the future of next-gen sequencing (ngs) · pdf fileit is my pleasure to introduce cambridge...

The Future of NGS Market Study 2011 Conducted by CHI Professional Marketing Services

I think NGS is the great-est thing since yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada yada. 1

The Future of Next-Gen Sequencing (NGS) Market Research Study | July 2011

ConduCted by:

CHI ProfessIonal marketIng servICes

Market Research Group

In ConjuCtIon wIth:

Cambridge Healthtech Institute, 250 First Avenue, Suite 300, Needham, MA 02494 • www.healthtech.com • Fax: 781-972-5425

http://www.bio-itworld.com

http://www.ngsleaders.org

http://www.healthtech.com

http://www.healthtech.com


2

july 2011

Dear Colleague:It is my pleasure to introduce Cambridge Healthtech Institute’s The Future of Next-Gen

Sequencing market study. For the past 5-6 years, my colleagues at Bio•IT World and CHI have been covering

the rapidly evolving field of next-gen sequencing (NGS), through a combination of print and digital media, web symposia and several marquee conferences. Like you, we have observed that the field is moving into a critical new phase: new third-generation sequencing technologies are reaching the market, while genome sequencing studies are showing signs of providing both diagnostic and therapeutic benefits in clinical settings. Seldom does a week pass without news of another genome sequencing feat, but the challenges of analyzing and interpreting so much rich data are, if anything, getting bigger.

For reasons such as these, we decided that it was an ideal time to poll a broad constituency of NGS users to get their opinions on a range of critical issues facing the NGS community. Over the past few months, my colleagues at CHI have designed and conducted two exhaustive surveys of more than 1,400 professionals examining the key challenges in technology, data analysis and applications surrounding the field of NGS.

I am sure you will find much to ponder in this bumper study. Thanks to the contributions of so many researchers, this report offers a picture of some of the obstacles facing NGS implementation, from both a technological as well as managerial perspective. Further discussion around these issues is being hosted by our colleagues at NGS Leaders (www.ngsleaders.org).

We are very grateful to our sponsors — DataDirectNetworks, Illumina, Ingenuity and Perkin Elmer — for underwriting the production of this survey and everyone who took the time to participate. We hope you find the results interesting and informative, and welcome your feedback on this and other topics.

Yours faithfully,

Kevin davies Phd Editor, Bio•IT WorldAuthor, The $1,000 Genome


3


Study Sponsors

Cambridge Healthtech Institute participating business units involved in producing this study include:

Inside the Study

IntroduCtIon:Purpose of the Study ......................................................................................... 4Methodology ..................................................................................................... 4Study Sample .................................................................................................... 5Post Study Discussion Area .............................................................................. 5

ExECutIvE Summary: NGS Today ......................................................................................................... 6

SponSorS:Data Direct Networks ........................................................................................ 8Coping with NGS Data FloodData Direct Networks – Storage Scalability Experts

Illumina .............................................................................................................10Illumina’s Great iDEANGS Success Requires More Than Just Sequencing

Ingenuity Systems ............................................................................................11Deciphering the NGS Data Deluge: It’s all about Biological Interpretation

Perkinelmer ......................................................................................................12PerkinElmer’s NGS Offering: Experience, Expertise, and Commitment

Study SECtIonSurvey 1 Results ..............................................................................................14Survey 2 results .............................................................................................. 32Survey 1 Questions ......................................................................................... 54Survey 2 Questions ......................................................................................... 56

A Cambridge Healthtech Institute publication © 2011 by Cambridge Healthtech Institute (CHI). This report cannot be duplicated without prior written permission from CHI. Every effort is made to ensure the accuracy of the information presented. Much of this informa-tion comes from survey respondents. We do not assume any liability for the accuracy or completeness of this information, or for the opinions presented.

CHI will be conducting a series of sponsored market studies across life science and healthcare throughout 2011/12. If you are interested in learning more about sponsorship opportunities please contact:alan El Faye | 213-300-3886 | [email protected]


http://www.insightpharmareports.com

http://www.datadirectnet.com/

http://www.ingenuity.com

http://www.perkinelmer.com/

http://www.bio-itworld.com

http://www.illumina.com

mailto:aelfaye%40healthtech.com?subject=


4

ReSPondent CoMMent:

NGS will likely enter the clinics soon, and we need robust software solutions that are easy to use!”

This study was conducted through two separate surveys in paper form, and online. SurvEy 1 — Was first conducted in hard-copy format at CHI’s Xgen conference in San Diego, Calif. the week of March 14, 2011 among conference attendees. The same survey was then administered online the following week to current and prospective NGS users globally. SurvEy 2 — Was conducted online between May 24 and June 3, 2011. This survey asked different questions than survey 1. Survey 1 was intended to provide information around NGS platform usage, applications, and technology infrastructure focused on preferences, concerns, costs, technology and services needs and wants. Findings from that survey were intended to be used in help-ing form the basis of questions for survey 2. Additionally, small user groups were con-ducted during the Xgen conference to aid in the study design of survey 2.

Both surveys can be found at the end of this study.

Methodology

Purpose of the Study

This study was conducted to:• Gain a greater understanding of possible obstacles to the future advancement of next-

generation sequencing (NGS).• Uncover areas of need for advancing the use of next-generation sequencing technolo-

gies, services and processes in pharmaceutical companies, biotechs, and research based academic institutions and research based hospitals globally.

• Create a platform for ongoing, post-study online discussion around the above within the NGS user community.

To accomplish this the study takes an in-depth look at key NGS areas among current and potential NGS users, including:• NGS current and planned usage• Challenges• Timing• Technology implementation• Technology concerns• Use of outsourced services• NGS cloud adoption• User training• Costs• Events impacting NGS adoption and growth


5

A discussion area to comment on survey findings has been set up on CHI’s NGS Leaders website. It will remain active through December 2011. Commentary and input is encour-aged from professionals currently using, or planning to use NGS in their work. Providers of NGS technologies and services are also invited to comment. Cambridge Healthtech Institute will also organize upcoming group discussions around NGS topics on this site with specially invited discussion leaders. To join the discussion, CLICK HErE. www.ngsleaders.org/discussions.aspx?tid=883&groupid=posts&t=883

Respondents taking the paper-based survey were made aware of it during the Xgen conference through signage and announcements. Surveys were filled out and submitted by the end of the conference.

Members taking the online version of surveys 1 and 2 were sent an email from Cam-bridge Healthtech Institute inviting them to participate in a survey by clicking on a URL link to the questionnaire. The list of e-mail addresses for the study was selected from the Cambridge Healthtech Institute database choosing those records that were coded as NGS involved. They came from a combination of mid to large pharmaceutical companies, biotechs, academic cen-ters, research hospitals and government entities. Professional titles included scientists, researchers, analysts, technology professionals, group research heads, line-of-business managers, executive management, and more. In order to increase participation in the survey, respondents were offered entry into draw-ings for iPADS. response: 541 respondents completed Survey 1 893 respondents completed survey 2 A total of 1,434 respondents completed both surveys accuracy: The surveys each carry a margin-of-error of plus or minus 5%

Study Sample

Post Study Discussion AreaReSPondent CoMMent:

I think whole genome sequencing will eventually be done for every person born!”

www.ngsleaders.org/Discussions.aspx?tid=883&groupid=posts&t=883


6

Many researchers are passionate about the technology’s potential, but are still at odds over the best way to make use of it.”

BY ALLISON PROFFITTManaging Editor, Bio•IT WorldNext generation sequencing is without a doubt one of the areas of life sciences research with the most buzz. Sequencing costs are falling and vendors everywhere are stepping up to address the data management and analysis needs associated with this new data source. CHI Professional Marketing Services and Bio•IT World sought to separate the hype from actual practice and discover what researchers really want and need from next-generation sequencing, revealing some common complaints and new market opportunities.

Moving sequencing into the clinic and applying it to patient care comes up again and again in both user and potential user comments, and several survey questions were asked specifically in light of using genomic data in the clinic. Many roadblocks emerged: HIPPA and patient privacy, cost, FDA approval of genomic diagnostic tests, and action-able and accessible data for physicians were all listed as concerns. The second survey separated responses between current users of next-generation technologies and those who are still in the discovery and research stage, and both groups identified data man-agement as the biggest challenge to moving sequencing to the clinic, though current users also identified analytics as a key hindrance.

Security, an issue often raised in discussions about both genomics and the cloud, garnered surprisingly mixed views. Both users and potential users listed security least frequently as a challenge to moving sequencing to the clinic, yet both groups listed secu-rity most often when listing hurdles to cloud computing and storage. Many respondents dismissed the cloud completely as a potential aid to managing genomic data because of patient privacy concerns or company firewall requirements.

