Business Transformation – Becoming a Truly Data- Driven Pharmaceutical Company

Chris L. Waller, Ph.D.

OverviewPharmaceutical organizations are defining the road map for data integration but how prepared are they to base their decisions and practices on this data? Failure to truly encompass the attributes of a data driven unit will hurt your ability to compete in the market. This presentation will help business line executives and data professionals to understand the steps needed to create a data driven organization, by making the right decisions, while providing some real life examples on companies who have done this successfully. • Defining an information architecture framework for global research and

development processes • Enlisting champions and creating an entrepreneurial spirit to empower

people to own new processes • Key role players you cannot do without – creating a cohesive strategy

and building a winning team

OverviewPharmaceutical organizations are defining the road map for data integration but how prepared are they to base their decisions and practices on this data? Failure to truly encompass the attributes of a data driven unit will hurt your ability to compete in the market. This presentation will help business line executives and data professionals to understand the steps needed to create a data driven organization, by making the right decisions, while providing some real life examples on companies who have done this successfully. • Defining an information architecture framework for global research and

development processes • Enlisting champions and creating an entrepreneurial spirit to empower

people to own new processes • Key role players you cannot do without – creating a cohesive strategy

and building a winning team

The Worldwide Healthcare Ecosystem

Consumers/Patients

LicensesRegulationsApplications

and Approvals

CoverageCare$

“orders” $Products$

PolicyMakers

AccreditationEntities

Premium $

Licensed Health Prof’nals

Diagnostic Services/GCRCs

Health Delivery Systems/Facilities

Nursing and Home Health

Pharma.(including Biotech)

MedicalProducts

Distributors

Pharmacies ContractServices

InfoCompanies

Providers

Producers

PayersRegulators

$

Employers

Health Plans

Govt. Programs

CarveOuts(PBMs, others)

Global InsurersGeneric

Mfgs.

Healthcare Trends and Technologies

Research Development Commercial Medical EMR/PHR HIE NHIN Products Services

Producers Providers Payers

Regulators

Precision Medicine

Clinical Trial Design and Execution

Expansion into Emerging Markets

Pharmacovigilance

Patient Care and Outcomes

Comparative Effectiveness

Next Generation Sequencing-omicsBig Data Analytcis

Patient StratificationePlaceboVirtual TrialsRemote Monitoring

MobilityDigital MarketingSocial Sentiment Analysis

Social Media MiningBig Data Analytics (Text)

Clinical Decision Support AidsCare Augmentation ProvisionTele-health (mHealth, eHealth…)

Big Data AnalyticsBehavioral Modification Tools-etics

Trends

Technologies

A week in the lab can save an hour of data mining.Today’s real problem – how to use what we already know!

Data Data Data

Data

Data

Yesterday

Tomorrow

Data Mining

Experiments

True/False

Massive Databases

Data

-

Cheminformatics Platform at Merck

Sharepoint (one.merck.com/cheminfo)End User Interface, Analytics Tools, Chemist WorkBench

Get Me The Data What Do I Make Next? Now, Help Me Make It

Sharepoint (one.merck.com/cheminfo)Integration and Model/Workflow Services

Sharepoint (one.merck.com/cheminfo)Core Merck Data Repositories

Sharepoint (one.merck.com/cheminfo)Transactional IT Applications

LeadIdentification

Lead Optimization

Preclinical Candidate to

First in Human

First in Human to

Phase 2B

Phase 3 to File

Lead Optimization

Lead Optimization

PCC

Sharepoint (one.merck.com/cheminfo)

Local (Project Team) QSAR Models

Sharepoint (one.merck.com/cheminfo)

Ligand-based Design Support

Sharepoint (one.merck.com/cheminfo)

Structure-based Design Support

Need to converge activities to gain the most value and leverage

SARChemistry

Screening

ChemicalGenomicsChemistry

Genomics

PathwaysScreening

Genomics

Today

IndependentPairwise Processes

Chemical -

Biology

Chemistry

Screening Genomics

Future State

Converged Processes

Build Systems To FindCorrelation In The Data

The Greatest Information Content & Value Is In The Intersection Of The Data “Chemical-Biology”

-

Translational Research Platform at Merck

Sharepoint (one.merck.com/cheminfo)End User Interface, Analytics Tools, Chemist WorkBench

Get Me The Data What Do I Make Next? Now, Help Me Make It

Sharepoint (one.merck.com/cheminfo)Integration and Model/Workflow Services

Sharepoint (one.merck.com/cheminfo)Core Merck Data Repositories

Sharepoint (one.merck.com/cheminfo)Transactional IT Applications

LeadIdentification

Lead Optimization

Preclinical Candidate to

First in Human

First in Human to

Phase 2B

Phase 3 to File

Pre-LeadOptimization

Pre-LeadOptimization

Lead Optimization

Lead Optimization

Early Development

Early Development

PCC Phase IIb

Chemical Biology(chemical probes predict targets)

