1. BD4BC An Introduction George W. Sledge, MD Professor of Medicine Stanford University

2. Three Data Revolutions “Omics” Electronic Health Records Internet of Things “A total of 2.5 quintillion terabytes of data were generated every day in 2012 alone, and it is estimated that as much data is now generated in just two days as was created from the dawn of civilization until 2003.” Why Health Care May Finally Be Ready for Big Data Nilay D. Shah and Jyotishman Pathak, Harvard Business Review, 12/3/14

3. The Human Genome Host and Cancer

6. TCGA: 507 Patients in 2012 Nature, 2012

7. Fig 1. Growth of DNA sequencing. Stephens ZD, Lee SY, Faghri F, Campbell RH, Zhai C, et al. (2015) Big Data: Astronomical or Genomical?. PLoS Biol 13(7): e1002195. doi:10.1371/journal.pbio.1002195 http://127.0.0.1:8081/plosbiology/article?id=info:doi/10.1371/journal.pbio.1002195 1 ZB = 1000 7 bytes = 10 21 bytes

8. Human “GIS” Eric Topol “The Patient will see you now”

9. Electronic Health Records

11. Objects Connected to Objects via the Internet

12. The IoT is Exploding

13. “With enough data and the ability to crunch it, virtually any challenge facing humanity today can be solved.” Eric Schmidt et al, How Google Works, 2014

14. Prof Atul Butte (Genomic Medicine, Stanford) at TEDMED 2012 “Who needs the scientific method? Vast stores of available data (…) are simply waiting for the right questions.”

16. The Present Reality EHR, Omics and IoT unconnected Doctors dislike their EHR systems Doctors can’t use genomic data Clinical decision support: your partner Clinical trials: difficult to access Patients: only partially empowered Care is expensive, ineffective and unchanged

17. Physician Satisfaction With EHRs: American College of Physicians Survey

18. RAND/AMA Physician Satisfaction Survey (2013)

20. The future Healthcare is a seamless web Hyper-connected Big Data systems EHR is the doctor’s best friend Genomics universal and comprehensible Effective, available clinical decision support Clinical trials available to all Patients empowered and active participants Research makes increasing use of Big Data Healthcare works: fewer women die of BC

21. How Do We Get There From Here?

22. Who is at BD4BC? Patient Advocates Clinical genetics/Genomics Bioiformaticians/Health IT Bioethicists Health Quality and Learning Health Systems Breast cancer physicians Cancer Epidemiologists

23. How BD4BC Will Work Framing lectures Break-Out Working Groups – Interactive – Self-selected – Moderated

24. Working Group Session 1 From Bits to Biology: Accelerating Breast Cancer Research via Big Data Moderator: Gordon Mills Risky Business: Informatics and Risk Modeling for Breast Cancer Moderator: Elad Gil EHRs and Analytics: Improving the Quality and Consistency of Patient Care Moderator: Mia Levy

25. Working Group Session 2 APIs, Platforms, and Open Data: the Value of Sharing Moderator: Joe Gray One Size Does Not Fit All: Data Mining for Better Breast Cancer Outcomes Moderator: Karen Gelmon EHRs and Analytics: Improving the Quality and Consistency of Patient Care Moderator: Mia Levy

26. What Do We Want from BD4BC? Increase interactions Generate new directions Assist Komen in Navigating Big Data Generate a White Paper

27. Thank You All Participants: for Attending The Rockefeller Institute: for hosting us Komen and the Robertson Foundation: for supporting the meeting The Organizing Committee The Komen Staff

28. “The future is already here — it's just not evenly distributed.” William Gibson

29. Slide courtesy of Deniz Kural, Seven Bridges Genomics