Multimodal AI to Accelerate Precision Medicine for Type 1 Diabetes (U01- Clinical Trials Not Allowed)
Forecasted Federal grant Posted
- Opportunity number
- RFA-DK-28-116
- Agency
-
National Institutes of Health
Department of Health and Human Services
- Applications expected due
- Award size
- Not on record
Opportunity facts
- Expected posting
- Assistance listings
- Funding instrument
- Cooperative Agreement
- Category
-
- Health
- Eligible applicants
-
- Small Businesses
- Tribal Organizations (Not Federally Recognized)
- Public or Indian Housing Auth.
- 501(c)(3) Nonprofits
- Other
- For Profit Organizations
- City/Township Governments
- Non-501(c)(3) Nonprofits
- Higher Education Inst. (Public)
- State Governments
- Special District Governments
- Higher Education Inst. (Private)
- County Governments
- Tribal Governments (Federally Recognized)
- Independent School Districts
- Points of contact
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- Albert Hwa niddk_dem@nih.gov
Opportunity details come from Grants.gov. Updated .
About this opportunity
The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) is soliciting cooperative agreement applications to fund multimodal AI research integrating Type 1 diabetes datasets across multiple consortia; clinical trials are not allowed. The opportunity is assigned to CFDA 93.847 (Diabetes, Digestive, and Kidney Diseases Extramural Research). No application deadline appears in the source material.
Eligible applicants include small businesses, higher education institutions (public and private), 501(c)(3) and non-501(c)(3) nonprofits, state and county governments, city and township governments, tribal governments (federally recognized and not federally recognized), tribal organizations, independent school districts, public or Indian housing authorities, special district governments, for-profit organizations, eligible federal agencies, U.S. territories or possessions, faith-based or community-based organizations, regional organizations, and non-domestic entities.
The project will combine multimodal human pancreas and clinical datasets collected across prior NIDDK consortia to understand how biological processes interact in Type 1 diabetes development and progression. Research objectives include identifying new biomarkers, characterizing different forms and stages of disease, and informing prevention, intervention, and treatment strategies. The project will develop and validate advanced multimodal AI models and AI-enabled research workflows to integrate complementary datasets spanning tissues, disease stages, and biological levels. Work is milestone-driven and coordinates across existing consortium resources.
Evaluation will assess scientific merit and significance, technical adequacy of experimental design, investigator competency, adequacy of facilities and resources, budget necessity relative to proposed work, and relevance to program objectives. Standard NIH peer review processes apply, with initial scientific review by an appropriate panel followed by advisory council consideration and merit-based competition for available funds.
Forecast synopsis
Type 1 diabetes (T1D) is a complex disease involving interactions among many different cell types, tissues, organs and biological processes. Genetics, the environment, and lifestyle all play a role in disease development and progression. Over the past two decades, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) has supported major T1D research consortia covering basic, translational, and clinical research. Each consortium has focused on different aspects of T1D, such as specific organs, stages of disease or clinical outcomes. Together, these consortia have collected large longitudinal and multimodal datasets using standardized protocols and coordinated studies. While individual consortia have improved our understanding of specific areas, combining their work offers a rare opportunity to see how different biological processes interact to drive T1D development and progression. This integrated view can answer fundamental questions about T1D biology that cannot be answered using individual datasets or studies alone.
Recent advances in artificial intelligence (AI) now make it possible to integrate these complementary datasets and study T1D across various tissues, disease stages, and biological levels. Building on these resources, NIDDK will support a coordinated, milestone-driven research project to answer fundamental questions about T1D biology and accelerate the development of personalized medicine.
The project will combine multimodal human pancreas and clinical datasets to better understand how biological processes interact as T1D develops and progresses. The research will generate new insights into T1D biology, help us understand the different forms and stages of T1D, identify biomarkers, and inform new approaches for disease prevention, intervention, and treatment. To support the research, the project will develop and test advanced multimodal AI models. It will also develop AI-enabled research workflows, new methods to integrate data, and privacy-preserving synthetic datasets.
Eligibility
Other Eligible ApplicantsIndian/Native American Tribal Governments (Other than Federally Recognized);Eligible Agencies of the Federal Government;U.S. Territory or Possession;Faith-based or Community-based Organizations;Regional Organizations;Non-domestic (non-U.S.) Entities (Foreign Institutions).
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