.88 46.19 Washington, D.C. 1.85 45.410 Philadelphia 1.44 35.511 Austin-San Marcos 1.41 34.612 Oakland N/A N/A

U.S. 1.86 45.7

Biotech Venture Capital InvestmentPer $100,000 GMP, Annual Average, 2000-2003

BiotechRank MSA

Natural LogScale

RelativeScore

1 San Francisco 3.63 100.02 San Jose 3.52 97.13 Raleigh-Durham-Chapel Hill 3.21 88.64 San Diego 3.18 87.75 Boston NECMA 2.82 77.86 Oakland 2.77 76.37 Seattle-Bellevue-Everett 2.44 67.28 Washington, D.C. 2.39 65.99 Philadelphia 2.32 63.910 Austin-San Marcos 1.01 27.811 Orange County 0.94 25.912 Los Angeles-Long Beach 0.87 24.1

U.S. 1.61 44.4

Biotech Patents IssuedPer 100,000 Pop., 1996-1999

BiotechRank MSA

Natural LogScale

RelativeScore

1 San Francisco 4.54 100.02 San Jose 4.12 90.83 Oakland 4.10 90.44 Washington, D.C. 4.05 89.25 Boston NECMA 3.99 87.96 Philadelphia 3.89 85.77 San Diego 3.83 84.48 Raleigh-Durham-Chapel Hill 3.80 83.79 Orange County 3.38 74.510 Seattle-Bellevue-Everett 3.37 74.211 Los Angeles-Long Beach 3.32 73.212 Austin-San Marcos 3.15 69.3

U.S. 3.90 85.9

Biotech Patents IssuedPer 1,000 Biotech Workers, 1996-1999


89

Biotech Risk Capital & Entrepreneurial Infrastructure

BiotechRank MSA

Natural LogScale

RelativeScore

1 San Francisco 5.35 100.02 Raleigh-Durham-Chapel Hill 4.93 92.13 Oakland 4.80 89.84 San Diego 4.80 89.75 San Jose 4.76 89.06 Boston NECMA 4.42 82.77 Seattle-Bellevue-Everett 4.01 74.98 Washington, D.C. 3.79 70.99 Philadelphia 3.74 69.910 Orange County 2.65 49.611 Los Angeles-Long Beach 2.26 42.212 Austin-San Marcos 2.01 37.6

U.S. 2.91 54.3

Biotech Patent CitationsPer Million Pop., 1996-1999

BiotechRank MSA

Natural LogScale

RelativeScore

1 San Francisco 3.96 100.02 Oakland 3.84 97.03 Boston NECMA 3.29 83.04 Raleigh-Durham-Chapel Hill 3.21 81.05 San Diego 3.15 79.66 Washington, D.C. 3.14 79.47 San Jose 3.06 77.28 Philadelphia 3.01 76.09 Orange County 2.79 70.610 Seattle-Bellevue-Everett 2.64 66.611 Los Angeles-Long Beach 2.40 60.712 Austin-San Marcos 1.85 46.7

U.S. 2.89 73.1

Biotech Patent CitationsPer 1,000 Biotech Workers, 1996-1999

BiotechRank MSA

Natural LogScale

RelativeScore

1 Austin-San Marcos 4.04 100.02 Washington, D.C. 3.40 84.23 Raleigh-Durham-Chapel Hill 3.37 83.34 Seattle-Bellevue-Everett 3.19 78.95 San Diego 3.12 77.16 Oakland 3.05 75.47 San Jose 2.96 73.28 Orange County 2.74 67.89 Los Angeles-Long Beach 2.73 67.510 Philadelphia 2.64 65.211 San Francisco 2.58 63.912 Boston NECMA 2.47 61.0

U.S. 3.03 74.9

Business StartsPer 1,000 Businesses, 2002

BiotechRank MSA

Natural LogScale

RelativeScore

1 San Diego 4.73 100.02 San Francisco 4.64 98.13 San Jose 4.39 92.84 Raleigh-Durham-Chapel Hill 4.37 92.45 Oakland 4.22 89.36 Orange County 3.87 81.87 Boston NECMA 3.67 77.58 Seattle-Bellevue-Everett 3.66 77.49 Austin-San Marcos 3.44 72.710 Philadelphia 3.42 72.311 Washington, D.C. 1.90 40.112 Los Angeles-Long Beach 0.00 0.0