As with any rapidly evolving field, training is a concern for NGS users. Roughly two thirds of researchers currently using NGS feel adequately trained for experimental design and using the actual sequencers, but slightly more than half of them feel inadequately trained to use analysis software. The margin narrows for bioinformaticians analyzing NGS data and for those supporting core facilities. Only half of those supporting a core facility feel adequately trained in experiment design, though about two-thirds feel well-trained to run the sequencers themselves. Understandably, those not yet using next-generation se-quencing feel generally under-trained, though the highest proportion is concerned about analysis software.

Visualization consistently emerged as an area ripe for continued growth and develop-ment. No respondents from any group believed that current visualization tools are very adequate, though most researchers and bioinformaticians believed that tools available now are reasonably adequate. One third of potential users felt that available data visu-alization tools are not at all adequate for NGS research and analysis needs, which may reflect a linkage to the same respondents’ concern about training. Write-in responses asked not just for better visualization tools, but easier user interfaces. As the sequencing itself becomes more accessible, user-friendly visualization tools for analysis could have a huge impact on researchers that have data and desire, but no bioinformatics training.

Workflow WoesUsers don’t seem terribly overwhelmed by any particular step in the NGS workflow. Few

Executive Summary: NGS Today


7

steps were marked by any respondents as “extremely difficult.” Moving data along the workflow and data analysis and construction received the highest consensus markings, both being labeled somewhat difficult. About 70% of researchers currently using NGS rated the sequencing itself as either not difficult at all, or only slightly difficult.

Almost half of those supporting a core research facility found storage somewhat dif-ficult, but that seemed to be less of a concern for researchers and bioinformaticians, likely reflecting the amount of data each group needs to store. Data volume was an issue raised several times by respondents to the first survey, but seemed to reflect pain points in transfer, analysis, and management rather than in storage alone. Only eight responding users listed storage as extremely difficult, suggesting that their basic needs are met, but that there is room for improved solutions.

threats to the IndustryResearchers and bioinformaticians agreed, in general, which events were most likely to negatively impact the future of next-generation sequencing technologies. Both groups listed lack of qualified analysts as the biggest concern, with NIH budget cuts coming in second. Core facilities were more concerned about NIH budget cuts than any other event. The gene patent landscape was of high concern to all respondents.

Potential users were most highly concerned about lack of industry standards, asking for government or regulatory changes including updated patent laws (again reflecting gene patent concerns) and clear FDA guidance to approve genomics in the clinic. How-ever both users and potential users felt strongly that the best way to develop industry standards for data management and collection is user-driven directives as opposed to government or vendor intervention.

At the bottom of the list, unplanned or overrun costs and migration of sequencing to big data centers both garnered only 13 votes each from current users and even less from potential users.

Wish ListRespondents also identified several industry opportunities. As can be expected, many asked for cheaper and faster sequencing. But some respondents listed more specific requests as well, including PCR-free sequencing or other solutions to speed and simplify sample preparation; analysis tools that can combine types of NGS data (DNA, mRNA, methylation patterns, etc.); and a shared database of sequencing artifacts.

While many of the survey responses reflected a consensus among users and potential users, the survey write-in responses revealed that next generation sequencing is still a field with significant variability in opinion. Many researchers are passionate about the technology’s potential, but are still at odds over the best way to make use of it.

One respondent called all users to adopt and love cloud storage and computing, while another called for a paradigm shift in data storage and management and an infrastructure solution. A handful of users expressed concern that sequencing could shift to big data centers, while one respondent proposed that very solution to commoditize sequencing.

Perhaps most surprisingly in light of sequencing’s technical advances, is how nascent the field is in the minds of researchers. Many respondents are still looking for buy-in from their executive levels, from physicians, from the public, and from regulatory agencies, and hope for strong clinical NGS success stories to illustrate the technology.

Roughly two thirds of researchers currently using NGS feel adequately trained for experimental design and using the actual sequencers.”

8


Eagerness among life science researchers to make the most of next generation DNA sequencing often stirs anxiety among IT staffers charged with supporting the flood of data pouring from NGS machines, and with good reason. A single NGS instrument can produce 200 Gigabases in a week’s run, larger NGS centers generate multiple Tera-bases in a day, and this is just the beginning

of the NGS revolution. The rate and volume of data spewing from NGS machines will only grow.

Data Direct Networks (DDN), the largest privately held storage company and the fourth largest overall by revenue, under-stands the NGS data management chal-lenge. Founded in 1998 to solve high perfor-mance storage issues, just two years later in 2000 DDN became the first company whose storage solution could ingest data streaming directly from satellites. Today some of the largest and most demanding applications – the French nuclear research agency — CEA (world’s fastest file system at more than 300 GB/s ) and Shutterfly (roughly six billion files, more than 36 Petabytes) for example — rely upon DDN storage.

Within life sciences NIH, Welcome Trust Sanger Institute, Translational Genom-ics Institute (TGEN), and Merck among many others are DDN customers. “Not unlike many of our customers, we tend to be a focused com-

pany,” says Larry Jones, Sr. Director, HPC and Life Science Marketing. “At our core we are engineers selling to other engineers and scientists. The need for high-performance storage has grown very quickly in life sci-ences and one of the strengths we bring is that we have encountered and already solved many of the data storage problems now cropping up in life sciences.”

“At a very high level we have a complete storage portfolio including block, file, and cloud solutions, depending on what the workflow requires,” says Jones.

DDN offers three core storage architec-tures:• Storage Fusion Architecture (SFA). Us-

ing highly parallelized storage processing technology, SFA delivers up to 1 million IOPS and 10GBs throughput from a single storage system. Combined with enter-prise-level data protection, it is often used for highly scalable storage infrastructure projects.

• Silicon Storage Architecture (S2A). Often used in verticals requiring high bandwidth (up to 6GB/s of read/write) performance, S2A also features auto-healing and drive rebuilds providing real-time protection for mission-critical data. S2A is the only stor-age architecture able to provide quality of service (QoS) metrics says Jones.

• Web Object Scaler (WOS). Designed to cloud storage, WOS delivers a single global namespace for billions of files dis-persed among multiple sites, robust data protection, and powerful object serving performance to help reduce the need for content delivery networks. WOS is a solid collaboration tool: You could have multiple, geographically dispersed labs running in-dividual file systems but are able to easily share data.Every solution is customized. “We under-

stand the customer’s environment, exactly what the workload is, what problems they are trying to solve, what’s their budget and performance requirements and then work to define a solution optimized for just that particular customer,” Jones says.

Jones emphasizes that life science’s emerging storage problems look a lot like many that DDN has already dealt with. Consequently, NGS users are getting the benefit of DDN’s extensive experience. For example, as Serial ATA (SATA) disk densi-ties increase so do the chances for silent data corruption; a disk can send data to the application and not know that the data is incorrect. To cope with potential problem, DDN’s SFA architecture includes a feature called SATAssure, which calculates the parity and corrects it in real time with no loss in performance.

Supporting multiple file systems is another

Coping with NGS Data FloodData Direct Networks — Storage Scalability Experts

ddn headquarters in Chatsworth, CA.

STUDY

S

P O N SOR


http://www.datadirectnet.com/index.php?id=226





9

distinct DDN advantage he says, “You’re not locked into a single file systems for differ-ent parts of your workflow. That’s important because some types of data access may require very fast parallel operations, for example post processing of sequencing data where you are taking in data files, editing them and writing them back to the file store. In those environments you want the flexibil-ity of multiple files systems, some optimized for parallel operations, some for basic ingest and high-speed data transfer.”

Among life science clients GRIDscaler and NAS Scaler are popular. NIH, for example, runs GRIDScaler, an industrial grade file system that integrates file services, data management and S2A Extreme Storage to

optimize performance, data integrity and availability, and simplify the environment. GRIDScaler enables the S2A Extreme Stor-age to scale bandwidth to 200GB/s and always perform at full speed.

Research organizations that require modu-lar scalable storage systems using NAS protocols and basic NFS are well suited by NAS Scaler, says Jones.

A recent DDN offering that fits well in life sciences, he says, is the SFA10000e inte-grated storage server. The 10KE appliance consolidates failover protected file systems including GridScaler and ExaScaler with highly available, shared storage. This architecture eliminates the cost, power, cooling, and rack space of physical servers and failover hard-ware while reducing latencies, improving availability and simplifying management for capacity rich and I/O intensive workloads.

“Basically, it’s an embedded virtualized environment and that creates a very close connection between the file system and the data store. This simplifies and accelerates the storage system while lowering the Total Cost of Ownership by eliminating storage servers and management tasks,” he says.

Predictably, DDN supports all of the vari-ous high speed interfaces – Fibre channel, InfiniBand, and 10Gigabit Ethernet. It also has a unique energy conserving technology called Dynamic MAID (massive array of idle disks) “so you can archive data on disk as opposed to tape making it easier and faster to access. But while it’s in the disk-based archive you’re not spending the power to maintain it.”

