The Future of Pharmacogenomic Informatics Gerry Higgins, M.D., Ph.D.
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Transcript of The Future of Pharmacogenomic Informatics Gerry Higgins, M.D., Ph.D.
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 ScienceAssureRx Health, Inc.
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.
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)
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.
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
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 www.clinicaltrials.gov
→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