U.S. 2.34 49.4

Tech Fast 500 Companies in Life SciencePer Million Businesses, 2003

BiotechRank MSA

CompositeScore


1 San Jose 91.0 100.02 San Francisco 90.0 98.93 San Diego 88.6 97.44 Raleigh-Durham-Chapel Hill 86.8 95.45 Boston NECMA 81.8 89.96 Seattle-Bellevue-Everett 77.4 85.17 Washington, D.C. 73.6 80.98 Philadelphia 70.3 77.39 Orange County 69.2 76.010 Los Angeles-Long Beach 57.9 63.611 Oakland 51.8 56.912 Austin-San Marcos 48.3 53.1

U.S. 67.2 73.9

Biotech Risk Capital & Entrepreneurial InfrastructureComposite Index, 2004

Appendix

90

Biotech Human Capital Investment

BiotechRank MSA

Natural LogScale

RelativeScore

1 Raleigh-Durham-Chapel Hill 4.51 100.02 Boston NECMA 3.79 84.13 Philadelphia 3.43 76.24 Seattle-Bellevue-Everett 3.29 73.15 Washington, D.C. 3.26 72.36 Oakland 3.23 71.77 San Jose 3.16 70.18 Los Angeles-Long Beach 2.95 65.69 San Diego 2.94 65.210 San Francisco 2.91 64.511 Austin-San Marcos 2.78 61.812 Orange County 1.91 42.4

U.S. 3.03 67.2

Biotech Graduate Students25-34-Year-Olds Per 10,000 Pop., 2001

BiotechRank MSA

Natural LogScale

RelativeScore

1 Raleigh-Durham-Chapel Hill 4.64 100.02 Boston NECMA 3.59 77.53 Seattle-Bellevue-Everett 3.36 72.54 San Jose 3.29 70.95 Oakland 3.28 70.86 Austin-San Marcos 3.09 66.77 Philadelphia 2.99 64.48 San Francisco 2.93 63.19 San Diego 2.90 62.610 Washington, D.C. 2.62 56.511 Los Angeles-Long Beach 2.52 54.412 Orange County 2.08 44.8

U.S. 2.77 59.7

Biotech PhDs Awarded25-34-Year-Olds Per 100,000 Pop., 2002

BiotechRank MSA

Natural LogScale

RelativeScore

1 Boston NECMA 6.13 100.02 Raleigh-Durham-Chapel Hill 6.13 99.93 San Jose 5.82 95.04 Seattle-Bellevue-Everett 5.32 86.85 San Diego 5.02 81.86 Philadelphia 5.01 81.67 Austin-San Marcos 4.97 81.18 Oakland 4.96 80.89 San Francisco 4.90 80.010 Los Angeles-Long Beach 4.35 70.911 Orange County 3.69 60.112 Washington, D.C. 3.42 55.8

U.S. 4.30 70.2

Biotech Postdocs Awarded25-34-Year-Olds Per 100,000 Pop., 2001

BiotechRank MSA

Natural LogScale

RelativeScore

1 San Jose 6.90 100.02 Seattle-Bellevue-Everett 6.69 97.03 San Diego 6.52 94.54 Boston NECMA 6.38 92.55 Oakland 6.27 90.86 Philadelphia 6.22 90.27 Austin-San Marcos 5.86 84.98 Los Angeles-Long Beach 5.73 83.19 Raleigh-Durham-Chapel Hill 5.51 79.810 Orange County 5.23 75.711 Washington, D.C. 3.71 53.712 San Francisco N/A N/A

U.S. 5.27 76.4

Biotech Postdocs Awarded25-34-Year-Olds Per Research University, 2001

BiotechRank MSA

Natural LogScale

RelativeScore

1 Oakland 2.20 100.02 Raleigh-Durham-Chapel Hill 2.17 98.93 San Diego 2.10 95.44 Seattle-Bellevue-Everett 2.04 93.05 Boston NECMA 1.83 83.36 Los Angeles-Long Beach 1.73 78.87 Austin-San Marcos 1.71 78.08 Washington, D.C. 1.62 73.69 Philadelphia 1.60 72.810 San Jose 1.35 61.411 San Francisco 1.31 59.812 Orange County 0.44 20.1

U.S. 1.67 76.1

Bachelor's Degrees Granted in Biotech FieldPercent of Total Bachelor's Degrees, 2001

BiotechRank MSA

Natural LogScale

RelativeScore

1 Raleigh-Durham-Chapel Hill 3.45 100.02 Boston NECMA 3.32 96.23 Washington, D.C. 2.96 85.94 Philadelphia 2.86 82.95 San Diego 2.85 82.46 Austin-San Marcos 2.70 78.17 San Jose 2.47 71.78 Oakland 2.09 60.79 Seattle-Bellevue-Everett 2.09 60.610 Orange County 1.92 55.611 Los Angeles-Long Beach 1.81 52.512 San Francisco 1.76 51.1

