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Towards a Platform for Global Health


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Keynote presentation at the Global Alliance for Genomic Health (GA4GH) meeting in Vancouver, Canada on November 18, 2016.

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Towards a Platform for Global Health

  1. 1. Towards a Platform for Global Health Philip E. Bourne, PhD, FACMI Associate Director for Data Science The National Institutes of Health
  2. 2. Bias • Worked on long standing data resources – PDB, IEDB • Systems pharmacology with emphasis on the role of molecular structure • AVC for innovation and industrial alliances at UCSD • Chief data officer for the National Institutes of Health • Open science zealot psychological-research-407/biases-in-experimental-design-validity-reliability-and-other-issues-132-12667/images/research- bias/
  3. 3. Before we look at platforms .. and thinking as a funder .. I want to describe an emergent effort that may have some valuable lessons for GA4GH going forward in their relationship to funders (something that should not be ignored) Preprints
  4. 4. What is a preprint? • A complete manuscript/research report shared prior to/instead of publication – in ArXiv 80% of preprints get published at a later date • Not formally peer reviewed but may be commented on by the community – depends on the preprint service
  5. 5. Preprints – Long the realm of physicists are gaining traction in the life sciences  Speeds up dissemination  Record of priority  More informed grant review  Negative data ✘ Fear of scooping ✘ Career disadvantage ✘ Inability to publish ✘ Quality: Moderation only; no peer review
  6. 6. Status • ASAPbio to issue RFI for what a central preprint service should look like • ~15 global funders (government and foundations) – the coalition of the willing – defined basic principles to support such a service • Collectively expect to fund ASAPbio to award a contract to build the system • While sustainability models should be sought, funders anticipate funding a central service for 5-10 years at least Endpoint • Accelerated scientific outcomes through a human and machine accessible corpus of open knowledge accessible to all
  7. 7. How should GA4GH view this development? …
  8. 8. Perceived critical mission Strong leadership Leading scientists engaged Significant community support ✖Obvious endpoint/singular message ✖Funders - coalition of the willing ✖Identified champions within each funding body
  9. 9. Obvious endpoint/singular message Possible Touchpoint to Funders: “The partners in the Global Alliance are working together to create a common framework of harmonized approaches to enable the responsible, voluntary, and secure sharing of genomic and clinical data.”
  10. 10. Funders too are increasingly looking at moving from pipes to platforms (aka common framework).. What would such a platform look-like? … Sangeet Paul Chowdry
  11. 11. Making Biomedical Research More Like Airbnb Philip E. Bourne, PhD, FACMI Associate Director for Data Science The National Institutes of Health
  12. 12. I am not crazy, hear me out • Airbnb is a platform that supports a trusted relationship between consumer (renter) and supplier (host) • The platform focuses on maximizing the exchange of services between supplier and consumer and maximizing the amount of trust associated with a given stakeholder • It seems to be working: • 60 million users searching 2 million listings in 192 countries • Average of 500,000 stays per night. • Evaluation of US $25bn
  13. 13. Is not biomedical research the same?
  14. 14. Why a comparison to Airbnb is not fair • Airbnb was born digital • The exchange of services on Airbnb are simple compared to what is required of a platform to support biomedical research Nevertheless there is much to be learnt
  15. 15. Consider why this appeals to funders
  16. 16. Author Submission via the Web Depositor Submission via the Web Syntax Checking Syntax Checking Review by Scientists & Editors Review by Annotators Corrections by Author Corrections by Depositor Publish – Web Accessible Release – Web Accessible Similar Processes Lead to Similar Resources Bourne, PLoS Comp. Biol. 2005 1(3) e34de Waard Nature Proceedings 2010 10101/npre.2010.4742.1
  17. 17. What is different is the perceived value of each to the research enterprise. That value difference is diminishing in part because of openness, accessibility, policy, governance, increased data reuse and lets not forget other forms of madness…
  18. 18. The Analog-Digital Data Knowledge Cycle P.E. Bourne, 2016, There is No Intelligent Life Down There
  19. 19. Platforms - the situation today
