qubbd program innovation lab and foa - data scienceinnovation lab • one week, facilitated,...
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QuBBD Program Innovation Lab and FOA
NIH: Vinay Pai, Jennifer Couch, Gabriel Rosenfeld, and Michelle Dunn
NSF: Nandini Kannan
BD2K Multi-Council Working Group January 11, 2016
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NIH/NSF QuBBD Program• Goal: to nurture new interdisciplinary teams (biomed from NIH and
math/stats/cs from NSF) to address data science roadblocks
• Components:– Series of Innovation Labs to build new teams– Follow up meetings to nurture new teams– Planning grants to support the collaborative research by new teams
• Purpose of Today’s Presentation:– Update on pilot within QuBBD program– Proposed next steps
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Rationale for the QuBBD Program• It can be challenging to develop interdisciplinary collaborations
between biomedical and quantitative researchers, especially at early stage of career
• New teams can lead to innovative science that couldn’t be solved otherwise
• Innovation Labs can break through initial barriers, and subsequent seed funding can support the groundwork that can lead to initiation of a research program to successfully compete for continued funding
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Innovation Lab• One week, facilitated, interactive workshop
– For generation of new interdisciplinary teams– For ideation of an innovative research program – Through nurturing from mentors who are experts in their
respective fields
• New teams form of early-stage biomedical and quantitative researchers– Biomed come with problems (high-need, high-impact data science)– Quant brings methods and the desire to develop innovative
solutions
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FY15 Innovation Lab• Addressed data science roadblocks in Precision Medicine
• Catalyzed new interdisciplinary teams– Teams formed around biomedical scientist with a partially-formulated
problem – Data scientists brought knowledge of many tools, and the ability to
adapt/extend
• Teams wrote applications for small planning grants – Applications received from Innovation lab teams and public– 10 applications funded after NSF review– NIH/BD2K and NSF partnered to fund these projects
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Lessons Learned from FY15 LabObserved Problem Identified Cause Potential Fix
Gaps in expertiseDiffuse focus and limited # participants
Scoping workshop to
refine problem space
Some teams had difficulty selecting
problems
Participants not asked to bring
identified problems
2-track process: biomed brings
problems, quant brings tools
Confusion about new teams
Definitions not given in “Dear
Colleague Letter”
FOA will have clear definitions
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SUMMARY: Innovation Lab Successful
Proposal: Hold annual Innovation Labs in FY16-18, with the first Lab having an mHealth focus, and issue a multi-year FOA for planning grants
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FOA Concept• Joint NSF/NIH FOA/solicitation that provides a funding
opportunity open to Innovation Lab participants and the general public
• Goal: To foster new interdisciplinary teams– Early stage investigators from biomedical science and data
science– To address data science roadblocks that are impeding
progress in a biomedical research problem• Science: Projects to develop novel or significantly adapted
computational and quantitative approaches, methods, or tools
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Timeline of Key StepsInnovation Lab
participantsExtramural community
Scoping workshop
February 2016
FOA release
June 2016
Innovation Lab
July 2016
Receipt and Review
Oct 2016
Funding
Feb 2017
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Data Science at NIH
Data Science at NIH https://datascience.nih.gov/adds [email protected]@NIH_BD2K #BD2K, #BigData