1. Overview of Discovery & Development Informatics at Lilly Rick Bishop, Manager, DDIT Phil Brooks, Information Consultant, DDIT Hans Constandt, Senior Business Consultant, DDIT Andy Ring, Information Consultant, DDIT Susie Stephens, Manager, DDIT

2. Agenda Introduction to Lilly Discovery & Development Informatics Plans External Focus

3. Introduction to Lilly

4. Eli Lilly Background A heritage more than 130 years strong Headquarters located in Indianapolis, Indiana, USA Approximately 40,000 employees worldwide Approximately 8,000 employees engaged in R&D Clinical research conducted in more than 50 countries Research and development facilities located in 8 countries Manufacturing plants located in 13 countries Products marketed in 143 countries

5. Breakthrough Products ** Lilly has launched 9 new products since 2001 ** Malignant pleural mesothelioma and lung cancer ** Type II diabetes (developed and marketed in partnership with Amylin pharmaceuticals) ** Erectile dysfunction ** Major depression and DPNP (Partnership with Quintiles) Osteoporosis in women past menopause ** Osteoporosis for men and women in post menopause who are susceptible to fractures Cancer (pancreatic and non-small-cell lung cancer; bladder and breast cancer in Europe) Type 1 & Type 2 Diabetes Humatrope  Growth deficiency Type 1 & Type 2 Diabetes Cardiac ischemic complications (developed by Centocor, marketed by Lilly) ** Treatment of ADHD ** Treatment of bipolar depression ** Treatment of severe sepsis ** Stress urinary incontinence (marketed in Europe with Boehringer Ingelheim) Schizophrenia, bipolar mania, and bipolar maintenance

6. Discovery & Development Informatics Functional Areas Biology Chemisty ADME/Tox Experimental Medicine Process R&D Skills Informatics Software engineering Systems integration Discovery PMO Discovery COE External Surveillance MaryJo Zaborowski, Information Officer 230 employees globally

7. Industry spends more to get less Source: PhRMA, FDA, Lehman Bros.

8. Patient-centric Focus

9. Silos Need to be Broken Down Data Transform Model & Understand Generate/Test Hypothesis Analyze & Mine TargetHitLeadPgSCSFHDFEDPD/RDFSFAFLGL Target To Hit To Lead To PgS Lead Optimization Pre-Clinical Development Phase IPhase 2Phase 3 Registration Launch Global Launch ProjectProgramProduct Exploratory Data Transform Model & Understand Generate/Test Hypothesis Analyze & Mine Data Transform Model & Understand Generate/Test Hypothesis Analyze & Mine Data Transform Model & Understand Generate/Test Hypothesis Analyze & Mine Data Transform Model & Understand Generate/Test Hypothesis Analyze & Mine Data Transform Model & Understand Generate/Test Hypothesis Analyze & Mine Data Transform Model & Understand Generate/Test Hypothesis Analyze & Mine Data Transform Model & Understand Generate/Test Hypothesis Analyze & Mine Data Transform Model & Understand Generate/Test Hypothesis Analyze & Mine Data Transform Model & Understand Generate/Test Hypothesis Analyze & Mine

10. Integrating Heterogeneous Data Cell/Assay Technologies

11. Re-Aligning IT Spend Source: Professor Peter Weill, MIT Sloan School of Management

12. Discovery & Development Informatics Plans

13. Custom Software Engineering Systems Integration Research Operations Workflow/ Business Logic Discovery SOA Components Ontology Data Consumers Data Providers Integration Services Custom COTS Composite Application Application CRO Ops DB Mart WS Application Ops DB Application Ops DB Application Ops DB Semantic Layer

14. Discovery Metadata: Architecture Application 1Application 2Application 3 … SOA Layer/Enterprise Service Bus (WebServices, Visualizers, DataAccess Components ) Authentication SOASOA DATADATA APPSAPPS SQLSPARQL Source Model 1 Source Model 2 Source Model 3 Source Model 4 Local Assertions Top Level Ontology Provenance Other Sources Other Sources Source … ETL Other Tools Spreadsheets Rdbms

15. Proposed Architecture RDFXMLRDFCSVWeb RDBMS Top level ontology RDF RDBMS RDF RDBMS Sparql endpoints Manual Automated Semantic pipes RDF Middleware - Relational2RDF XLS RDBMS Docs RDBMS (**) – URI / Unique resource identifiers Lilly & Public Structured & Unstructured Data sources. Standardize (*) – (**) Client APIs C#, Java, Ruby Browsers & Visualization Datamarts /Warehouses Desktop applications Domain Ontologies & vocabs Domain Ontologies & vocabs Domain Ontologies & vocabs (*) – Data clean, map to vocabularies, ontologies Security – http standard Lilly Security standards: LillyNet DIT, GMR

16. LSG Going Forward Evolve CAB toward CompositeWCF Establish ESB D2R Establish SOA fabric Governance - Design time Monitoring - Run time Extend semantics within LSG messaging Incorporate semantic provenance

17. External Focus

18. Open Innovation Group Activities Identify suitable innovation projects from the DDIT portfolio Work with internal scientist &/or external collaborators to create POCs of the identified projects Demonstrate value of innovation projects within DDIT Showcase novel solutions to senior management in LRL Promote work of group through Web site, newsletter, etc. Scout for interesting new technologies from universities, standards organizations Write up brief reviews of interesting technologies for dissemination across DDIT Organize presentations/demos of appealing technologies to DDIT Support Lilly’s open source projects Influence development of 3rd party products to better meet our needs

19. Benefits of Open Innovation Team Fast assessment of the value of a technology Quick delivery of informatics solutions to LRL that meet prioritized scientific needs Increased awareness of how emerging technologies may change the landscape in 3-5 yrs Streamlined dissemination of information about new technologies Use knowledge gained to make best investments going forwards Establish relationships with key technology players for the future environment Influence vendors to develop solutions in ways that work for us Increased success in using tools from academia More formalized process for developing ‘supported’ technologies Ability to more easily utilize output from the Open Innovation Center Raise awareness of DDIT and the importance of IT within LRL

20. Ongoing Open Innovation Projects RDF Access to Relational Databases Eric Prud'hommeaux End User Semantic Web Authoring David Karger Scientist-Driven Semantic Integration of Knowledge in AD Tim Clark, June Kinoshita Provenance Collection and Management Carole Goble, Beth Plale Linking Open Drug Data Chris Bizer Drug Target Networks Lászó Barabási

21. Standards Group Participation W3C –HCLS IG, RDB2RDF XG, Social Networking Workshop, tracking WACG, likely participation in DAWG CDISC –SDTM, Metadata Repository, SEND HL7 The Open Group EBI’s Industry Consortium

22. Conclusions Lilly is a successful mid-sized pharma company The pharma industry is under considerable pressure to become more effective Industry shifts requires a greater exploitation of information Need greater adoption of innovative solutions in cutting edge infrastructure and informatics LSG, Semantic Web and SOA are all in our architectural plans Increased focus on external collaborations