“There are two ends of the spectrum we really address,” says Jones. “The first is you’ve got an explosion of file based data coming from the laboratory instruments and that means you need storage that is able to keep up with the data deluge. We do that. Second, you need scalability to be built into the system architecture; it’s very impor-tant to people in this market. We do that very well. Because we deliver storage for the largest systems in the world, we have solved problems that other competitors are just beginning to encounter. We’re deploy-ing storage systems in Life Science that are proven in the world’s most demanding application environments.”

NAS Scaler: Built to Accelerate NGS Research

http://www.datadirectnet.com/gridscaler

http://www.datadirectnet.com/nasscaler

http://www.datadirectnet.com

10


Driving the tremendous impact next genera-tion sequencing (NGS) can have on biomedi-cal research and medicine isn’t just a matter of producing better sequencing instruments — although that’s fundamental. It’s also necessary to foster development of the en-tire NGS ecosystem, expand access to NGS technology, and offer proof points of NGS technology at work. Founded in 1998, NGS

technology pioneer Illumina understands these impact-building requirements well.

Introduction of the HiSeq last year reset the boundaries of sequencing technology to the highest throughput

and data quality NGS has produced so far. This year in Q4 2011 Illumina will begin vol-ume shipping of its new MiSeq instrument intended to put the power of NGS within easier reach of small labs. “It uses the same chemistry as HiSeq with all of the improve-ments that have been made and puts it into a box that is a little bigger than a six pack of coke,” says Scott Kahn, Illumina CIO. Both instruments reflect Illumina’s mission to push NGS boundaries, which is well docu-mented with an online library of more than 1700 peer-reviewed papers in which Illumina technology was critical to the research undertaken.

“We are a company that embraces scientific rigor,” says Kahn. “High data qual-ity, comprehensiveness of coverage, and diversity of applications are things we feel continue to distinguish us from competi-tors.” In keeping with that strategy Illumina held its first iDEA Challenge (Illumina’s Data Excellence Award) this year, a competi-tion established to drive innovation in data visualization and analysis. Indeed, few NGS challenges are as stymying as data visualiza-tion and analysis — points made loudly by respondents to Bio•IT World ’s 2011 “The Future of NGS” Market Study.

iDEA tackles this problem head on and leverages the wisdom of the research com-munity. Researchers were given a dataset of five different types of sequencing data types and asked to produce innovative data analysis and visualization ideas. Twelve final-ists presented their ideas to an expert panel of judges who selected the winning entries.

The culmination of the iDEA Challenge was a conference held in San Diego, CA.

Six institutions took awards, including Overall Winner, Most Creative Visualization, and Most Creative Algorithm for Academic and Commercial categories. The two top winners were:• Enlis Genomics was Overall Winner in the

Commercial category. Its entry represent-ed a new generation of interactive genom-ic discovery that would enable genomic investigation for a broader audience.

• Pennsylvania State University was the Overall Winner for the Academic category. Pen’s entry of inGAP software includes their structural variation analysis compo-nent, inGAP-sv, which identifies and visual-izes structural variation from paired end mapping data.Illumina would like to congratulate the

winners and all iDEA participants. Their efforts and others like theirs are critical in helping NGS fulfill its promise.

Illumina’s Great iDEANGS Success Requires More Than Just Sequencing

Scott KahnChief Information Officer

Six Distinguished Winners

overall WinnerThis award goes to the entry describing software that, as proposed, would most substantially improve the scientific utility of Illumina data. The utility of integrated data and accessibility to all levels of users are the key criteria. Pennsylvania State University Enlis Genomics acadeMIc coMMeRcIal

most Creative algorithmThis award goes to an algorithm, data format or software (as described in an entry) that shows promise to substantially improve the scientific utility of Illumina data. University of Tubingen Partek Incorporated acadeMIc coMMeRcIal

most Creative visualizationThis award goes to a visualization or software (as described in an entry) that shows the most promise to substantially improve the scientific utility of Illumina data. VIB Genomatix Software acadeMIc coMMeRcIal

iDEA Challenge Winners

STUDY

S

P O N SOR

http://www.illumina.com


11

Deciphering the NGS Data Deluge: It’s all about Biological Interpretation

Speaking at MIT’s Conquering Cancer Symposium1 this spring, Eric Lander noted the Broad Institute sequenced 70 giga-bases (GB) in 2006, 1,800 GB the next year, 125,000 GB in 2010, and showed no signs of slowing this year. But the point, emphasized Broad’s director, is not just to do the se-quencing, it’s all about the biological inter-pretation. “The real goal is to map all this back onto pathways,” he said.

Ingenuity Systems agrees entirely with this perspective. “We call it the 5 million to 50 problem,” says Ingenuity Systems’ Chief Science Officer, Doug Bassett. “We want to help researchers in a dynamic and agile way get from large numbers of variants identi-fied by NGS re-sequencing studies down to the 50 or ten that really matter--those most compelling for follow up.”

Founded in 1998, Ingenuity was a pioneer in developing tools to decipher large data sets and put them into biological context. Its flagship product, IPA, is powerful analy-sis software that helps researchers model, analyze, and understand the complex bio-logical and chemical systems at the core of life science research. IPA’s early strength in microarray analytics has steadily expanded to encompass most omics disciplines.

manuaL CuratIon CountSThe foundation on which IPA works is Inge-nuity Knowledge Base, a manually curated (Ph.D. level curators) and highly structured database of millions of data points and relationships extracted from peer-reviewed literature. Here are just a few of Ingenuity Knowledge Base’s components:• Integrated biological and chemical knowl-

edge including relationships between proteins, genes, metabolites, protein com-plexes, cells, cellular components, tissues, organs, small molecules, cellular pheno-types, pathways, and disease processes

• Comprehensive, species-specific knowl-edge about gene function and regulation, tissue and cell line expression patterns, clinical biomarkers, subcellular location, mutations, and disease associations

• Chemical and drug information for clinical candidates and FDA-approved drugs

• Systematic capture of signaling and meta-bolic pathway relationships

• Experimentally demonstrated and predict-ed microRNA-mRNA relationships, includ-ing biological roles and potential impactsResearchers can upload, analyze, and

visualize their data sets. IPA helps them ex-amine data and in the context of published research. It overlays the context of what’s available in the literature, information on molecular relationships, pathways, disease and other related knowledge from the Ingenuity Knowledge Base.

“This allows researchers to quickly float to the surface what’s most important,” says Bassett. “We feel IPA isaccelerating the pace of biological discovery in the NGS era. IPA significantly decreases the time it takes to get to from generation of data to biologi-cal insight.”

rampInG For nGSRecently Ingenuity ramped up efforts to cap-ture and curate NGS related data and knowl-edge. Moreover, it maintains an online ‘best practices’ library of more than 4000 peer reviewed publications in which researchers have applied Ingenuity technology in helping them get to a novel publishable insight.

Most customers use IPA as a software-as-a-service (SaaS) and Ingenuity also offers services, such as customizing the software or actually conducting data analysis for clients. Although Ingenuity is focused on biological interpretation, it has taken steps to ensure IPA is seamlessly integrated into the workflows and has partnerships with upstream analysis packages that do primary and secondary analysis of NGS data.

For 13 years, Ingenuity has been a driving force in providing analytics for dealing with the large datasets spawned the ongoing omics revolution and helping scientists ac-celerate their time-to-insight. Next generation sequencing is the next omics frontier. For more information, visit www.ingenuity.com.

1 Conquering Cancer through the Convergence of Science and Engineering, http://mit150.mit.edu/symposia/conquering-cancer

Doug Bassett, Ph.DChief Scientific Officer and Chief Technology Officer

STUDYSP

O N S O R




12

PerkinElmer’s NGS Offering:Experience, Expertise, and Commitment

Driven by advancing technology and rising demand, the next generation DNA sequenc-ing (NGS) services market is a bit like a bois-terous bazaar in which vendors of varying capabilities and buyers with varying needs mingle and haggle to find best solutions for

their projects. It pays to be a careful buyer, says dick begley, president, Emerging Technologies, PerkinElmer, Inc. (PKI).

PKI, a key player in protein-based drug discovery and diagnostics, entered the NGS services arena last January (PKI DNA Sequencing & Analysis), and Begley — former

CEO of NGS pioneer 454 — is convinced few other commercial NGS services suppli-ers can rival PKI’s quality, speed, or pricing. PKI’s innovative cloud computing environ-ment, powerful informatics tools, and high interactivity with customers are important competitive differentiators, he says.

“We have a very different services model. We start the project at the customer site with an interactive planning and quality control procedure. We have automated the facility (Branford, CT) so most manual steps in exome extraction and library preparation are done on PKI automated systems. The result is very high throughput, quality and reproducibility,” he says.