U.S. 2.49 72.2

Number of Biotech PhD Granting InstitutionsPer 10 Million Pop., 2002


91


BiotechRank MSA

Natural LogScale

RelativeScore

1 Boston NECMA 3.66 100.02 Raleigh-Durham-Chapel Hill 3.62 99.03 Washington, D.C. 3.35 91.74 Philadelphia 3.34 91.45 San Diego 3.03 82.86 Austin-San Marcos 2.83 77.57 San Jose 2.65 72.48 Seattle-Bellevue-Everett 2.53 69.39 Oakland 2.36 64.610 Orange County 2.16 59.111 Los Angeles-Long Beach 2.11 57.612 San Francisco 1.89 51.7

U.S. 2.99 81.8

Number of Biotech PhD Granting InstitutionsPer Million College Enrollees, 2002

BiotechRank MSA

Natural LogScale

RelativeScore

1 Raleigh-Durham-Chapel Hill 5.11 100.02 Boston NECMA 4.43 86.63 San Diego 4.34 84.94 San Jose 4.29 83.95 Seattle-Bellevue-Everett 4.26 83.26 Washington, D.C. 4.24 82.97 Oakland 4.19 81.88 San Francisco 4.12 80.69 Philadelphia 3.69 72.210 Los Angeles-Long Beach 3.53 69.111 Austin-San Marcos 3.17 61.912 Orange County 2.85 55.8

U.S. 3.55 69.5

Biotech ScientistsPer 100,000 Pop., 2002

BiotechRank MSA

Natural LogScale

RelativeScore

1 San Jose 3.01 100.02 Oakland 2.09 69.73 Boston NECMA 1.99 66.24 Orange County 1.87 62.15 San Diego 1.57 52.36 Washington, D.C. 1.40 46.77 Raleigh-Durham-Chapel Hill 1.37 45.78 Philadelphia 1.07 35.69 Los Angeles-Long Beach 0.94 31.110 San Francisco 0.56 18.611 Seattle-Bellevue-Everett 0.48 16.112 Austin-San Marcos 0.00 0.0

U.S. 0.91 30.2

Biotech EngineersPer 100,000 Pop., 2002

BiotechRank MSA

Natural LogScale

RelativeScore

1 Raleigh-Durham-Chapel Hill 4.44 100.02 Austin-San Marcos 3.77 84.83 San Diego 3.61 81.44 Oakland 3.51 79.05 Boston NECMA 3.32 74.96 Orange County 3.28 73.97 Seattle-Bellevue-Everett 3.21 72.48 Philadelphia 3.13 70.59 Washington, D.C. 3.02 68.010 Los Angeles-Long Beach 3.01 67.811 San Jose 2.78 62.612 San Francisco 2.64 59.4

U.S. 2.35 53.0

Recent Bachelor's Degrees in BiotechPer 10,000 Workers, 2002

BiotechRank MSA

Natural LogScale

RelativeScore

1 Raleigh-Durham-Chapel Hill 2.91 100.02 Boston NECMA 2.41 82.73 Washington, D.C. 1.92 66.14 Oakland 1.89 65.05 Seattle-Bellevue-Everett 1.85 63.56 San Diego 1.73 59.57 San Jose 1.44 49.38 Philadelphia 1.38 47.69 Los Angeles-Long Beach 1.36 46.810 San Francisco 0.89 30.611 Austin-San Marcos 0.72 24.712 Orange County 0.02 0.6

U.S. 0.53 18.3

Recent Master's Degrees in BiotechPer 10,000 Workers, 2002

BiotechRank MSA

Natural LogScale

RelativeScore

1 Raleigh-Durham-Chapel Hill 5.08 100.02 Boston NECMA 3.99 78.43 Oakland 3.73 73.44 Austin-San Marcos 3.65 71.85 San Jose 3.52 69.36 Seattle-Bellevue-Everett 3.35 66.07 Philadelphia 3.22 63.38 San Francisco 3.17 62.49 San Diego 3.07 60.410 Washington, D.C. 2.94 57.811 Los Angeles-Long Beach 2.75 54.112 Orange County 2.47 48.6

