Notice Number: NOT-EB-16-008
Release Date: July 5, 2016
National Institutes of Health (NIH)
National Cancer Institute (NCI)
National Eye Institute (NEI)
National Heart, Lung, and Blood Institute (NHLBI)
National Human Genome Research Institute (NHGRI)
National Institute on Aging (NIA)
National Institute of Allergy and Infectious Diseases (NIAID)
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)
National Institute on Deafness and Other Communication Disorders (NIDCD)
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
National Institute on Drug Abuse (NIDA)
National Institute of Environmental Health Sciences (NIEHS)
National Institute of Mental Health (NIMH)
National Institute of Neurological Disorders and Stroke (NINDS)
National Institute of Nursing Research (NINR)
National Library of Medicine (NLM)
National Center for Complementary and Integrative Health (NCCIH)
National Center for Advancing Translational Sciences (NCATS)
Division of Program Coordination, Planning and Strategic Initiatives, Office of Research Infrastructure Programs (ORIP)
Office of Strategic Coordination (Common Fund)
Biomedical research is rapidly becoming more data-intensive as investigators are generating and using increasingly large, complex, multidimensional, and diverse datasets. This era of big data in biomedical research taxes the ability of many researchers to release, locate, analyze, and interact with these data and associated software due to the lack of tools, accessibility, and training. In response to these new challenges in biomedical research, and in response to the recommendations of the Data and Informatics Working Group (DIWG) of the Advisory Committee to the NIH Director (http://acd.od.nih.gov/diwg.htm), NIH has launched the trans-NIH Big Data to Knowledge Initiative (https://datascience.nih.gov/bd2k).
The purpose of this Notice is to announce that the NIH, through the Big Data to Knowledge (BD2K) Initiative, is collaborating on a multi-agency funding opportunity, the Quantitative Approaches to Biomedical Big Data (QuBBD) initiative [http://nsf.gov/funding/pgm_summ.jsp?pims_id=505292]
Recent advances in medical and healthcare technologies are creating a paradigm shift in how medical practitioners and biomedical researchers approach the diagnosis, prevention, and treatment of diseases. New imaging technologies, advances in genetic testing, and innovations in wearable and/or ambient sensors are allowing researchers to predict health outcomes and develop personalized treatments or interventions.
Coupled with the rapid growth in computing and infrastructure, researchers now have the ability to collect, store, and analyze vast amounts of health- and disease-related data from biological, biomedical, behavioral, social, environmental, and clinical studies. The explosion in the availability of biomedical big data from disparate sources, and the complex data structures including images, networks, and graphs, pose significant challenges in terms of visualization, modeling, and analysis.
While there have been some encouraging developments related to foundational mathematical, statistical, and computational approaches for big data challenges over the past decade, there have been relatively few opportunities for collaboration on challenges related to biomedical data science.
The National Science Foundation (NSF) and the National Institutes of Health (NIH) recognize that fundamental questions in basic, clinical, and translational research could benefit greatly from multidisciplinary approaches that involve experts in quantitative disciplines such as mathematics, statistics, and computer science.
The Quantitative Approaches to Biomedical Big Data Program is designed to support research that addresses important application areas at the intersection of the biomedical and data sciences by encouraging inter- and multi-disciplinary collaborations that focus on innovative and transformative approaches to address these challenges.
The NIH expects to fund projects with durations of up to 3 years. Award sizes are expected to be less than $200,000 (direct costs) per year. All awards made under this Funding Opportunity Announcement (FOA) by NIH will be as grants or cooperative agreements, as determined by the supporting agency.
Application Preparation and Submission Instructions
Applications submitted in response to this (FOA) should be prepared and submitted in accordance with the general guidelines contained in the NSF Grant Proposal Guide (GPG). Applications must be submitted to the NSF, not to the NIH. The complete text of the GPG is available electronically on the NSF website at http://www.nsf.gov/publications/pub_summ.jsp?ods_key=gpg. Applicants are reminded to identify the NSF program announcement number in the program announcement block on the NSF Cover Sheet for Proposal to the National Science Foundation. Compliance with this announcement is critical to determining the relevant application processing guidelines. Failure to submit this information may delay processing.
Inclusion of voluntary committed cost sharing is prohibited. For NIH, indirect costs on foreign subawards/subcontracts will be limited to 8 percent.
For those applications that are selected for potential funding by the Big Data to Knowledge (BD2K) Program, the PD/PI will be required to submit the application in an NIH-approved format. PD/PIs invited to submit to NIH will receive further information on submission procedures from NIH. An applicant will not be allowed to increase the proposed total budget or change the scientific content of the application in the submission to the NIH as an NIH application. These NIH applications will be entered into the NIH IMPAC II system. The results of the review will be presented to the involved Institutes' National Advisory Councils for the second level of review. Subsequent to the Council reviews, NIH will make final funding determinations and selected awards will be made.
Subsequent grant administration procedures for NIH awardees, including those related to New and Early Stage Investigators (http://www.niaid.nih.gov/researchfunding/grant/Pages/aag.aspx), will be in accordance with the policies of NIH. Applications selected for NIH funding will use the NIH funding mechanisms.
For information purposes, NIH PD/PIs may wish to consult the NIAID web site, "All about Grants," which provides excellent generic information about all aspects of NIH grantsmanship (http://www.niaid.nih.gov/researchfunding/grant/Pages/aag.aspx).
Please direct all inquiries to:
Vinay M. Pai
National Institute of Biomedical Imaging and Bioengineering (NIBIB)