The M.U.R.D.O.C.K. Study 22 Oct 2007

1. Introduction to the Medical CommunityThe Measurement to Understand Reclassification of Disease Of Cabarrus/Kannapolis Study The M.U.R.D.O.C.K. Study 22 Oct 2007

2. Agenda • Welcome and introductory comments • Andrew Conrad PhD - CSO LabCorp and NCRC • Lynne Scott Safrit - President Castle & Cooke • Allan Dobson MD – VP Clinical Practice Development, CFM • Overview of study plan - Rob Califf MD • Overview of -omics study tools – Jessie Tenenbaum PhD • Example of liver project - John McHutchison MD • Community engagement plan - Lloyd Michener MD • Discussion - All • Timeline and next steps - Victoria Christian 

3. NCRC collectively improving human health Farming Practices Food Sciences Nutrition Effective Healthcare Disease Management Health Maintenance Medical Education Public Health Population Health Productivity Global Health

4. In 20 years… • All people in developed nations will have — • An electronic health record • Biological samples • Digitized images • Healthcare will be personalized using an individual’s images, samples and clinical data. • The health of a community will be monitored using aggregate records. • Kannapolis — as hub of the Carolinas — could define this future through a public-private partnership.

5. The MURDOCK Study will … • Build value using assets already in our reach. • Sub-classify major diseases into populations with specific risks and optimal therapy. • Apply new knowledge to the study of community health. • Re-define clinical research using the power of genomics and biomedical informatics. • Re-write the textbook of medicine. Improve human health.

6. The MURDOCK Study will ... • Fuel the financial success of the DHMRI Core Laboratory and Biorepository. • Foster breakthrough collaborations between NCRC schools with diverse and interconnected perspectives and expertise • Quickly increase the visibility and scientific impact of the DHMRI Lab. • Attract the scientific community. • Attract the biotechnology community. • Engage the local population in a high-impact, internationally recognized project. • The modern equivalent of the Framingham Heart Study

7. Current data assets & DHMRI tools:Powerful once-in-a-lifetime value proposition

8. A new era of biomedical research • Novel research technologies have enabled the study of thousands of molecules at a time • Referred to as “high throughput” approach • These novel methods enable ‘-Omics’ scale research

9. What is ‘-Omics’? • The study of the totality of a type of biological data • All genes: Genomics • All transcribed genes: Transcriptomics • All proteins: Proteomics • All metabolites: Metabolomics • Omics scale research has enabled patient profiling at the molecular level

10. Continuum of -Omics Genomics Genes  mRNA  Proteins  Metabolites Transcriptomics Proteomics Metabolomics

11. Genomics and the media

12. Cells of interest Known DNA Isolate mRNA, label Glass slide Reference sample An example: DNA Microarrays Dr. Russ Altman, Stanford Univ.

13. Expt 1 2 3 4 5 6 Gene 1 Gene 2 Gene 3 Gene 4 Gene 5 Gene 6 Gene 7 Gene 8 Gene 9 DNA Microarray visualization: heatmaps Experiment 1 (e.g. Patient X)

14. An opportunity • For the first time, diseases can be defined by molecular fingerprints or profiles • Mechanistic pathways of diseases can be elucidated • Symptomatic descriptors can be replaced by meaningful tools for stratification  These tools will enable truly personalized medicine

15. Medicine today • Drugs are developed to treat all patients with the same clinical diagnosis - “one size fits all” • Many drugs only work in less than half of the patients for which they are prescribed • Over 100,000 people die annually from drug related adverse events - a ‘top 10’ cause of death

16. Cancer Diabetes ‘-Omics’ technologies can help predict treatment response. -Omics Technologies Responder Excercise + Diet A Adverse event Exercise +Diet B Non-responder Exercise +Diet +Medication

17. Combining clinical and molecular data will redefine disease management. • Quantify risks of developing diseases. Apply preventive measures more effectively. • Establish diagnosis earlier.  Prevent disability by treating earlier. • Predict death and disability.  Use healthcare resources strategically.