U.S. 2.23 43.8

Recent PhD Degrees in BiotechPer 100,000 Workers, 2002

Appendix

92


BiotechRank MSA

CompositeScore


1 Raleigh-Durham-Chapel Hill 93.7 100.02 Boston NECMA 84.5 90.23 Oakland 74.9 80.04 San Diego 74.7 79.75 San Jose 73.7 78.76 Philadelphia 69.6 74.37 Washington, D.C. 69.3 74.08 Seattle-Bellevue-Everett 69.1 73.79 Austin-San Marcos 62.4 66.610 Los Angeles-Long Beach 59.8 63.811 San Francisco 56.1 59.912 Orange County 48.4 51.7

U.S. 58.6 62.6

Biotech Human Capital InvestmentComposite Index, 2004


93

Biotech Workforce

BiotechRank MSA

Natural LogScale

RelativeScore

1 Raleigh-Durham-Chapel Hill 5.79 100.02 Boston NECMA 5.68 98.23 San Diego 5.26 90.94 Oakland 5.20 89.85 San Jose 5.17 89.36 Washington, D.C. 4.96 85.67 Seattle-Bellevue-Everett 4.95 85.68 San Francisco 4.69 81.19 Philadelphia 4.56 78.710 Los Angeles-Long Beach 4.50 77.711 Orange County 3.90 67.512 Austin-San Marcos 3.90 67.4

U.S. 4.44 76.6

Intensity of Life ScientistsPer 100,000 Workers, 2002

BiotechRank MSA

Natural LogScale

RelativeScore

1 Oakland 4.40 100.02 Raleigh-Durham-Chapel Hill 4.36 99.13 San Diego 4.35 98.84 San Jose 3.98 90.55 Philadelphia 3.84 87.16 Boston NECMA 3.31 75.17 San Francisco 3.09 70.38 Washington, D.C. 2.93 66.59 Orange County 2.22 50.410 Seattle-Bellevue-Everett 1.53 34.811 Los Angeles-Long Beach 1.38 31.312 Austin-San Marcos 0.00 0.0

U.S. 2.48 56.3

Intensity of Biochemists & BiophysicistsPer 100,000 Workers, 2002

BiotechRank MSA

Natural LogScale

RelativeScore

1 Washington, D.C. 3.78 100.02 Raleigh-Durham-Chapel Hill 3.63 96.13 San Jose 3.29 87.04 Boston NECMA 3.29 86.95 Oakland 2.89 76.46 Seattle-Bellevue-Everett 2.88 76.07 San Francisco 2.57 67.98 San Diego 2.35 62.29 Los Angeles-Long Beach 2.19 57.910 Orange County 2.14 56.611 Philadelphia 2.05 54.112 Austin-San Marcos 0.00 0.0

U.S. 2.45 64.7

Intensity of MicrobiologistsPer 100,000 Workers, 2002

BiotechRank MSA

Natural LogScale

RelativeScore

1 Raleigh-Durham-Chapel Hill 4.82 100.02 Oakland 4.64 96.33 San Diego 4.51 93.54 San Jose 4.39 91.15 Washington, D.C. 4.35 90.36 Seattle-Bellevue-Everett 4.17 86.57 Philadelphia 4.08 84.58 Boston NECMA 4.05 84.19 San Francisco 3.56 73.810 Orange County 2.88 59.711 Los Angeles-Long Beach 2.63 54.612 Austin-San Marcos 0.00 0.0

U.S. 3.52 72.9

Intensity of Biological ScientistsPer 100,000 Workers, 2002

BiotechRank MSA

Natural LogScale

RelativeScore

1 Boston NECMA 5.36 100.02 Raleigh-Durham-Chapel Hill 5.27 98.43 San Diego 4.51 84.14 Seattle-Bellevue-Everett 4.30 80.35 San Francisco 4.27 79.66 Los Angeles-Long Beach 4.24 79.27 Oakland 4.06 75.78 San Jose 4.04 75.59 Washington, D.C. 4.04 75.310 Austin-San Marcos 3.90 72.811 Philadelphia 3.40 63.512 Orange County 2.91 54.4

U.S. 3.81 71.1

Intensity of Medical ScientistsPer 100,000 Workers, 2002

BiotechRank MSA

Natural LogScale

RelativeScore

1 San Jose 3.64 100.02 Boston NECMA 3.16 86.93 Oakland 2.99 82.24 Orange County 2.60 71.55 San Diego 2.43 66.76 Washington, D.C. 2.06 56.77 Raleigh-Durham-Chapel Hill 2.02 55.68 Philadelphia 1.86 51.29 Los Angeles-Long Beach 1.83 50.210 Seattle-Bellevue-Everett 1.13 30.911 San Francisco 1.10 30.312 Austin-San Marcos 0.00 0.0

