Multimodal AI to Accelerate Precision Medicine for Type 1 Diabetes (U01- Clinical Trials Not Allowed)

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.

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).

The major elements in evaluating proposals include assessments of: (1) The scientific merit and general significance of the proposed study and its objectives; (2) the technical adequacy of the experimental design and approach; (3) the competency of the proposed investigator or group to successfully pursue the project; (4) the adequacy of the available and proposed facilities and resources; (5) the necessity of the budget components requested in relation to the proposed project; and (6) the relevance and importance to announced program objectives. The following criteria will be used in considering the scientific and technical merit of SBIR/STTR Phase I grant applications: (1) The soundness and technical merit of the proposed approach; (2) the qualifications of the proposed principal investigator, supporting staff, and consultants; (3) the technological innovation of the proposed research; (4) the potential of the proposed research for commercial application; (5) the appropriateness of the budget requested; (6) the adequacy and suitability of the facilities and research environment; and (7) where applicable, the adequacy of assurances detailing the proposed means for (a) safeguarding human or animal subjects, and/or (b) protecting against or minimizing any adverse effect on the environment. Phase II grant applications will be reviewed based upon the following criteria: (1) The degree to which the Phase I objectives were met and feasibility demonstrated; (2) the scientific...

This program has no statutory formula. Matching requirements are not applicable to this assistance listing. MOE requirements are not applicable to this assistance listing.

Not Applicable.