Systems Biology(off target activity prediction)

Clinical Trials(ADMET predictions)

Chemical Pharmacology(toxicity predictions)

From Two Crows Consulting in 1999

(1)What Are The Questions(2)Agile Process First – Find All The Data and Layers(3)Then Build The Solution on SOA Framework

Information Models

Source: http://www.inmoncif.com

Source: http://www.w3.org

Source: Apache Software Foundation

Hybrid Solutions

Source: Cloudera and Teadata

OverviewPharmaceutical organizations are defining the road map for data integration but how prepared are they to base their decisions and practices on this data? Failure to truly encompass the attributes of a data driven unit will hurt your ability to compete in the market. This presentation will help business line executives and data professionals to understand the steps needed to create a data driven organization, by making the right decisions, while providing some real life examples on companies who have done this successfully. • Defining an information architecture framework for global research and

development processes • Enlisting champions and creating an entrepreneurial spirit to empower

people to own new processes • Key role players you cannot do without – creating a cohesive strategy

and building a winning team

Information SilosAn information silo is a management system incapable of reciprocal operation with other,

related management systems.

Information Silo Causes

• Technology– Enterprise data systems are too rigid, slow, prone to

outages, hard to use…• Process

– Legacy processes don’t factor in the need for information sharing (the technologies didn’t exist)…

• People– People are not properly incentivized for

collaborative work and lack trust…

Information Silo Effects

• Limits productivity• Stifles creativity• Hampers innovation• Inhibits collaboration• <Fill in the blank with your favorite pejorative

expression>

Information Silo Solutions

• Provide technologies that support information sharing processes and reward collaborative behaviors (people).

Information Integration Technologies (Life Sciences)

• Standard Data Models (CDISC, etc.)• Standard RDB Platforms (Oracle, etc.)• Standard Ontologies (W3C, etc.)• Semantic Platforms (IOInformatics, etc.)• All of the above (Open PHACTS)

Collaboration Platforms(Life Sciences)

Collaborative Business Culture

• Not knowing the answer. • Unclear or uncomfortable roles. • Too much talking, not enough doing. • Information (over)sharing. • Fear of fighting. • More work. • More hugs than decisions. • It's hard to know who to praise and who to blame.

http://blogs.hbr.org/cs/2011/12/eight_dangers_of_collaboration.html

Why Don’t People Collaborate (Share Information)?

Collaborative Business Culture

• 10% of Senior HR Execs and 39% of Employees Believe that their Companies Effectively Encourage Collaboration

• Mutual Trust (Lack of) is a Significant Barrier to Collaboration– 31% of Developed Market R&D Staff Trust

Emerging Market Colleagues– 22% of Emerging Market R&D Staff Trust

Developed Market Colleagues

Source: Research and Technology Executive Council Research

Stimulating Information Sharing (NIH/FDA)

FDA currently houses the largest known repository of clinical data (all of which is de-identified to protect patients’ privacy), including all the safety, efficacy, and performance information that has been submitted to the Agency for new products, as well a an increasing volume of post-market safety surveillance data. The ability to integrate and analyze these data could revolutionize the development of new patient treatments and allow us to address fundamental scientific questions about how different types of patients respond to therapy.

With the establishment of NCATS in the fall of 2011, NIH aims to reengineer the translation process by bringing together expertise from the public and private sectors in an atmosphere of collaboration and precompetitive transparency.

Through partnerships that capitalize on our respective strengths, NIH, academia, philanthropy, patient advocates, and the private sector can take full advantage of the promise of translational science to deliver solutions to the millions of people who await new and better ways to detect, treat, and prevent disease.

Stimulating Information Sharing (NHS, EU)

Prime minister David Cameron has announced a package of measures designed to boost the UK's life sciences industry. These include a £180 million fund to support innovation and plans to allow healthcare companies access to NHS patient records to support research.

This conference will explore how EU funding can promote economically and socially sustainable innovation models with the aim of more openness, easier accessibility and higher result-oriented efficiency.

Horizon 2020 is the financial instrument implementing the Innovation Union, a Europe 2020 flagship initiative aimed at securing Europe's global competitiveness.

Caveats

A well-constructed system can enable scientist to test but also generate new hypotheses using well-curated, high-content translational medicine data leading to deeper understanding of various biological processes and eventually helping to develop better treatment options. Active curation and enterprise data governance have proven to be critical aspects of success.