U.S. 1.72 47.3

Intensity of Biomedical EngineersPer 100,000 Workers, 2002

Appendix

94

Biotech Workforce

BiotechRank MSA

CompositeScore

Rebased CompositeScore

1 Raleigh-Durham-Chapel Hill 93.1 100.02 Boston NECMA 92.3 99.23 San Jose 89.0 95.64 Oakland 87.4 93.95 San Diego 85.3 91.76 Washington, D.C. 80.3 86.37 Seattle-Bellevue-Everett 72.9 78.38 Philadelphia 72.3 77.79 San Francisco 70.9 76.110 Los Angeles-Long Beach 65.9 70.811 Orange County 63.1 67.712 Austin-San Marcos 39.3 42.2

U.S. 68.8 73.9

Biotech WorkforceComposite Index, 2004


95

Current Impact – Biotech

MSA1 Boston NECMA 18,7412 San Diego 14,5423 Philadelphia 10,5544 Seattle-Bellevue-Everett 9,4645 Washington, D.C. 9,2666 San Jose 9,1747 Los Angeles-Long Beach 8,1458 San Francisco 6,9359 Raleigh-Durham-Chapel Hill 6,47410 Oakland 6,20811 Orange County 2,45012 Austin-San Marcos 1,419

Addendum: Ventura 5,797

Rank

Biotech Employment Size2002

Number MSA1 San Diego 5.452 San Jose 4.653 Raleigh-Durham-Chapel Hill 4.354 San Francisco 3.235 Seattle-Bellevue-Everett 3.226 Oakland 2.747 Boston NECMA 2.728 Philadelphia 2.029 Washington, D.C. 1.5210 Austin-San Marcos 0.9911 Los Angeles-Long Beach 0.9312 Orange County 0.80

Addendum: Ventura 9.53

Rank

Biotech Location Quotient2002

LQ(US=1)

MSA1 Washington, D.C. 123.22 Oakland 120.23 San Jose 114.64 San Diego 110.05 Seattle-Bellevue-Everett 108.86 San Francisco 106.07 Los Angeles-Long Beach 96.28 Raleigh-Durham-Chapel Hill 92.49 Boston NECMA 88.810 Philadelphia 81.611 Orange County 70.212 Austin-San Marcos 61.2


Biotech Relative Employment Growth1997-2002

RankIndex

(US=100)

Biotech IndustryEmployment - Concentration, Growth, and Size

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

50 60 70 80 90 100 110 120 130 140

RelativeGrowth 1997-2002 (Index U.S. = 100)


verage

=1.0)

Philadelphia

Wash.,D.C.

Raleigh-Durham

Austin

San Jose

San Francisco

Boston Seattle

San Diego

LosAngelesOrangeCo.

Oakland

BIOTECH Current ImpactEmployment

LevelLQ



# of Ind.LQ>2

# of Ind.LQ<0.5

# of Ind.growing>US

CompositeIndex

MSA 2002 2002 97-02 2001 2002 2002 2002 2002San Diego 78 100 89 80 100 100 80 100Boston NECMA 100 50 72 45 60 50 20 80San Jose 49 85 93 100 60 33 40 78Raleigh-Durham-Chapel Hill 35 80 75 61 80 100 40 69Seattle-Bellevue-Everett 50 59 88 32 60 50 60 68Washington, D.C. 49 28 100 64 40 50 100 65Oakland 33 50 98 47 60 50 100 64San Francisco 37 59 86 48 40 33 100 64Philadelphia 56 37 66 25 40 100 20 58Los Angeles-Long Beach 43 17 78 19 40 100 20 50Orange County 13 15 57 31 20 50 20 29Austin-San Marcos 8 18 50 34 40 33 40 28Addendum:Ventura* 31 175 167 28 60 33 80 111

DiversitySize and Performance

Current Impact Measures (CIM) - Scores for BiotechRanked by Composite Index

Appendix

96

Current Impact – Medical Devices

MSA1 Boston NECMA 18,9012 Los Angeles-Long Beach 12,9723 Orange County 11,3414 San Jose 9,0445 Philadelphia 6,6046 San Diego 5,7017 Oakland 4,7008 Seattle-Bellevue-Everett 4,4049 San Francisco 2,33010 Washington, D.C. 2,00311 Austin-San Marcos 1,86112 Raleigh-Durham-Chapel Hill 1,163

Addendum: Ventura 929

Medical Devices Employment Size2002

Rank Number MSA1 San Jose 3.572 Orange County 2.903 Boston NECMA 2.144 San Diego 1.665 Oakland 1.626 Seattle-Bellevue-Everett 1.167 Los Angeles-Long Beach 1.158 Austin-San Marcos 1.019 Philadelphia 0.9810 San Francisco 0.8411 Raleigh-Durham-Chapel Hill 0.6112 Washington, D.C. 0.26


