SILS 2015 - Connecting Precision Medicine to Precision Wellness

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By: Joel Dudley, Mount Sinai School of Medicine
At Sherbrooke International Life Sciences Summit - 2nd edition | September 28/29/30 2015
www.sils-sherbrooke.com

Publié dans : Santé & Médecine
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SILS 2015 - Connecting Precision Medicine to Precision Wellness

  1. 1. Connecting Precision Medicine to Precision Wellness towards a systems understanding of health and disease Joel Dudley, PhD Director of Biomedical Informatics & Associate Professor of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai Icahn School of Medicine at Mount Sinai @IcahnInstitute
  2. 2. Mount Sinai Health System >6,000 Physicians 7 Member hospital campuses >3,500 >3,100,000 Patient visits Hospital beds
  3. 3. “The future is already here — it's just not very evenly distributed”. - William Gibson
  4. 4. There are rarely smoking guns in human health
  5. 5. There are rarely smoking guns in human health
  6. 6. No such thing as a “simple” disease Cutting GR. Nature Reviews Genetics. (2014) doi:10.1038/nrg3849 Woody Guthrie
  7. 7. Complex molecular networks underlie human physiology
  8. 8. We must embrace complexity to fully understand patient physiology and disease “A complex adaptive system has three characteristics. The first is that the system consists of a number of heterogeneous agents, and each of those agents makes decisions about how to behave. The most important dimension here is that those decisions will evolve over time. The second characteristic is that the agents interact with one another. That interaction leads to the third—something that scientists call emergence: In a very real way, the whole becomes greater than the sum of the parts. The key issue is that you can’t really understand the whole system by simply looking at its individual parts”. - Michael J. Mauboussin (investment banker)
  9. 9. Icahn Institute for Genomics and Multiscale Biology
  10. 10. Being masters of really big data is now critical for biomedical research (TB→PB→EB→ZB) Organisms Tissues Single cells Single cell, real-time, continuous?
  11. 11. Biology’s atom smasher moment— We can measure more than we know
  12. 12. Redefining the system of human disease with data ~300 Diseases and Conditions 20k+ Genes Blue: gene goes down in disease Yellow: gene goes up in disease
  13. 13. Redefining the system of human disease with data Suthram S, Dudley J et al. Network-based elucidation of human disease similarities reveals common functional modules enriched for pluripotent drug targets. PLoS Computational Biology (2010) Figure 2. Significant disease-disease similarities. (A)Hierarchical clustering of thediseasecorrelations.Thedistancebetweentwo disease defined to be(1-correlation coefficient) of thetwo diseases. Thetree wasconstructed using theaverage method of hierarchical clustering. Th line corresponds to a p-value of 0.01 and FDRof 10.37%and, disease correlations below this line are considered significant. The different c
  14. 14. Unexpected connection: anticonvulsant drug treats inflammatory bowel disease • TNBS chemically induced rat model of IBD • Animals treated with 80mg/kg topiramate oral after sensitization • Prednisolone positive control (approved for IBD in humans) Dudley, J. T., Sirota, M., et al. (2011). Computational Repositioning of the Anticonvulsant Topiramate for Inflammatory Bowel Disease. Science Translational Medicine, 3(96).
  15. 15. Control Imipramine Unexpected connection: antipsychotic drug treats small cell lung cancer p53/Rb/p130 triple knockout model of SCLC Mice dosed after tumor formation
  16. 16. Kidd BA, Wroblewska A, Agudo J, Merad M, Brown BD, Dudley JT. Systematic integrative analysis of immune pharmacology. (2015) Nature Biotechnology. in press. How do approved drugs modulate networks in immune cells?
  17. 17. Antifungal activates neutrophil migration Drug A Drug B Drug A Drug A Drug B Drug A Drug B Drug A Drug B Kidd BA, Wroblewska A, Agudo J, Merad M, Brown BD, Dudley JT. Systematic integrative analysis of immune pharmacology. (2015) Nature Biotechnology. in press.
  18. 18. Antifungal activates neutrophil migration Drug A Drug B Drug A Drug A Drug B Drug A Drug B Drug A Drug B Kidd BA, Wroblewska A, Agudo J, Merad M, Brown BD, Dudley JT. Systematic integrative analysis of immune pharmacology. (2015) Nature Biotechnology. in press.
  19. 19. Immunemod score predicts immune cell perturbations in patient populations Kidd BA, Wroblewska A, Agudo J, Merad M, Brown BD, Dudley JT. Systematic integrative analysis of immune pharmacology. (2015) Nature Biotechnology. in press.
  20. 20. Understanding the multiscale complexity of patient populations = Genomic Environment Clinical
  21. 21. Capturing rich multi scale data on patients through the Mount Sinai Biobank
  22. 22. Image credit: Li Li (ISMMS)
  23. 23. Type 2, Type 3, and Type 4 diabetes?
  24. 24. 200 Data Feeds 5Gb Data/lap
  25. 25. 300 Sensors 3,000 Variables/0.1 sec >200Gb Data/day
  26. 26. We are on the crest of a tsunami in consumer sensor technologies
  27. 27. Printable tattoo biosensor
  28. 28. Genome function is very context dependent • eQTL • What? • Where? • When?
  29. 29. Genome function is all about context
  30. 30. Genome function is all about context
  31. 31. 1. Drug A 2. Drug B 3. Drug C 4. Tolfenamic Acid 5. Drug D 6. Drug E 7. … SP1 NDMN Network Model Drugs perturbing SP1 sub- network towards healthy prioritized by network activity The network as the target
  32. 32. Web-scale deep computing as the future of medicine and research http://www.bbc.com/news/technology-18595351
  33. 33. Web-scale deep computing as the future of medicine and research Xiong et al. Science 9 January 2015
  34. 34. Consumer health tools as a driver of data-driven healthcare Where will most of the health data be in 5-10 years?
  35. 35. We can embrace digital health and sensors to map the human phoneme and envirome
  36. 36. Electronic Consent and Patient Engagement
  37. 37. Electronic Consent and Patient Engagement
  38. 38. A Learning Digital Health Platform for Chronic Lung Disease
  39. 39. A Learning Digital Health Platform for Chronic Lung Disease
  40. 40. We need to collect “long” dynamic data for Precision Wellness
  41. 41. In the future you will have coordinates instead of a diagnosis Topol EJ. Individualized Medicine from Prewomb to Tomb Cell 157, March 27, 2014
  42. 42. The emergence of science- and data-driven wellness info@precisionwellness.org
  43. 43. The emergence of science- and data-driven wellness info@precisionwellness.org Digital Health Molecular Profiling Data Science Clinical Medicine The Harris Center for Precision Wellness www.precisionwellness.org
  44. 44. “The future is already here — it's just not very evenly distributed”. - William Gibson
  45. 45. Email: joel.dudley@mssm.edu Twitter: @jdudley Web: dudleylab.org precisionwellness.org Icahn School of Medicine at Mount Sinai Thank you for your attention!

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