Most customers nod agreeably when first told they will receive frequent progress reports and quickly come to appreciate the promptness of PKI’s ongoing follow-up dur-ing a project, says Begley. “Geospiza’s LIMS software monitors and runs basically every part of the process. At each step we do a quality check, and the output of that is fed back to the customer,” Begley says.

PKI began by focusing on “exome re-sequencing of humans and mice. That rapidly led us to targeted re-sequencing where you design a particular extraction kit

for a selected genomic region. It’s also lead-ing us to do microbes.”

PKI deliberately chose not to go into NGS hardware business — there are plenty of companies doing that — and currently uses Illumina HiSeq machines. “We settled on a services and knowledge-base model that is highly interactive, and will be hardware ag-nostic.” PKI is a certified Illumina and Agilent (for SureSelect) provider. Begley says PKI will expand the equipment it uses over time when needed for capacity or other applica-tions. He emphasizes the PKI team is very experienced. Recently PKI acquired Geospi-za whose LIMS and analytics software it had been using, as are many other sequencing facilities.

Cloud computing plays a major role. All sequencing activities are captured and may be analyzed using a robust private cloud that PKI built. Customers can also customize their work environment, if desired, he says.

“PKI offers 4-to-6 week turnaround. We know plenty of people who have been waiting for months to get either sequencing done or the data analyzed,” he says. “You have to really be good to be competitive in this space. We are really good.”

dick begleyPresident, emerging Technologies

STUDY

S

P O N SOR

http://www.perkinelmer.com/MY/Pages/000/DNA-Analysis/datasequencing/cat1/NAV_05_SVC_Services_004/cat2/NAV_SVC_DNA%20Sequencing_and_Analysis_013

http://www.perkinelmer.com/MY/Pages/000/DNA-Analysis/datasequencing/cat1/NAV_05_SVC_Services_004/cat2/NAV_SVC_DNA%20Sequencing_and_Analysis_013

http://www.illumina.com/systems/hiseq_2000.ilmn

http://www.genomics.agilent.com/CollectionOverview.aspx?PageType=Application&SubPageType=ApplicationOverview&PageID=2094

http://www.geospiza.com/

http://www.geospiza.com/

http://www.perkinelmer.com/

The Future of NGS Market Study 2011

Study Section

13


Survey 1

14


15

ReSPondent CoMMent:

diagnostics is the key to growth, but it’s unclear how quickly that will happen.”

Which platforms do you own?

1. Do you own, or support a major NGS platform. If so which of the following:

Total respondents: 541


note: Pie chart exceeds 100% due to some respondents owning multiple platforms.


ReSPondent CoMMent:

I think there needs to be a focus on indi-vidual researcher’s ability to assemble and annotate genome data. Then to use analysis software to rap-idly identify associations of markers within their genome related to popula-tion phenotypes. We are using pathway analysis of model organisms to predict phenotypic as-sociations in populations in developing countries. There is a great need for database and software development around these areas to encourage long-term NGS utilization.”

Selected write-in responses:• To find regulatory binding sites • Diagnostics • To identify variants in large sets of clini-

cal samples. • Sequencing small genomes • To identify and characterize mutation in

pathogens • De novo genome assembly• RNAseq & SNP discovery • Epigenomic studies (histone modifica-

tion) • Cancer profiling • Service provider, DHS performer, envi-

ronmental analysis, pathogen detector, cancer biology Identification of new mutations

• NIH funded research projects • Drug sensitivity • B-Cell heavy and light chains for anti-

body screens • Core Service — Basic Research • Brain tumor to look at bacterial diversity • Develop software to support data analy-

sis• Medical and population genetics • New platform validation clinical market• Because it’s there. Like Everest. To dis-

cover

• For structural elucidation • Seeking CNVs that may influence the

genetic and epigenetic factors involved in birth defects

• Clinical diagnostics • Genome Wide Association Studies • We have determined the nuclease map

of plasmodium falciparum (epigentic studies) and also its transcriptome (RNA -Seq) to study changes in expression

• Plant Genomics • Core lab, offering all sorts of applica-

tions, from bacteria to humans, includ-ing de novo sequencing, re-sequencing, targeted sequencing, metagenomics, RNA-seq, microRNA, etc.

• To supply data to collaborators/ clients • I am a part of the Center for Genetics

Research & the focus is on the relation-ship between genetic variation and a huge array of diseases/ outcomes. This is the direction human genetics is headed.

• Life is in the code • To reduce the cost • To study human disease with the most

cutting edge technology


2. Why do you sequence?

16


17

ReSPondent CoMMent:

Molecular epidemi-ology will use this more if the price keeps dropping.”

Selected write-in responses:• De novo sequencing. • Identifying SNP linked to avirulence in

fungal pathogen genome re-sequencing • Our primary application would be post-

marketing safety databases i.e. argus, oracles aers etc.

• Biomedical research, cancer diagnostics • Targeted resequencing. • Mutation detection • small genomes • RNA-seq • Target ID Polymorphism studies • ChIP-seq • RNA-seq cancer profiling • Target enrichment • DNA repair • LIMS • Disease biomarkers • Human/animal microbiome • Structural variation • Amplicon sequencing • Exome resequencing • I examine ethical issues related to large

data sets • Mutation scanning, whole exome se-

quencing • Population genetics and evolutionary

studies • Agricultural breeding • Epignetics • IGV - great for viewing data with analy-

sis • Clinical exome sequencing• Population genetics, GxGxE interac-

tion, coevolution of legume and sym-biotic bacteria, need to map and iden-tify genes possibley under selection (genome — genome interaction, and genome — environment interaction) and follow them.

• Cancer research • Sequencing and comparison of clinical

human samples. Usually about 10 sam-ples per group. Less than 50 samples total.

• Application of NGS technology: Detec-tion of disease causing variants. Applica-tion (software): In house programs.


3. What is your primary application?


18


2. Do you feel computing infrastructure will keep pace with the growth of platform technologies like sequencers from Illumina, Life Technologies, Roche/454, Complete Genomics, Helicos, Oxford Nanopore, Pacific Biosciences, etc?


1. Is currently available computing infrastructure (servers/storage/etc.) adequate enough to support today’s needs for NGS?

Study Area: NGS COMPUTING INFRASTRUCTUREReSPondent CoMMent:

We need to do NGS on portable devices, with capacity enough to sequence complete bacte-rial genomes, viruses, metagenomes, and human genomes.”


194. Is cloud-based NGS growing, or losing appeal within your organization as a traditional infrastructure replacement?



3. Do you generally account for any unforeseen infrastructure costs in your NGS system spending, like data handling and storage, or do these costs climb faster than anticipated?

ReSPondent CoMMent:

It is sad to see the movement of sequencing from the individual lab to the big genome centers. a few will get all the money and glory. The rest of us will starve.”


ReSPondent CoMMent:

There will be a period when everybody will be spending money on NGS that will lead to a lot of data that will be impossible to analyze. This will lead to a decrease in NGS activity that will be rekindled once compre-hensive data analysis, de-livery and storage systems arrive that are approved by regulatory authorities.”

Selected write-in responses:• Security • Storage and storage costs• Data storage, retention policies • Long term storage, data integration,

best practices, secondary analysis• Accuracy, speed and cost. • Data management & visualization• Administration • Data transfer speed • Data alignment • Data sharing• Storage and distribution and memory

constraints• Standardization of data between lab and

studies • Network bandwidth, storage and ease

of use software pipelines • Bioinformatics, Bioinformatics, Bioinfor-

matics, Standardized formats to allow easier bioinformatics analysis

• Lack of trained people to do the analy-sis, problems in communication time between servers (just uploading the data to do an analysis is getting harder and harder, not just the amount of pro-

cessing power or memory) • Miniaturization. We need to do NGS

smaller, cheaper and easy to use and in-terpreting enough to have them in every small size laboratory.

• Better visualization tools are needed • Software error rates• High cost • Rapid turnover/upgrade of technology

is a challenge in a grant-funded envi-ronment. Data management capability cannot keep pace with data production capabilities. Instrument providers/manu-facturers ability to maintain adequate QC on products in a rapidly advancing technology.

• NGS software is usually poorly docu-mented and buggy. LIMS always lags behind other considerations.

• Robust LIMS systems • Not enough tools to organize, sparse,

and manage the reads that are pro-duced.


5. What areas of concern, or need can you identify in NGS infrastructure?

20


21

ReSPondent CoMMent:

The industry cannot expand to $100B/ year unless the data analysis bottleneck is addressed. We may soon be able to sequence the human genome in a day for less than $1000 but what use will this be if it still takes a man/year to analyze and interpret the results.”