Medical Devices Location Quotient2002

RankLQ

(US=1)

MSA1 Raleigh-Durham-Chapel Hill 127.82 Oakland 112.53 Philadelphia 108.24 Los Angeles-Long Beach 106.55 Austin-San Marcos 102.06 Orange County 96.77 Boston NECMA 94.48 San Francisco 92.69 San Jose 91.710 San Diego 90.511 Seattle-Bellevue-Everett 89.512 Washington, D.C. 82.6


Medical Devices Relative Employment Growth1997-2002

RankIndex

(US=100)

Medical Devices IndustryEmployment - Concentration, Growth, and Size

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

70 80 90 100 110 120 130

RelativeGrowth 1997-2002 (Index U.S. = 100)


verage

=1.0)

Philadelphia

Wash.,D.C. Raleigh-Durham

Austin

San Jose

San Francisco

Boston

Seattle

San Diego

LosAngeles

OrangeCo.

Oakland

MEDICAL DEVICES Current ImpactEmployment

LevelLQ



# of Ind.LQ>2

# of Ind.LQ<0.5

# of Ind.growing>US Composite

MSA 2002 2002 97-02 2001 2002 2002 2002 2002Boston NECMA 100 60 74 56 86 50 67 100Orange County 60 81 76 80 100 100 67 95San Jose 48 100 72 100 71 25 67 89Los Angeles-Long Beach 69 32 83 48 43 100 100 82San Diego 30 47 71 67 43 100 83 66Oakland 25 45 88 68 57 50 83 65Philadelphia 35 28 85 53 14 50 100 60Seattle-Bellevue-Everett 23 33 70 64 43 25 83 53Austin-San Marcos 10 28 80 38 43 20 67 45Raleigh-Durham-Chapel Hill 6 17 100 42 14 20 83 44San Francisco 12 24 72 50 14 33 67 42Washington, D.C. 11 7 65 34 14 14 67 32Addendum:Ventura 5 33 53 81 43 100 17 42


Current Impact Measures (CIM) - Scores for Medical DevicesRanked by Composite Index


97

Current Impact – Bio-Medical

MSA1 Boston NECMA 37,6412 Los Angeles-Long Beach 21,1183 San Diego 20,2434 San Jose 18,2195 Philadelphia 17,1586 Seattle-Bellevue-Everett 13,8677 Orange County 13,7918 Washington, D.C. 11,2699 Oakland 10,90810 San Francisco 9,26511 Raleigh-Durham-Chapel Hill 7,63712 Austin-San Marcos 3,279


Bio-Medical Employment Size2002

Rank Number MSA1 San Jose 4.042 San Diego 3.323 Boston NECMA 2.394 Raleigh-Durham-Chapel Hill 2.255 Oakland 2.116 Seattle-Bellevue-Everett 2.067 Orange County 1.988 San Francisco 1.899 Philadelphia 1.4410 Los Angeles-Long Beach 1.0611 Austin-San Marcos 1.0012 Washington, D.C. 0.81


Bio-Medical Location Quotient2002

RankLQ

(US=1)

MSA1 Oakland 118.32 Washington, D.C. 117.73 San Diego 106.74 San Francisco 105.85 Seattle-Bellevue-Everett 104.36 San Jose 102.17 Los Angeles-Long Beach 102.08 Raleigh-Durham-Chapel Hill 101.89 Philadelphia 92.810 Boston NECMA 92.411 Orange County 88.512 Austin-San Marcos 80.3


Bio-Medical Relative Employment Growth1997-2002

RankIndex

(US=100)

Bio-Medical Industry AggregateEmployment - Concentration, Growth, and Size

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

70 80 90 100 110 120 130


Loc

atio

nQ

uoti

ent

(U.S

.Ave

rage

=1.

0)

Philadelphia

Wash.,D.C.

