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Forecasted

Single Source for Establishing Pilot/Opportunity program for AI Models to Accelerate Diabetes Research (U24- Clinical Trials not allowed)

Federal funding opportunity RFA-DK-26-314 from National Institutes of Health.

View forecast on Grants.gov →Forecasted — not yet open

Posted
September 25, 2025
Closes
See announcement
Cost sharing
No
Instrument
Cooperative Agreement
Assistance listing
93.847
Category
Health

Program funding history

Awards made under Assistance Listing 93.847 across FY2024–FY2026, from public federal spending records.

FY2024 obligated
$1.9B
FY2025 obligated
$2B
FY2026 (to date) obligated
$1B
Awards in window
8,079

Top recipients: Regents of the University of Michigan, Trustees of the University of Pennsylvania, the, Washington University, the, University of Pittsburgh - of the Commonwealth System of Higher Education, Regents of the University of California, San Francisco, the

Source: USAspending.gov · refreshed July 2026

Synopsis

Diabetes has become a major public health challenge due to its high prevalence and chronic nature, with many individuals managing the condition for decades. One major challenge in diabetes is the enormous heterogeneity associated with the disease, which necessitates personalized approaches to its prevention, diagnosis, treatment, and prognosis. To address this, the research field has generated a large amount of complex data, and has accumulated vast prior knowledge about the disease. These data and prior knowledge contain critical, but mostly hidden, information relevant to solving this challenge. However, major hurdles exist in integrating them and extracting predictive signals, including a lack of data science expertise in the diabetes research field and the absence of diabetes-specific data science and AI expert systems, models, and tools. This initiative proposes to address these issues by establishing a pilot funding program that leverages the emerging opportunities from recent data science and AI advances. It will recruit multidisciplinary teams that include both diabetes and data science experts, to (1) develop AI foundation models for diabetes; (2) validate the models with top research questions in diabetes heterogeneity; (3) disseminate the models and engagement the community for further development, validation and application, and; (4) develop use cases that demonstrate models’ potential in accelerating the tempo of research. The expected outcomes include the integration of new AI experts into the diabetes research workforce, the creation of AI models that the average diabetes researcher can use, and informative use cases demonstrating the models' potential.

All applications will be peer-reviewed and only meritorious applications will be considered for funding. 

Who can apply

NIDDK requests a Single Source competition for the Pilot/Opportunity program at the University of California, San Diego for AI Models to Accelerate Diabetes Research to the dkNET.

How to apply

Applications go through the official government listing. Grants Radar links you straight to the source.

View on Grants.gov

Agency contact: Xujing Wang, Ph.D. · xujing.wang@nih.gov · 301-451-2862

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