Category Composite Satisfaction rating

# of Category respondents

Re-sequencing 3.62 306

High-throughput sequencing 3.57 322

Comparative analysis 3.12 308

Genome assembly 3.08 312

Pipeline 3.06 312

Follow-up analysis 3.04 300

Visualization 2.98 314

Pre-analysis 2.98 300

Sequence data management 2.97 310

LIMS 2.89 296

Single molecule sequencing systems 2.75 291

Single molecule analysis 2.73 286

1. In the area of NGS software please rate on a scale of 1-5, with 5 highest, your satisfaction with current products available within the following categories

Study Area: NGS SOFTWARE


22

ReSPondent CoMMent:

(I’m) curious as to how this patent will im-pact the marketplace: US Patent 7089498 (Method for preparing and using personal and genetic profiles)”

Selected write-in responses:• More visualization tools would be nice.• Better, more intelligent genome assem-

bly software • Better data mining and manipulation

software, old methods are not effective for NGS sequences and uses

• Integrated phylogenetic analysis • Pipeline and visualization• Visualization and real-time manipulation

of the underlying data instead of a static representation.

• The more that the analysis tools can eventually be put in the hands of end-users, many of them not having a com-putational background, the better.

• The software that has been developed by the major NGS companies has been difficult to implement in a productive work flow.

• Accuracy and consistency• Speed• Speed in handling large data sets n/a• Data analysis possible by bench scien-

tists• Faster genome assembly — will always

be a need for this. LIMS and data management are not easily translatable across institutions.

• Pipelines and assembly improvements• Standardization and interoperability be-

tween software packages and computer

operating systems• Web-based technologies that allow ease

of use of data pipelines and analyses.• Some problems are hard — assembly

and annotation — with short reads; these need more work. Visualization and comparative analysis is most often done by the end PI who needs to either be taught a difficult system or needs an intuitive system.

• Need a big shift in visualization tools, much more efficient pipelines, more analysis tools that don’t get bogged down with visulaizations, sequence data management is poor.

• Sequence data storage• Clinical data management• Standardization of software of better

algorithms • Better assembly/ sequence analysis

tools for non-bioinformatics & dedicated simple pipelines to downstream applica-tions

• Alignment software like bowtie (used for illumina) does not work well for RNA-seq data from genomes with high level of repeats

• Make data accessible to biologists with-out requiring IT folks or data analysis in between


2. In any of the prior software categories, or any not listed, what key improvements do you feel need to be made for NGS to advance to its next generation of improvement and productivity?


234. Does your organization prefer commercial or open-source NGS software solutions?



3. Do you feel current NGS systems are available that are centralized enough to efficiently support the general, and growing demands of NGS?

ReSPondent CoMMent:

NGS is heading in the right direction and is moving at an amazing pace.”


24Study Area: NGS SERvICES

5. If you were highly confident of a commercial software offering’s capability to support your needs would you invest in it, even if a less proven open source alternative were available?

1. How much of your overall NGS work is conducted within your organization vs. using an outside service?



ReSPondent CoMMent:

We need more com-puter scientists to join us and improve the technol-ogy and the computing analysis.”


25

ReSPondent CoMMent:

NGS will have a great impact on future molecular diagnostics, if data handling and analysis as well as sample prepa-ration techniques will be improved.

Selected write-in responses:• None — HIPPA concerns• NGS data analysis pipeline and web

service interface Geospiza, DNA Nexus. • Ingenuity • Storage • Some Amazon• AWS; mimecast • Amazon EC2 and Open Cloud Testbed. • Amazon Translation Med • GenomeQuest: DNA services • Proteomics service • Mygenomatix because of data security

and speed of turnaround • Cloud-based data management is all

internal, currently.

• Genious cbio mg-rast internal cloud (sun grid engine)

• Use of Amazon and Google services for compute and visualization.

• Exploring cloud solutions. trust re:access to the data is an issue.

• My org stated using a LIMS as a Soft-ware solution, called htlims.net and it’s quite good.

• Omixon Variant Toolkit • Storage (S3) & computer (EC2) • None used. Privacy concerns trump

everything. • Private cloud


2. What cloud-based services has your organization added over the past 12 months?

3. Do you find large data/file transfer a problem that can hurt the growth of NGS?



26

ReSPondent CoMMent:

The future for single molecule sequencing is much smaller than antici-pated. It is something that will be good for hypoth-esis development, but due to the error rate you need a large number of repeti-tive reads for accuracy.”

Selected write-in responses:• Galaxy • Gene discovery using RNA-Seq over

genomic assembly • Visualization• Fast data transfer and easy to use inter-

faces • Unlimited storage and forever • Biological interpretation & variant analysis • Powerful visualization and data analysis

tools that can compete with open-source or at least add value to open source efforts

• Easier setup of parallelized workflows • Comparative genomics • Amazon has made getting on the cloud

quite easy, but it’s still quite a program-ming challenge to run custom software on their cloud, especially if you want to take advantage of the spot services. Real understanding of queuing and local storage within the AWS environment is

still quite rare with bioinformaticians• Cheap reliable backup of large amounts

of data • Scalable grid assembly • Full automated pipeline genbank file to

results • Directed sequencing against a group of

genes • Something tied directly to dbGAP - Very

hard to automate data transfers with dbGAP

• Comparative analysis • Again, just entering this realm. The idea

of a standardized platform to evaluate data is appealing.

• Sequence Data Management • Datasets generally too large for cloud

computing • Large scale file transfer and analysis


5. What new cloud, or commercial NGS services would you like to see offered in the future?

4. Are you concerned over security issues with cloud-based NGS solutions?



27

ReSPondent CoMMent:

Make NGS data more accessible through visualization. less reliance on bioinformatics people.”

1. Are you satisfied with the lowered cost, higher output, and integrated offerings coming from NGS platform products today?

2. Would you like to see more technologies that enable desktop sequencing, or is the current crop of offerings adequate?



Study Area: NGS SEqUENCING PlATFORMS


28

ReSPondent CoMMent:

Benefits from NGS will continue to be throttled by software not adequate to cope with analyses required and issues associated with sensible safe storage (costs that no one wants to pay for sensibly).”

Selected write-in responses:• Data management • User-friendly analysis software at low-

cost! • Sample prep• Accuracy and read length.• Transportability• LIMS and tracking systems• Easier preps• Consistency• Base calling accuracy • Less expensive runs• Speed• Cost of single molecule sequencing• Faster assembly tools, better repeti-

tive sequence analysis, ability to map translocations/insertions/ and track copy number

• Desktop• The ability to perform small pilot proj-

ects that currently require only a single lane of a flow cell. Most sequencing services cannot handle these small jobs

that would require sharing of the high-throughput resources.

• Storage and data accessibilities, im-proved the ease of use of the software workflow for QC and downstream analy-sis

• Karyotyping from SNPs• I’m eager for single molecule sequenc-

ing systems and “third generation” — the current second generation systems just fail to provide enough read length and accuracy for a precise COMPLETE assembly — I’m waiting for the time when NGS doesn’t need to be validated by qPCR, Sanger sequencing etc.

• Error rates• Lower costs, FDA approved, CLIA &

supported documents• Quality of data output & quality analysis• Data storage


3. In the area of advanced platform systems what would you like to see improved?


29

1. Current annual sales estimates for DNA sequencing hardware along with medical gene tests and molecular diagnostics are about $4bil. Some feel they could reach $100bil driven by advancements in NGS technologies, and applied usage. Do you agree, and if so how long do you think it will take to achieve such growth?

If you agree, how long do you feel it will take?



Study Area: FUTURE GROWTh OF NGSReSPondent CoMMent:

currently, people are analyzing NGS data like it is a more fancy microar-ray. We need to shift our ideas about normalization and analysis so that we can develop new, NGS- specific methods and algorithms.”


30

2. Do you feel the future growth of NGS will take place more in large sequencing centers, or at researcher’s desktops?

3. In your opinion, if biotechnology companies are allowed to patent genes will it slow the overall progress of NGS?



ReSPondent CoMMent:

certain technolo-gies will act as ‘stepping stones’ to the next BIG technological advance-ment. I think PacBio technology will eventu-ally lend its technology to things beyond just dNa sequencing.”


31

4. Do you feel that NGS today adequately integrates with biology?


Selected write-in responses:• Workshops designed for biologists, not

necessarily bioinformaticians • A major cancer discovery based on NGS

work • Accurate single-molecule system • Data storage, back-up & transfer, &

speed/ cost. • $1000 assembled, annotated genome • Highly accurate multi analytic predictive

biomarker (diagnosis, prognosis or treat-ment response) for a common disease

• Lower cost for easy to use desk top models

• Genome editing • Getting more biologists into the analysis

- to really see an impact of the results of the sequencing we already have...

• A true accurate single molecule sequenc-er with 100’s of Gbs of sequence output.

• Fast, high length reading of sequences, specially in transcriptome sequencing.