Raleigh-Durham

Austin

San Jose

San Francisco

Boston

Seattle

San Diego

Los Angeles

Orange Co. Oakzand

BIO-MEDICAL Current ImpactEmployment

LevelLQ



# of Ind.LQ>2

# of Ind.LQ<0.5

# of Ind.growing>US Composite

MSA 2002 2002 97-02 2001 2002 2002 2002 2002Boston NECMA 100 59 71 48 100 33 44 100San Diego 54 82 85 76 88 100 89 98San Jose 48 100 76 100 88 17 56 93Oakland 29 52 100 53 75 33 100 75Los Angeles-Long Beach 56 26 74 28 50 100 67 71Seattle-Bellevue-Everett 37 51 80 42 63 20 78 69Orange County 37 49 70 46 88 50 44 67Philadelphia 46 36 72 34 25 50 67 64San Francisco 25 47 83 48 25 20 89 61Raleigh-Durham-Chapel Hill 20 56 72 55 50 20 67 60Washington, D.C. 30 20 88 55 25 13 89 56Austin-San Marcos 9 25 65 35 50 14 56 40Addendum:Ventura 18 120 53 44 63 33 44 74


Current Impact Measures (CIM) - Scores for Bio-MedicalRanked by Composite Index

Appendix

98

Current Impact – Life Science

MSA1 Boston NECMA 42,8552 Philadelphia 27,6133 Los Angeles-Long Beach 23,5334 San Diego 20,9865 San Jose 18,5186 Orange County 17,7937 Seattle-Bellevue-Everett 14,0198 San Francisco 13,3899 Washington, D.C. 12,24210 Oakland 11,01511 Raleigh-Durham-Chapel Hill 9,24712 Austin-San Marcos 3,327


Life Science Employment Size2002

Rank Number MSA1 San Jose 3.252 San Diego 2.733 San Francisco 2.164 Boston NECMA 2.165 Raleigh-Durham-Chapel Hill 2.156 Orange County 2.027 Philadelphia 1.838 Oakland 1.699 Seattle-Bellevue-Everett 1.6510 Los Angeles-Long Beach 0.9311 Austin-San Marcos 0.8012 Washington, D.C. 0.70


Life Science Location Quotient2002

RankLQ

(US=1)

MSA1 Washington, D.C. 121.22 Oakland 112.23 San Francisco 109.74 San Diego 105.55 Seattle-Bellevue-Everett 101.86 Los Angeles-Long Beach 101.17 Raleigh-Durham-Chapel Hill 97.28 Boston NECMA 94.99 San Jose 91.710 Orange County 87.211 Philadelphia 82.412 Austin-San Marcos 77.4


Life Science Relative Employment Growth1997-2002

RankIndex

(US=100)

Life Science Industry AggregateEmployment - Concentration, Growth, and Size

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

70 80 90 100 110 120 130


Loc

atio

nQ

uoti

ent

(U.S

.Ave

rage

=1.

0)

Philadelphia

Wash.,D.C.

Raleigh-Durham

Austin

San Jose

San FranciscoBoston

Seattle

San Diego

Los Angeles

Orange Co.

Oakland

LIFE SCIENCE Current ImpactEmployment

LevelLQ



# of Ind.LQ>2

# of Ind.LQ<0.5

# of Ind.growing>US

CompositeIndex

MSA 2002 2002 97-02 2001 2002 2002 2002 2002Boston NECMA 100 66 72 49 100 67 56 100San Diego 49 84 83 77 88 100 100 92San Jose 43 100 72 100 88 29 56 85Philadelphia 64 56 70 35 38 100 67 79Orange County 42 62 71 48 100 100 44 74San Francisco 31 67 85 48 38 40 100 70Los Angeles-Long Beach 55 29 76 28 50 100 78 68Oakland 26 52 88 53 75 50 100 67Seattle-Bellevue-Everett 33 51 80 42 63 33 78 64Raleigh-Durham-Chapel Hill 22 66 74 57 50 40 67 62Washington, D.C. 29 21 100 55 25 22 100 57Austin-San Marcos 8 25 65 35 50 25 56 38Addendum:Ventura 16 118 53 43 63 50 56 71


Current Impact Measures (CIM) - Scores for Life ScienceRanked by Composite Index


99

About the Authors

Ross DeVol is Director of Regional Economics at the Milken Institute. He oversees the Institute’s research on the dynamics of comparative regional growth performance, and technology and its impact on regional and national economies. He is an expert on the intangible economy and how regions can prepare themselves to compete in it. He authored the ground breaking study, America’s High-Tech Economy: Growth, Development, and Risks for Metropolitan Areas, an examination of how clusters of high-technology industries across the country affect economic growth in those regions. He also created the Best Performing Cities Index, an annual ranking of U.S. metropolitan areas that shows where jobs are being created and economies are growing. Prior to joining the Institute, DeVol was senior vice president of Global Insight, Inc. (formerly Wharton Econometric Forecasting), where he supervised their Regional Economic Services group. He was the firm’s chief spokesman on international trade. He also served as the head of Global Insight’s U.S. Long-Term Macro Service and authored numerous special reports on behalf of the U.S. Macro Group. DeVol earned his master’s degree in economics at Ohio University.

