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Internet2 Member Meeting Austin, Texas September 30, 2004

Unlocking Our Treasures Enhancing Access to Tissue for Genomics Research Henry Chueh Massachusetts General Hospital Harvard Medical School. Internet2 Member Meeting Austin, Texas September 30, 2004. “ Be careful of reading health books. You may die of a misprint .”. Mark Twain.

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Internet2 Member Meeting Austin, Texas September 30, 2004

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  1. Unlocking Our TreasuresEnhancing Access to Tissue for Genomics ResearchHenry ChuehMassachusetts General HospitalHarvard Medical School Internet2 Member Meeting Austin, Texas September 30, 2004

  2. “Be careful of reading health books. You may die of a misprint.” Mark Twain

  3. Genetic alphabet AT GC

  4. Mutations Image credit: U.S. Department of Energy Human Genome Program, http://www.ornl.gov/hgmis

  5. Molecular foundation of disease Image credit: U.S. Department of Energy Joint Genome Institute

  6. Epithelial Growth Factor Receptor EGFR Tyrosine Kinase Receptor Cell membrane K K EGFR-TK Inhibitor Proliferation Metastasis Invasion Angiogenesis Image credit: Modified from Astra-Zeneca educational materials

  7. Clustering of Mutations in the EGFR Gene at Critical Sites within the ATP-Binding Pocket Lynch, T. J. et al. N Engl J Med 2004;350:2129-2139

  8. Genomics research • Clinical research in the genomics era requires, at a minimum: • Access to diseased and healthy tissue • Clinical information associated with the tissue (demographics, outcomes, etc)

  9. Shared Pathology Information Network

  10. SPIN Collaborators • National Cancer Institute (NCI) • Children’s Hospital • Massachusetts General Hospital • Brigham and Women’s Hospital • Dana-Farber Cancer Institute • Beth Israel Hospital • UCLA Medical Center • Regenstrief Institute • Univ. of Pittsburgh Medical Center

  11. SPIN Themes • Think “framework” • Specifications clear enough to develop products independently • Local control • Network planning

  12. SPIN: p2p Model Assumptions • No ongoing aggregation of data, no central repository to govern • Provision of data into a SPIN node from systems internal to the institution is managed locally with SPIN tools • Any information search by any SPIN Query Tool is HIPAA Privacy Rule compliant

  13. SPIN Network Today BI OliveView Cedars UPMC VA HMS Running type A SPIN node software Link established Running type B SPIN software Link planned RI BWH UCLA MGH CH (other) SPIN HMS Tissue Banks VSL

  14. SPIN: Key Activities • Join: Become a member of the network • Host: Provision clinical, specimen data • Search: Locate specimens • Acquire: Obtain specimens

  15. SPIN Host / Search: Data Flow Source Systems Source Systems Clinical Systems Identified Data SPIN Protocols SPIN Node Software SPIN Loading Tools SPIN node SPIN Query SPIN Response Anonymous or De-identified Data Set De-identified Limited Data Set Codebook Internet Intranet Internal Threshold Institutional Firewall

  16. Clinical reports to coded annotations … <Specimen> <Topology> <Term Code="C0227375" Source="UMLS">Right colon</Term> </Topology> <Diagnosis> <Term Code="C0267375" Source="UMLS">Chronic colitis</Term> <Modifier Code="C0205177" Source="UMLS">Active</Modifier> <Modifier Code="C0205080" Source="UMLS">Mild</Modifier> </Diagnosis> <Diagnosis> …

  17. SPIN Query Propagation and Response BI Cedars Compose query using a Web browser SPIN (aggregate) XML Response Query Server SPIN XML request RI UPMC BWH SPIN peer responses return directly to originating SuperNode UCLA MGH CH SPIN request propagates SPIN

  18. Clinical Research Scenarios • ? Rare subset of non-small cell lung cancer (NSCLC) shares common mutation that would make it more susceptible to certain novel therapeutics • ? Infection with herpes zoster (chickenpox) virus enhances mutagenicity in lung cancer

  19. SPIN Open Architecture • Accommodates alternative node and query server implementations • Will accommodate additional data models and schema: • Clinical data (symptoms, outcomes, etc) • Clinical imaging data (MRI, CT scans, etc) • Molecular biology data (microarray data, etc) • Pathology imaging

  20. What’s ahead? • Bringing phenotypes in juxtaposition with genotypic information • NIH roadmap initiatives to include integrated biomedical computing • In silico experiments and analysis

  21. Acknowledgements Jules Berman (NCI) Isaac Kohane Clem McDonald Jonathan Braun Michael Becich Ulysses Balis David Berkowicz David Korn (AAMC) Elias Zerhouni (NIH)

  22. Image credit: U.S. Department of Energy Human Genome Program, http://www.ornl.gov/hgmis

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