The Future: Virtual Life Sciences

• Forrester has identified three themes driving the future of collaboration and information sharing technology– The global, mobile workforce

• 62% of workforce works outside an office at some point (this number is growing)

– Mobility driven consumerization• Cloud-based collaboration solutions are being used in

conjunction with numerous devices

– The principle of “any”• Need to connect anybody, anytime, anywhere on any device

Life Science Information Landscape

A rapidly evolving ecosystem

26

Big Life Science

Company

Yesterday Today Tomorrow

Yesterday Today TomorrowInnovation Model

Innovation inside Searching for Innovation Heterogeneity of collaborations. Part of the wider ecosystem

IT Internal apps & data Struggling with change Security and Trust

Cloud/Services

Data Mostly inside In and Out Distributed

Portfolio Internally driven and owned Partially shared Shared portfolio

The Evolving Life Sciences Ecosystem Evolving paradigm for the discovery of medicines (Collaborative)

A vision that points towards open innovation and collaborations Open research model to collectively share scientific expertise

Enhance speed of drug discovery beyond individual resource capabilities (Speed) Limited research budgets and capabilities driving greater shared resources Goal to see all partners succeed by accelerating the SCIENCE

Synergize Pfizer’s strengths with Research Partners (Knowledge) Pair Pfizer’s design, cutting edge tools, synthetic excellence with research partners (academics, not-for-profits,

venture capitalists, or biotechs) to develop break through science, novel targets, and indications of unmet medical need

Current example of academic and not-for-profits partners (Discover and Publish) Drive to publish in top journal with science receiving high visibility and interest

Body clock mouse study suggests new drug potentialMon, Aug 23 2010By Kate KellandLONDON (Reuters) - Scientists have used experimental drugs being developed by Pfizer to reset and restart the body clock of mice in a lab and say their work may offer clues on a range of human disorders, from jetlag to bipolar disorder.

Contacts: Travis Wager (travis.t.wager@pfizer.com) Paul Galatsis (paul.galatsis@pfizer.com)

a few months ago we entered into a collaboration with the giant pharmaceutical industry Pfizer to test some of their leading molecules for potential relevance to HD.

OverviewPharmaceutical organizations are defining the road map for data integration but how prepared are they to base their decisions and practices on this data? Failure to truly encompass the attributes of a data driven unit will hurt your ability to compete in the market. This presentation will help business line executives and data professionals to understand the steps needed to create a data driven organization, by making the right decisions, while providing some real life examples on companies who have done this successfully. • Defining an information architecture framework for global research and

development processes • Enlisting champions and creating an entrepreneurial spirit to empower

people to own new processes • Key role players you cannot do without – creating a cohesive strategy

and building a winning team

Collaboration and Information Sharing Barometer

• Does your company..– …motivate and link innovation efforts by

identifying and routinely communicating key areas for innovation activity?

– …have a strategy that allows for geographically dispersed staff to access the resources necessary to collaborate and share information?

– …have tools that support rapid collaboration, such as data sharing and analysis or crowdsourcing platforms?

People: Some Questions to Ask

• What is the staff structure as it relates to data reporting?

• Do staff members have the training they need to understand relevant data?

• Do staff members understand how to glean insights and actionable steps from data?

• Do staff members have good working relationships with data analysts?

http://wholewhale.com/data-culture-building/

Process: Some Questions to Ask

• Are staff accessing and communicating data across teams well?

• Do staff act on data or regularly share learnings from experiments?

• Are goals set in a way that can be tracked through metrics?

• Does the organization use a Gather<Analyze<Insight method?

• How often do staff receive data feedback?http://wholewhale.com/data-culture-building/

Technology: Some Questions to Ask

• Are tools in place to analyze large data sets (beyond Excel)?

• Are consistent naming and storage conventions in place across databases?

• Are dashboards and metrics updated as automatically as possible?

• Is data stored in a way that reporting can be done across the organization?

• Are semi-annual security audits and passwords changed?

http://wholewhale.com/data-culture-building/

OverviewPharmaceutical organizations are defining the road map for data integration but how prepared are they to base their decisions and practices on this data? Failure to truly encompass the attributes of a data driven unit will hurt your ability to compete in the market. This presentation will help business line executives and data professionals to understand the steps needed to create a data driven organization, by making the right decisions, while providing some real life examples on companies who have done this successfully. • Defining an information architecture framework for global research and

development processes • Enlisting champions and creating an entrepreneurial spirit to empower

people to own new processes • Key role players you cannot do without – creating a cohesive strategy

and building a winning team

Thank You

• Chris L. Waller, Ph.D.• chris.waller@merck.com• http://www.linkedin.com/in/wallerc