The Future of Personalized Medicine
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Edgewater Technology Healthcare Executive Event Houston, TX October 2, 2008 Ed Martinez Moffit Cancer Center
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The Future of Personalized Medicine
- 1. A Cancer Center Vision: The development and state-wide adoption of a centralized scientific and clinical Data Warehouse The Future of Personalized Medicine Edward Martinez (Former VP & CIO of Moffitt Cancer Center) Case Study
- 5. The Solution: Total Cancer Care Total Cancer Care Personalized Cancer Care 2010 Study large populations… Identify cancer sub-populations… Develop therapies for sub-populations of individuals…
- 8. New Standard Of Care Personalized Molecular Medicine Signatures Central Data Warehouse 50,000 Patients (Primaries + Metastatic Biopsies) QOL, Clinical Tissue Survivorship Surveys Banking Pipeline Evidence IT Quality Therapeutic Based Improvement Solutions Trials Medicine TCC Affiliate MCC Consortium Network (Resections + Trials) (Metastatic Biopsies) The Building Blocks of Total Cancer Care
- 10. Potential to capture 50% of cancer cases In second highest cancer burden State State-wide affiliations allow for sharing of clinical and genomic information
- 14. Operational Data Flow Challenges Tissue Tracker Cerner Surginet OnCore HPV Colon 400 Capstone Galvanon MDDB Cancer Registry Capstone Micro Array LabVantage SurgiNet PathNet PharmNet Staging Area Data is extracted from source systems and delivered here ETL ETL ETL DR ETL DM ETL Data Warehouse Data is transformed into Standard Structures Tissue Analysis Person Tissue Events EMR Micro Array Data Mining Genetic Analysis EMR Analysis Event Analysis
- 16. Data Elements – Sample Person Biospecimen EMR Trials Age Gender Race Ethnicity Source Category Gross Diagnosis Preparation Type Assay Results Diagnosis Lab Results Medications Surgeries Scheduling Physician Protocols Studies Phases Participation Consent Therapy Event Type Hierarchy Attribute Result Date Association Chip Type Array Type Probe set Probe Signal Level Genes Present QC Metrics Form Observation Answer Language Skip Pattern MRN SSN Name Birth Date Address Date of Death Phone Events Questionnaire MicroArray PHI
- 19. Same Data – User Categories Nurse Bio-Informatics Scientist Data Manager Clinician Researcher
- 21. Vision: Aligned Data Sources Cerner OPTX Tissue Bank Lawson Cancer Registry CT Admin Affiliate Systems Sunquest Research Systems Other Databases Legacy Database
- 22. Vision: Disparate Sources CUI Extract, Transform, Load Common Data Semantics, Standards Interactive Presentation Lab or Medical Instruments IVR Hand-Held Databases Other Systems DB
- 24. Logical View: Shared Meta-Data Clinical Outcomes Facts Patient Descriptors Location Descriptors Protocol Descriptors Investigator Descriptors Date / Time Descriptors Data Collection Facts Patient Satisfaction Facts Trial Enrollment Facts Data Warehouse Facts Dimensions Data Warehouse Facts Dimensions Data Warehouse Facts Dimensions Data Warehouse Facts Dimensions
- 25. Logical View: Process-Driven View Per Protocol Per Study Per Site Per Patient Patient Screened Patient Randomized Data Set Received CRFs Received Data Set Coded Data Set Queries CRFs Certified Per Visit Patient Dropped Data Set Certified Safety Review Patient on Listing Patient Certified Patient Withdrawn
- 26. Data Pipeline Extraction / Capture Mapping Transformation OpTx Trial Metrics Affiliate Systems Cancer Registry Cerner (lists, code maps, dictionaries) Subject Area Data Marts Master Reference Data Analytics / Dashboards Standard Reports Live (ad hoc) reports Alerts Source Data Data Preparation Data Provisioning Applications Data Cubes 01 02 M F IF(sum(a,b) . . .
- 27. Enterprise Data Strategy Requirements: Scientific, Business, Functional, Technical, Data Implementation Plan Technology Architecture Vision
- 34. Integrating Genomic and Clinical Data
- 35. Data Governance Data Stewards Data Owners Data Governance and Monitoring Committee (DGMC) Data Users IT Executive Sponsors
- 38. Three Portals to Data Patient View Clinician View Researcher View TCC Multi-Dimensional Data Warehouse View my lab Clinical Data Gene Expression Results online • Data guides Rx Clinical Data Signatures
- 39. Building on the Foundation Genomic Data Biospecimen Data Quality P4P Costs Risk Factors Integrated Data System
- 40. How Pharmacogenomics Can Streamline Clinical Trials & Build Pharma Partnerships Traditional Clinical TCC Trial Trials Responders Only Broad Patient Population 10-12 Years 3-5 Years
- 42. PLASMA EXPRESSION URINE PROTEOMICS PROFILNG PROTEOMICS BIOINFORMATICS ( PREOP/postop) CONSULTING COMMERCIAL OPPORTUNITIES CPG CGH/LOH METHYLATION AGILENT/ (AGILENT AFFY SNP CHIP BASED) M 2 GEN TCC DATA WAREHOUSE TISSUE SINGLE CELL PHOSPHO- SEQUENCING PROTEOMICS (SOMATIC (SHOTGUN) MUTATIONS) PARAFFIN Molecular RTPCR Imaging TMA HIGH THROUGHPUT TECHNOLOGIES IN HOUSE VS. OUTSOURCE
- 45. Edward Martinez [email_address] 813-420-4703