18. Validate hypotheses prospectively • Apply new knowledge to local community through partnership with local medical community • Improve human health Horizon 2 Horizon 1.5 • Engage community • Build community registry Horizon 1 • Use assets on hand to generate molecular data • Generate hypotheses by leveraging bioinformatics Three horizons of MURDOCK Study

19. Outcomes of Hepatitis C virus infection Spontaneous clearance (~25%) Chronic infection Treatment Responders Non-responders (>50%) Hepatic FibrosisSteatosisInsulin resistanceDyslipidemia Increased risk of diabetes Unknown consequences

20. Reclassification of HCV disease • Use genomic technologies to subset patients based on their molecular signature • This signature may become a useful marker of: • Treatment response – therapeutic decision-making • Development of fibrosis or steatosis - non-invasive diagnostic alternative • Insulin resistance or dyslipidemia – may have broader relevance for diagnosing and treating non-HCV patients with these conditions

21. Selection of biomarkers for HCV profiling • Standard available assays: inflammatory, lipid metabolism, glucose metabolism, etc. • Novel protein biomarkers – proteomic discovery • Novel protein biomarkers – genetic approaches

22. Novel biomarker discovery strategies • Genetic discovery • Proteomic discovery • Open discovery platform allows for discovery of novel protein biomarkers (host or viral-specific) that may be associated with treatment response and/or HCV genotype • These biomarkers, along with others, will be typed in a large HCV patient cohort • Unbiased discovery platform tests for association of >500,000 gene variants with HCV outcomes and/or quantitative traits (protein markers) • Genes discovered in this way may become useful protein biomarkers or remain as DNA diagnostics

23. Molecular profiling of HCV patients Tx response Fibrosis Steatosis Diabetes Dyslipidemia • Type large number of biomarkers in ~1000 chronic HCV patients from the Duke Hepatology Research Clinic cohort • Correlate molecular signatures with outcomes in HCV patients and similar traits in non-HCV patients • Use statistical modeling to subset HCV patients based on common biomarker signatures

24. Deploy assets for maximum potential benefit to communities. • Uncover new knowledge in diseases that afflict large patient populations. • Epidemics — obesity, diabetes, depressionDiseases of aging — arthritis, dementia • Use this new knowledge in clinical practice. • Make decisions based on breakthroughs in the individualized treatment of breast cancer and depression • Make new discoveries with commercial potential. • Contributory drug-able pathwaysNovel biomarkers

25. Challenge of biomedical informatics:Turning data into knowledge Knowledge DATA

26. Groundwork for successful community engagement • Transparency of efforts • Advice from appropriate community groups • Questions to ask: how are citizens best reached? where do they gather? how do they prefer to receive information? • Preparation of documents and study plans in iterative process with feedback from community • Communication strategy based on community groups’ advice • Formation of Community Advisory Group

27. Possible modes of engagement • Interactive website • Community surveys • Posters, brochures, other written materials • Educational presence at community events (e.g., health fairs) • Targeted cable television programs • Local physician and patient with 15 min on specific topic (living with osteoarthritis, managing diabetes, etc.) • Videos for doctors’ offices • Interactive kiosks • Open communication with local media outlets • Meetings with community groups (health related and non-health related)

28. Community Registry Accelerating Discovery: Finding • Suppose we identify a Biomarker that distinguishes a sub-population of patients correlating with new insulin resistance • If this is true, we’d treat differently to achieve better patient outcomes • We need to test this to assure improved patient outcomes • Positive result would drive creation of the diagnostic and care guidelines. Application Confirm Translation into Practice

29. Community Registry • Allow patients to declare interest in research participation • Store information • People interested in research participation • Summary level health information • Permission to contact • Primary physician • Accelerate discovery by having this information when discoveries are ready to be tested

30. Summary • We are committed to building transparent, open partnership with local community. • We will seek to maximize opportunities to have meaningful impact on local human health and local economy. • The MURDOCK Study offers an opportunity for the local community to have global impact by generating knowledge that improves health and alleviates disease.