• Open-market services • Improved data visualization and analysis

tools • Highly efficient analysis pipelines that run

on a laptop rather than a parallelized HPC environment.

• Success of Oxford’s Nanopore technology • Every new child born in the US had

the opportunity to have their DNA sequenced for free by US government-- database used as a base for various programs

• Changing the IP management aspect to one in which “pools” are created and simple cross licenses are used.. similar to the entertainment industry’s handling of movie/distribution rights.

• Adoption of standard data analysis & data format. AKA improving the repro-ducibility of NGS data.


5. If there were a single event that could have the greatest impact on advancing NGS what do you feel it might be?

ReSPondent CoMMent:

Biology…get the biologist/Md closer to interpreting the data. statistical relevance does not include biological relevance.”


Survey 2

32


33

Researcher currently using NGS

Researcher or bioinformatician currently analyzing/processing NGS data

Support a core facility or sequencers and handle data management or storage

Not currently using NGS, but am in the research/discovery stage

2. How can we develop a real industry reference point for better data management in conducting future NGS experimentation (check all that apply)

0%

10%

20%

30%

40%

50%

60%

70%

Government intervention

User-driven Vendor inclusion into their products

Q2





directives

1. Which of these best describes you? (select one)

Total respondents: Users- 371 Non-users- 385


Q20 . WHat IS needed?

The future of NGS is dependent on its meaning-ful use in personalized medicine.”


Researcher or bioinformatician currently analyzing/ processing NGS data


not currently using nGS, but am in the research/discovery stage






34

3. Are you currently, or planning to outsource NGS? (check one)

0%

10%

20%

30%

40%

50%

60%

70%

Yes No

Q3







The cost of sequenc-ing is moot, now the data deluge is coming and none of the experiments are reproducible because of data storage and sharing data issues.”


35





4. Which of the following phases are you in? (check one)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

At the experimental phase At the data analysis phase

Q4







Plug and play sequencing — very easy, cheap and reliable technology.”






36

5. What are the challenges of NGS moving to the clinic? (check all that apply)

0%

5%

10%

15%

20%

25%

Data Management

Data Storage

Analytics Inadequate Mutation

Databases

High costs Training Security Compliance issues

Q5Researcher currently using NGS




Selected write-in responses:

• Translating the data for physicians• Reimbursement• reliability of data (NGS accuracy)• Data integration (with clinical attributes)• True integration with the patient's EHR• Interpretation of novel / new variants and linking to disease phenotype• Bioethics/Consent• unavailability of reference or gold standard datasets



37





6. What do you see as the timing for NGS moving to the clinic? (select one)

0%

10%

20%

30%

40%

50%

60%

Within a year 2-3 years Over 3 years

Q6







a concrete and com-pelling real-world demon-stration of value to public health commensurate with costs.”






38

7. How long do you personally believe NGS data need to be stored?


0%2%4%6%8%

10%12%14%16%18%20%22%

Research Data Clinical Data

2-5 yearsResearcher currently using NGS




0%2%4%6%8%

10%12%14%16%18%20%22%


Under 2 yearsUnder 2 years Researcher currently using NGS

Under 2 years Researcher or bioinformatician currently analyzing/processing NGS data

Under 2 years Support a core facility or sequencers and handle data management or storageUnder 2 years Not currently using NGS, but am in the research/discovery stage

0%2%4%6%8%

10%12%14%16%18%20%22%


Over 5 years






eventually patients will demand to have se-quencing done to receive proper and most effica-cious treatments.”


39





0%2%4%6%8%

10%12%14%16%18%20%22%


Over 10 years





0%2%4%6%8%

10%12%14%16%18%20%22%


Indefinitely






ability to readily analyze the data without having to be a computer genius.”






40

8. Please estimate your annual cost to store one terabyte of NGS data.

There is no simple answer when it comes to the cost of storing scientific data. Ask-ing specifically about NGS data compli-cates the answer even more. This ques-tion was not intended to extract a literal answer, but rather to gain some insight into how NGS data costs are calculated, and reveal some trending around that. Re-spondents’ answers to the annual cost of storing a terabyte of data ranged between one dollar, and one million. In some cases respondents explained off higher stor-age costs as relating to overall IT costs, personnel, equipment, media, etc. be-ing factored in. Those with very low cost answers gave little explanation as to their rationale indicating that many respondents simply had no idea as to what storage really costs.

There were 642 responses received to this question. Of those responses only 356 included cost estimates with the bal-ance indicating various responses, mostly

stating “Don’t know.” To arrive at some type of answer, an average cost was cal-culated across all 356 responses with cost estimates received from both the current NGS user groups and the potential users. Then the top five highest and lowest cost estimates were removed and a second average cost was calculated. Findings are as follows:• Unfiltered average= $41,408 annual cost

per terabyte• Filtered average= $31,044 annual cost

per terabyteThe NGS user group trended higher

with their cost projections than did poten-tial users. That would suggest NGS users do place a higher price tag on data storage than the non-user group.



PcR-free sequenc-ing, which will bring down cost and simplify data analysis by eliminating major sources of arti-facts.”


41





9. Do you believe the cloud is over-hyped as a viable solution to improve NGS over the coming 2-3 years? (check one)

0%

10%

20%

30%

40%

50%

60%

70%

No Somewhat Strongly

Q9






10. Are you considering using cloud technologies for NGS data analysis/sharing? (check one)

0%

10%

20%

30%

40%

50%

60%

Yes No

Q10







Interest in general public to have their personal genomes sequenced.”






42

12. Would you consider outsourcing the experimental phase of NGS for data analysis to a cloud-based provider? (check one)

0%

10%

20%

30%

40%

50%

60%

Yes No

Q12






11. If yes (Q10), when are you considering using cloud technologies? (check one)

0%

10%

20%

30%

40%

50%

60%

70%

80%

Within the coming year? Within the coming 2-3 years?

Q11







43





13. What are the hurdles to embracing cloud computing/storage? (check all that apply)

0%

10%

20%

30%

40%

50%

60%

70%

80%

Cost Availability Knowledge Not advanced enough

Data Transfer Issues

Security Internal resources

Q13







• The cloud is not really a new technology — just repackaged.• Regulatory requirements for clinical data• Just needs to be more fully developed, and must be easy to use• Lack of depth of scientific analysis offered; no comprehensive cross database• Data management






44

14. At what point in the R&D process do you believe analysts should be involved? (select one)

0%

10%

20%

30%

40%

50%

60%

70%

80%

From the very first stages of experimental design

Once early results come in to help plan follow-up

experiments

Once all the data is in to conduct a complete analysis

Q14







Personalization: making NGS so cheap and simple and small sized that the common people could use it (built in mo-bile phones)”


45





15. Do you feel this timetable is being accomplished within your own organization? (select one)

0%

10%

20%

30%

40%

50%

60%

70%

Yes No

Q15







a well crafted update to patent law that properly allows for gene patents and resolves the issues that we currently are having.”






46

16. Are users/researchers adequately trained on the proper use of NGS systems within your particular organization in the following areas?


60%

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

Yes No

Experimental Design





0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

Yes No

Sequencers






organized competi-tions that provide gold standard datasets and call for analysis algorithms.”


47





17. Are current data visualization tools adequate for your NGS research and analysis needs? (check one)

0%

10%

20%

30%

40%

50%

60%

70%

Not adequate at all

Reasonably adequate

Very adequate

Q17






0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

22%

24%

Yes No

Analysis Software






More robust analyti-cal tools that have open source flexibility, but a friendly and efficient user interface.”






48

18. Ranked in order of difficulty, with 5 being the most difficult, please define the most challenging processes you face within your NGS workflow. (please rank)

Average Total respondents: Users- 303 Non-users- 264

0%

10%

20%

30%

40%

50%

Not Difficult at All

Slightly Difficult

Somewhat Difficult

Very Difficult Extremely Difficult

Sample prep or library construction

0%

10%

20%

30%

40%

50%Sequencing


Slightly Difficult

Somewhat Difficult


0%

10%

20%

30%

40%

50%Data analysis and construction


Slightly Difficult

Somewhat Difficult



advances in per-sonalized medicines will positively impact the future of NGS.”


49





0%

10%

20%

30%

40%

50%


Slightly Difficult

Somewhat Difficult


Storage

Not currently using NGS, but am in the research/discovery stageSupport a core facility or sequencers and handle data management or storageResearcher or bioinformatician currently analyzing/processing NGS dataResearcher currently using NGS

40%

0%

10%

20%

30%

40%

50%


Slightly Difficult

Somewhat Difficult


Moving the data along the workflow





0%

10%

20%

30%

40%

50%


Slightly Difficult

Somewhat Difficult


Sharing data with collaborators


Support a core facility or sequencers and handle data management or storageResearcher or bioinformatician currently analyzing/processing NGS dataResearcher currently using NGS


a significant ad-vance/paradigm shift in data storage/management — not the cloud, but an infrastructure solution.”






