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The Future of Pharmacogenomic Informatics Gerry Higgins, M.D., Ph.D.

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Presentation on theme: "The Future of Pharmacogenomic Informatics Gerry Higgins, M.D., Ph.D."— Presentation transcript:

1 The Future of Pharmacogenomic Informatics Gerry Higgins, M.D., Ph.D.
tranSMART Knowledge Management Platform: Pre-competitive data-sharing and biomedical informatics Gerry Higgins, M.D., Ph.D. Vice President, Pharmacogenomic Science AssureRx Health, Inc.

2 Vision: Realizing the promise of translational biomedical research by provision and continuous improvement of an open source code base for data sharing and analytics. Mission: The tranSMART Foundation enables effective sharing, integration, standardization, and analysis of heterogeneous data from collaborative translational research by mobilizing the tranSMART open-source and open-data community.

3 tranSMART Foundation Board of Directors
Gil Omenn, University of Michigan Christoph Brockel, PA / Pfizer. Leroy Hood, ISB Garry Neil, Appletree Ventures Brian Athey, University of Michigan (ex-officio) Michael Braxenthaler, Pistoia Alliance and Roche (ex-officio)

4 First developed on i2b2 informatics platform by Dr
First developed on i2b2 informatics platform by Dr. Eric Perakslis while he was at Johnson & Johnson. First Pilot in 2011: Sharing of trial data for asthma drug development in Europe.

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7 Selected tranSMART adopters:
eTRIKS (IMI), $€24M, 5 years, 16 partners EMIF (IMI), $€24M, 5 years, 55 partners TraIT (CTMM), $€16M, 4 years, 26 partners TBIG (Janssen, Millennium, Sanofi & Pfizer) Coordination of tranSMART enhancements on pre- competitive basis University of Michigan Johns Hopkins University – Brady Institute for Urology One Mind for Research Traumatic Brain Injury, Neuroscience Portal U.S. Food and Drug Administration Drug Safety and several other use cases St Jude Children’s Hospital and Research Foundation AssureRx Health

8 Suggested Requirements for an Advanced Pharmacogenomics Knowledge Base
→ Query-based, faceted search framework in cloud → Service Oriented Architecture (SOA) → Access to private / proprietary data as might be contained in primary data sources such from pharma, biotech, academia & publishers through a pre-competitive data-sharing community →Access to NLP-processed text from both longitudinal de-identified EHRs and →Access to public resources in cloud, including FAERS and iAEC, published literature, NCBI resources, etcetera → Allow users to enter their own clinical or experimental data, use ‘Apps Store’ and open-source analytics (R, Cytoscape, etc) → Provide heterogeneous database service, based on standards such as OWL-S (ontology web language service) and RDF

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