Perry Wong is a Senior Research Economist in Regional Economics at the Milken Institute. He is an expert on regional economics, development and econometric forecasting and specializes in analyzing the structure, industry mix, development and public policies of a regional economy. He designs, manages and performs research on labor and workforce issues, the relationship between technology and economic development, and trade and industry, with a focus on policy development and implementation of economic policy in both leading and disadvantaged regions. Wong is actively involved in projects aimed at increasing access to technology and regional economic development in California and the American Midwest. His work extends to the international arena, where he is involved in regional economic development in southern China, Taiwan and other parts of Asia. Prior to joining the Institute, Wong was a senior economist and director of regional forecasting at Global Insight, Inc. (formerly Wharton Econometric Forecasting) where he managed regional quarterly state and metropolitan area forecasts and provided consultation. Wong earned his master’s degree in economics at Temple University in 1990 and completed all course requirements for his PhD.

Armen Bedroussian is a Research Analyst with the Milken Institute. Bedroussian has extensive graduate training in econometrics, statistical methods and other modeling techniques. Before joining the Institute he was an economics teaching assistant at U.C. Riverside where he taught intermediate micro and macro economics to undergraduates. Since coming to the Institute, Bedroussian has contributed to several projects including Butler County’s Economic Impact Assessment, The Impact of an Entertainment Industry Strike on the Los Angeles Economy, Los Angeles Mayors Task Force Study on the Assessment of Post Sept.11 Economic Conditions. He also co-authored Manufacturing Matters: California’s Performance and Prospects and The Economic Contributions of Health Care to New England. Bedroussian earned his bachelor of science in applied mathematics and a master’s in economics at the University of California, Riverside.

About the Authors

100

Rob Koepp is a Research Fellow at the Milken Institute. His research interests center on the topics of innovation, entrepreneurship and regional economic development, especially in the context of global technology businesses. His foreign geographic expertise is in the areas of East Asia and Europe, especially China, Taiwan, Japan, and the United Kingdom. He is the author of Clusters of Creativity: Enduring Lessons on Innovation and Entrepreneurship from Silicon Valley and Europe’s Silicon Fen (John Wiley, 2002) and is a report leader in a World Bank-sponsored study for China’s Ministry of Science and Technology on reform of China’s high-tech park system. In addition to his work at the Institute, he lectures on technical entrepreneurship and international entrepreneurship as an Adjunct Professor at the University of Southern California. Fluent in Chinese (Mandarin) and Japanese, Koepp served in various senior positions with Western and Japanese technology firms prior to joining the Institute in 2002. Koepp earned his BA in Asian Studies at Pomona College and his MBA with an emphasis in venture capital financing at Cambridge University.

Junghoon Ki is a Research Analyst in Regional Economics at the Milken Institute. His research interests include history of technology, human capital development, location of high-tech business, job creation strategy, and other urban planning related issues, especially in the planner’s perspective and with spatial context. He is responsible for capturing, analyzing, interpreting and visualizing regional economic data in order to create reasonable policy implications for the public. Ki is involved in the Institute’s Fresno Economic Development Project and its New England health care research. He wrote “The Role of Two Agglomeration Economies in the Production of Innovation: A Comparison between Localization Economies and Urbanization Economies,” Enterprise and Innovation Management Studies, 2001. Ki was awarded a doctoral dissertation grant from National Science Foundation and earned his PhD. at the University of Southern California.

About the Authors

101

About DeloitteDeloitte, one of the nation’s leading professional services firms, provides audit, tax, consulting, and financial advisory services through nearly 30,000 people in more than 80 U.S. cities. Known as an employer of choice for innovative human resources programs, the firm is dedicated to helping its clients and its people excel. “Deloitte” refers to the associated partnerships of Deloitte & Touche USA LLP (Deloitte & Touche LLP and Deloitte Consulting LLP) and subsidiaries. Deloitte is the U.S. member firm of Deloitte Touche Tohmatsu. For more information, please visit Deloitte’s Web site at www.deloitte.com/us.

About Milken InstituteThe Milken Institute is an independent economic think tank whose mission is to improve the lives and economic conditions of diverse populations in the U.S. and around the world by helping business and public policy leaders identify and implement innovative ideas for creating broad-based prosperity. We put research to work with the goal of revitalizing regions and finding new ways to generate capital for people with original ideas. We are nonprofit, nonpartisan and publicly supported. For more information, please visit www.milkeninstitute.org.

About Deloitte & Milken Institute

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