50

19. What single event do you feel could most negatively impact the future of NGS? (check one only)

0%

5%

10%

15%

20%

25%

Gene patents Migration of sequencing to big sequencing

centers from smaller labs

Lack of industry

standards

Budget cuts in NIH funding

Unplanned, or overrun costs

Lack of qualified scientists

Lack of qualified analysts

Inadequate data

visualization tools

Poor data management

High storage costs

q 19







• Need to interoperate with colloborators etc.• Ongoing release of upgrades means centres will keep waiting until technology is

stable.• Failure to demonstrate clinical relevance• Poor predictability• Rampant incompetent management



The development of industry standards that guarantee that only pro-cessed NGS data need to be stored (small footprint) and that those data are stored in a consistent format that is appropri-ate for any downstream analyses researchers from a variety of backgrounds may require.”

• Large scale adoption and migration to cloud computer systems.

• Availability of analysis resources under one umbrella!

• Cheap sequencer offering high through-put long reads and simple to use

• FDA involvement• Migration of sequencing to big sequenc-

ing centers from smaller labs• Access to high quality DNA with good

associated clinical data• Complete and open publication of re-

sults• Uniformity in standards, analysis, more

trained informaticians. The cost of se-quencing is moot, now the data deluge is coming and none of the experiments are reproducible because of data stor-age and sharing data issues.

• Better sequencing technologies, with high throughput (like Hi-Seq) and long read lengths (3kb+) at much cheaper costs.

• The further development of open-sourced analysis and visualization tools, as well as better characterization of bench mark standards; I’m specifically thinking of RNA-seq here.

• Plug and play sequencing--very easy, cheap and reliable technology.

• Standardize platforms and analysis tech-niques.

• Increased standardization and develop-ment of highly documented, open file formats.

• Clear path to monetization• An NGS apperatus that can sequence

an entire human genome with complete data analyses within a week and less than $1,000.

• Releasing it to clinical labs.• Solving data managemen storage• NGS can replace the single nucleotide

polymorphism (SNP)-based approaches currently used during clinical trials to search for associations with efficacy and safety end-points, which is essential to the successful registration and approval of that molecule.

• Implementation of industry standards and change in gene patent law

• Delivery of experimental platforms which combine (1) minimal labor, (2) minimal running costs, and (3) minimal capital investment but can rapidly de-liver actionable sequencing data starting from clinical material

• Cost reduction• Development of composable tools to

escape the issues with single-stream workflows having non-reproducible black-box components.

• A concrete and compelling real-world demonstration of value to public health commensurate with costs. Advanced imaging faced this hurdle, but the benefits were so immediately obvious that it has become indispensable and commonplace. NGS is nowhere close to being at this stage nor is it certain it will ever get there.

• The development of industry standards that guarantee that only processed NGS data need to be stored (small footprint) and that those data are stored in a con-sistent format that is appropriate for any downstream analyses researchers from a variety of backgrounds may require.

• Collaboration• A significant advance/paradigm shift in

data storage/management — not the Cloud, but an infrastructure solution.

• Advances in personalized medicines will positively impact the future of NGS.

• Eventually patients will demand to have sequencing done to receive proper and

20. What single event, in your opinion, can most positively impact the future of NGS? (Describe in 100 words or less)

51


52


National agreement on standards for the entire process from design to storage.”

20 continued. What single event, in your opinion, can most positively impact the future of NGS?

most efficacious treatments. This area is still in its infancy but I think it will grow with public demand as development of HIV directed drugs did when there was a mandate from specialized g roups fol-lowed by public demand.

• Understand the biological meaning of the 97% of non-coding region

• Clear regulatory guidance and FDA guid-ance on moving forward in true clini-cal world and applying it to predict the outcome of real patient samples

• Good experimental design based on clinical hypotheses and purposes.

• Shared databases of not only variants, but also common artifacts that arise (ei-ther due to the sequencing technology, or due to the underlying structure of the genome such as repeats, copy number variation, pseudogenes).

• Centralized databases that help filter re-sults into confident and likely artifactual categories will be invaluable!

• Organized competitions that provide gold standard datasets and call for analy-sis algorithms.

• Creation of universal reference ge-nomes

• Simply (actually not so simple) — con-tain cost, develop standards, develop in-teroperable technologies and implement proper security. All of the items listed above would fall under the interoperabil-ity umbrella — a single entity.

• Security to meet HIPPA standards. Prop-er de-identification of genomes.

• National agreement on standard for the entire process from design to storage

• Major IVD providers making the decision to commercialize a product readily avail-able to everyone

• $1000 per whole genome sequence• New sequencers to generate better

quality values• Successful treatment of rare genetic

diseases, when the improvement can be clearly linked to NGS

• Personalization: making NGS so cheap and simple and small sized that the common people could use it (built in mobile phones)

• A project targeted to organise existing resources and build up new ones into an NGS network, involving (1) clinicians, (2) scientists that already have a lot of experience with NGS, (3) engineers for building up a data infrastructure, and (4) managers to bring coherence into the system.

• PCR-free sequencing, which will bring down cost and simplify data analysis by eliminating major sources of artifacts.

• A significant clinical actionable example of medical resequencing. Right now we can’t even get clinical uptake of validat-ed pgx tests (see a growing list from the fda). I fail to see why NGS is going to come from left field and change all this.

• Let’s first get clinical uptake of things we already know to work. NGS is currently too often science driven by capacity rather than query. The cloud in its turn is capacity instead of ingenuity.

• The development of more advanced data analysis tools which can effectively combine different types of NGS data (e.g. DNA, mRNA, methylation patterns, chromatin marks, etc) into one big bio-logical picture.

• Developing better college programs to educate analysts

• Moving NGS to centralised / special-ised centres containing the experts in the field. This lowers running costs and labour costs. Such central facilities can also serve as centres of training and



Moving NGS to centralised / specialised centres containing the experts in the field. This lowers running costs and labour costs. Such central facilities can also serve as centres of training and education until such time most scientists under-stand what they are doing, not only in data usage, but in the administration and management involved with NGS.”

education until such time most scien-tists understand what they are doing, not only in data usage, but in the admin-istration and management involved with NGS.

• Simplification of patient consent forms and privacy issues General support for these issues//guidelines (we are not legal departments!)

• More robust analytical tools that have open source flexibility, but a friendly and efficient user interface.

• A successful clinical trial/biomarker ap-proval by a regulatory authority.

• Interest in general public to have their personal genomes sequenced.

• A well crafted update to patent law that properly allows for gene patents and resolves the issues that we currently are having.

• Spreading the word on the accomplish-ments and what it means in the future.

• The media doesn’t cover it enough. Most non Life Sciences people know little about what is going on and what we are trying to do.

• Easily interpretable data. MD’s con-stantly tell us that they don’t know what

it means and how to take action on this deluge of information. So actionable data backed by retro or prospective studies that produce clear guidelines for the practicing clinician.

• Incorporation into personalized medi-cine. The genetics and epigenetics are paramount to personalized medicine and it will be the NGS company who successfully addresses this (through development and partnering) that will be the industry standard in 5 yrs.

• Ability to readily analyze the data with-out having to be a computer genius. I’m not up on computer technology and do not for the life of me know how to program or use publicly available NGS raw data. If I did, some of the answers I’m looking for might already be avail-able. I’m hesitant because of the current need for a bioinformatics expert as a lab member or collaborator, yet I know what I’m looking for, just don’t know how to do it.

• The future of NGS is dependent on its meaningful use in personalized medi-cine.

53


54

The Cambridge Healthtech/CHI Media Group is conducting a multi-faceted market study on the future of next-gen se-quencing (NGS) technologies, services and NGS functionality. Results from this survey will be used in designing the next one. Through your participation you will have an opportunity to possibly shape the future of NGS with your input. You will also be able to review the survey findings and engage in online post-study commentary.

Thanks for answering any of the following questions, based on your job responsibility, and for your valued insight.