  20. 20. In summary there is not currently a widely adopted single platform for the exchange of services in biomedical research. Either there is a platform per service or no platform at all. Why have we not done better and what are the impediments today?
  21. 21. Impediments to a biomedical platform • Current work practices by all stakeholders • Entrenched business models • Size of the undertaking aka resources needed • Trust • Incentives to use the platform employee-innovation/#8bdbaa811133
  22. 22. The NIH through the Big Data to Knowledge (BD2K) is experimenting with a platform, keeping in mind the need to overcome these impediments Enter The Commons
  23. 23. Commons – Initial focus is on integrating two layers of the scholarly workflow
  24. 24. Commons topology Compute Platform: Cloud or HPC Services: APIs, Containers, Indexing, Software: Services & Tools scientific analysis tools/workflows Data “Reference” Data Sets User defined data DigitalObjectCompliance App store/User Interface PaaS SaaS IaaS
  25. 25. Commons compliance • Treat products of research – data, methods, papers etc. as digital objects • These digital objects exist in a shared virtual space • Digital object compliance through FAIR principles: • Findable • Accessible (and usable) • Interoperable • Reusable The FAIR Principles
  26. 26. NIH + Community defined data sets possible FOAs and CCM BD2K Centers, MODS, HMP & Interoperability Supplements Cloud credits model (CCM) BioCADDIE/Other Indexing NCI & NIAID Cloud Pilots Compute Platform: Cloud or HPC Services: APIs, Containers, Indexing, Software: Services & Tools scientific analysis tools/workflows Data “Reference” Data Sets User defined data DigitalObjectCompliance App store/User Interface Mapping current BD2K activities to the commons topology
  27. 27. Prediction – funder activities are about to accelerate and here lies the opportunity…. What are the funder incentives? ….
  28. 28. Incentives • Airbnb • Monetize unutilized space • Ease of use • New vacation experience • Commons • Need to improve rigor and reproducibility • Productivity • Sustainability • Education and training • Opportunity to undertake elastic compute on large complex data
  29. 29. NIH committed to (and would hope other funders will join) • The Commons and the FAIR principles • Pilots that test the feasibility of the platform for larger scale development/adoption • Provision of two large complex data sets in the Commons – TOPMed and GTEx are obvious choices, others may surface • Use cases that illustrate the feasibility and scientific value of: • Access to a single data source • Interoperability across data sources
  30. 30. Summary • NIH has endorsed the Commons and the FAIR principles • The Commons is the beginnings of a platform from which to conduct biomedical research • Over the next 1-2 years we are conducting pilots to evaluate the feasibility of the Commons • If feasible the intent is to expand into additional layers of the scholarly research lifecycle • The global reach of GA4GH can foster a coalition of the willing • Commons applications are an opportunity to provide a singular message
  31. 31. “I really admire Airbnb as a pioneer of the sharing economy and for building community. They've found an elegant way to help hosts make more money and for guests to have authentic experiences. It brings those people together in a unique way. “ Logan Green
  32. 32. “The Commons is an effort at creating a sharing economy and for building community. We hope for a more cost effective and productive research environment while bringing people together in a unique way. “ Phil Bourne
  33. 33. Speaking of a shared economy… You are invited to contribute to a shared document that describes this concept.. You will be acknowledged and the document put forward for NIH clearance to be blogged/preprinted/published….
  34. 34. Acknowledgements • ADDS Office: Vivien Bonazzi, Jennie Larkin, Michelle Dunn, Mark Guyer, Allen Dearry, Sonynka Ngosso, Tonya Scott, Lisa Dunneback, Vivek Navale (CIT/ADDS) • NCBI: George Komatsoulis • NHGRI: Valentina di Francesco • NIGMS: Susan Gregurick • CIT: Debbie Sinmao, Andrea Norris • NIH Common Fund: Jim Anderson , Betsy Wilder, Leslie Derr • NCI Cloud Pilots/ GDC: Warren Kibbe, Tony Kerlavage, Tanja Davidsen • Commons Reference Data Set Working Group: Weiniu Gan (HL), Ajay Pillai (HG), Elaine Ayres, (BITRIS), Sean Davis (NCI), Vinay Pai (NIBIB), Maria Giovanni (AI), Leslie Derr (CF), Claire Schulkey (AI) • RIWG Core Team: Ron Margolis (DK), Ian Fore, (NCI), Alison Yao (AI), Claire Schulkey (AI), Eric Choi (AI) • OSP: Dina Paltoo, Kris Langlais, Erin Luetkemeier, Agnes Rooke,
  35. 35. NIH… Turning Discovery Into Health