1. do you own, or support a major nGS platform? If so, which of the following:Life Technologies ( ) which system___________________________________Illumina ( ) which system___________________________________Roche/454 ( ) which system___________________________________other___________________________________________

2. Why do you sequence? (write-in response)

3. What is your primary application? (write-in)

STUDY AREA: NGS COMPUTING INFRASTRUCTURE

1. Is currently available computer infrastructure (serv-ers/storage/etc) adequate enough to support today’s needs for nGS? Yes ( ) No ( )

2. do you feel computing infrastructure will keep pace with market development from the growth of plat-form technologies like sequencers from Illumina, Life technologies (applied Biosystems and Ion torrent), roche/454, Complete Genomics, Helicos, oxford nano-pore, pacific Biosciences, etc.? Yes ( ) No ( )

3. do you generally account for any unforeseen infra-structure costs into your nGS system spending, like data handling and storage, or do these costs tend to climb faster than anticipated? Adequately factored ( ) Unexpected costs climb higher than anticipated ( )

4. Is cloud-based nGS growing, or losing appeal within your organization as a traditional infrastructure re-placement? More appealing ( ) Less appealing ( )

5. What areas of concern, or need can you identify in nGS infrastructure? (Write-in)

STUDY AREA: NGS SOFTWARE

1. In the area of nGS software please rate on a scale of 1-5, with 5 highest, your satisfaction with current products available in the following categories based on ability to support your research demands:Genome assembly 1( ) 2( ) 3( ) 4( ) 5( )Single molecule sequencing systems 1( ) 2( ) 3( ) 4( ) 5( )High-throughput sequencing 1( ) 2( ) 3( ) 4( ) 5( )Re-sequencing 1( ) 2( ) 3( ) 4( ) 5( )Sequence Data Management 1( ) 2( ) 3( ) 4( ) 5( )Single molecule analysis 1( ) 2( ) 3( ) 4( ) 5( )Pre-analysis 1( ) 2( ) 3( ) 4( ) 5( )Comparative analysis 1( ) 2( ) 3( ) 4( ) 5( )Follow-up analysis 1( ) 2( ) 3( ) 4( ) 5( )LIMS 1( ) 2( ) 3( ) 4( ) 5( )Pipeline 1( ) 2( ) 3( ) 4( ) 5( )Visualization 1( ) 2( ) 3( ) 4( ) 5( )

2. In any of the above software categories, or any not listed here, what key improvements do you feel need to be made for nGS to advance to its next generation of improvement and productivity? Write-in)

3. do you feel current nGS systems are available that are centralized enough to efficiently support the general, and growing demands of nGS? Yes ( ) No ( )

4. does your organization prefer commercial or open-source nGS software solutions? Commercial ( ) Open Source ( )

5. If you were highly confident of a commercial software offering’s capability to support your needs would you invest in it, even if a less proven, but open-source alter-native was available?Yes ( ) No ( )

SURvEY 1The Future of NGS: A life Science Market Study:


55

STUDY AREA: NGS SERvICES

1. How much of your overall nGS work is conducted within your organization, vs. using an outside service?Under 25% done in-house ( ) Under 50% ( ) Under 75% ( ) Over 75% ( )

2. What cloud-based services has your organization added over the past 12 months? (write-in)

3. do you find large data/file-transfer a problem that can hurt the growth of nGS? Yes ( ) No ( )

4. are you concerned over security issues with cloud based nGS solutions? Mildly ( ) Reasonably ( ) Very ( )

5. What new cloud or commercial nGS services would you like to see offered in the future? Write-in

STUDY AREA: NGS SEqUENCING PlATFORMS

1. are you satisfied with the lowered cost, higher output, and integrated offerings coming from nGS platform products today? Yes ( ) No ( )

2. Would you like to see more technologies that enable desktop sequencing, or is the current crop of offerings adequate? Need more ( ) Don’t need more ( )

3. In the area of advanced platform systems what would you like to see improved? Write-in

FUTURE GROWTh OF NGS:

1. Current annual sales estimates for dna sequencing hardware along with medical gene tests and molecular diagnostics is pegged at around $4bil. Some sources feel the market could reach $100bil in annual sales driven by advancements in nGS technologies, and applied usage. do you agree with that, and if so how

long do you think it will take:Yes, agree ( )No, do not agree ( )

If yES, It will take…Under 5 years ( ) 5-10 years ( )10-20 years ( )Over 20 years ( )

2. do you feel the future growth of nGS will take place more in large sequencing centers, or at the research-ers’ desktops:Sequencing centers ( ) By individual researchers ( )

3. In your opinion, if biotechnology companies are even-tually allowed to patent genes will it slow the overall progress of nGS?Yes ( )No ( )

4. do you feel that nGS today adequately integrates with biology? Yes ( )No ( )

5. If there were a single event that could have the great-est impact on advancing nGS what do you feel that might be? (Write-in)

GENERAl COMMENTS:

please write in any areas of coverage that you feel would be vital to learn more about relative to nGS market needs, or your own predictions around the future of nGS…

Your Name_____________________________________________

Organization____________________________________________

title___________________________________________________

email__________________________________________________

Phone_________________________________________________


56

• WhichofthesebestdescribesyouA. Researcher currently using NGS ( )B. Researcher or bioinformatician currently analyzing/pro-

cessing NGS data ( )C. Support a core facility or sequencers and handle data

management or storage ( )D. Not currently using NGS, but am in the discovery/re-

search stage ( )F. Have no familiarity with NGS ( )

• Howcanwedeveloparealindustryreferencepointfor better data management in conducting future nGS experimentation (check all that apply)A. Government intervention ( ) B. User-driven directives ( ) C. Vendor inclusion into their products ( )

• Areyoucurrently,orplanningtooutsourceNGS?At the experimental phase At the data analysis phase Yes ( ) Yes ( ) No ( ) No ( )

• WhatarethechallengesofNGSmovingtotheclinic(check all that apply).A. Data Management ( ) B. Data Storage ( ) C. Analytics ( ) D. Inadequate Mutation Databases ( ) E. High costs ( ) F. Training ( ) G. Security ( ) F. Compliance issues ( ) G. Other (write-in)

• WhatdoyouseeasthetimingforNGSmovingtotheclinic?A. Within a year B. 2-3 years C. Over 3 years

• HowlongdoyoupersonallybelieveNGSdataneedtobe stored? Research Data Clinical Data Under 2 years ( ) Under 2 years ( ) 2-5 years ( ) 2-5 years ( ) Over 5 years ( ) Over 5 years ( ) Over 10 years ( ) Over 10 years ( ) Indefinitely ( ) Indefinitely ( )

• Pleaseestimateyourannualcosttostoreoneterabyteof nGS data.Est. cost per terabyte-(write in)

• Doyoubelieve“Thecloud”isover-hypedasaviablesolution to improve nGS over the coming 2-3 years? No ( )Somewhat ( )Strongly ( )

• AreyouconsideringusingcloudtechnologiesforNGSdata analysis/sharing Within the coming year? Within the coming 2-3 years Yes ( ) Yes ( ) No ( ) No ( )

• Wouldyouconsideroutsourcingtheexperimentalphase of nGS for data analysis to a cloud based pro-vider?Yes ( ) No ( )

• Whatarethehurdlestoembracingcloudcomputing/storage (check all that apply)A. Cost ( ) B. Availability ( ) C. Knowledge ( ) D. Not advanced enough ( )E. Data Transfer Issues ( ) F. Security ( ) G. Internal resources ( ) H. Other (write-in)

• AtwhatpointintheR&Dprocessdoyoubelieveana-lysts should be involved?A. From the very first stages of experimental design ( )B. Once early results come in to help plan follow-up experi-

ments ( )C. Once all the data is in to conduct a complete analysis ( )

Do you feel this timetable is being accomplished within your own organization? Yes ( ) No ( )

SURvEY 2The Future of NGS: A life Science Market Study:


57

• Areusers/researchersadequatelytrainedontheprop-er use of nGS systems within your particular organiza-tion in the following areas?Experimental Design Sequencers Analysis SoftwareYes ( ) Yes ( ) Yes ( ) No ( ) No ( ) No ( )

• ArecurrentdatavisualizationtoolsadequateforyournGS research and analysis needs?Not adequate at all ( ) Reasonably adequate ( ) Very adequate ( )

• Rankedinorderofdifficulty,with5beingthemostdifficult, please define the most challenging processes you face within your nGS workflowLeast -------------- Most Sample prep or library construction ( ) ( ) ( ) ( ) ( ) Sequencing ( ) ( ) ( ) ( ) ( ) Data analysis and construction ( ) ( ) ( ) ( ) ( ) ( ) Storage ( ) ( ) ( ) ( ) ( ) Moving the data along the workflow ( ) ( ) ( ) ( ) ( ) Sharing data with collaborators ( ) ( ) ( ) ( ) ( )

• Whatsingleeventdoyoufeelcouldmost negatively impact the future of nGS (check one only):Gene patents ( ) Migration of sequencing to big sequencing centers from smaller labs ( ) Lack of industry standards ( ) Budget cuts in NIH funding ( ) Unplanned, or overrun costs ( ) Lack of qualified scientists ( ) Lack of qualified analysts ( ) Inadequate data visualization tools ( ) Poor data management ( ) High storage costs ( ) Other/write-in

• Whatsingleevent,inyouropinion,canmost positively impact the future of nGS(Write-in, 100 words max)

the future of next-gen sequencing (ngs) · pdf fileit is my pleasure to introduce cambridge...

Documents