New Generation of Glucose Control Technologies Incorporating AI/ML Tools/Strategies (R01 - Clinical Trial Optional)

The National Institutes of Health, through the National Institute of Diabetes and Digestive and Kidney Diseases, released the funding opportunity titled New Generation of Glucose Control Technologies Incorporating AI/ML Tools/Strategies (R01 - Clinical Trial Optional) under funding opportunity number RFA-DK-27-146. This federal research grant opportunity is associated with the Special Diabetes Program, a long-standing congressional initiative supporting research on the prevention, treatment, and cure of type 1 diabetes and its complications. The initiative seeks to accelerate the development of next-generation diabetes management technologies that incorporate artificial intelligence, machine learning, and digital twin modeling into open-loop and closed-loop glucose control systems. The agency emphasizes improving glycemic control, reducing the burden of care, and enhancing quality of life for individuals with type 1 diabetes through more adaptive, automated, and personalized systems. The funding opportunity specifically supports multidisciplinary biomedical and engineering research projects that address barriers limiting progress toward more effective diabetes management systems. Areas of interest include innovation in sensing technologies and physiologic signal monitoring, novel hormone formulations and delivery systems, AI-driven algorithms and tools, and digital twin modeling for predictive analytics and automated decision support. The announcement highlights opportunities for projects involving wearable devices, multianalyte sensing, ketone and lactate monitoring, physiologic signal integration, precision medicine approaches, AI-supported insulin delivery systems, interpretable AI advisory systems, and generative AI tools supporting shared decision making between patients and health care providers. The agency also encourages research focused on reducing algorithmic bias through balanced data sets and improved machine learning methodologies. Eligible applicants include a broad range of domestic and international entities. Public and private institutions of higher education, nonprofit organizations, small businesses, for-profit organizations, tribal governments and tribal organizations, state and local governments, school districts, public housing authorities, faith-based organizations, regional organizations, and foreign organizations are all eligible to apply. The funding opportunity also permits foreign components of U.S. organizations. However, NIH policy prohibits foreign subawards or subcontracts under this funding announcement unless specifically authorized through an international collaboration funding opportunity. The program does not require cost sharing or matching funds. Applicant organizations may submit more than one scientifically distinct application, but duplicate or substantially overlapping applications are prohibited. NIDDK intends to commit approximately 3 million dollars in fiscal year 2027 to support approximately three to five awards. Application budgets are limited to 500000 dollars in direct costs per year, and projects may extend for up to five years depending on project scope. Because the award limit is annual, applicants may request as much as 2500000 dollars in direct costs across the maximum project period. Clinical trials are optional under this funding opportunity, allowing both clinical and non-clinical research proposals. Funding is provided through the NIH R01 Research Project Grant mechanism. Allowable activities include basic research, translational studies, biomedical engineering development, algorithm and software development, physiologic modeling, wearable technology integration, and human subjects research where applicable. Applications involving human subjects or clinical trials must comply with NIH human subjects protections, data safety monitoring, and ClinicalTrials.gov registration requirements where applicable. The application process follows standard NIH submission procedures and requires electronic submission through Grants.gov, NIH ASSIST, or an institutional system-to-system solution. Applicants must complete registrations in SAM.gov, Grants.gov, eRA Commons, and obtain a Unique Entity Identifier prior to submission. Program Directors and Principal Investigators must maintain eRA Commons accounts linked to ORCID identifiers. The application package must conform to the NIH Research Instructions and include all required SF424 forms, budget materials, human subjects documentation if applicable, and a mandatory Data Management and Sharing Plan not exceeding two pages. Applications involving human subjects must include at least one study record. Appendix materials are limited, and publications may not be included except for blank questionnaires or surveys. NIH strongly encourages applicants to consult with NIDDK staff early during proposal development to confirm project responsiveness and alignment with program priorities. Applications open on May 17, 2026 and are due by June 17, 2026 at 5:00 PM local time of the applicant organization. The funding opportunity expires on June 18, 2026. Scientific merit review is scheduled for November 2026, advisory council review for January 2027, and the earliest anticipated project start date is April 2027. Applications will be reviewed according to NIH peer review criteria emphasizing significance and innovation, rigor and feasibility, and investigator expertise and environment. Reviewers will assess scientific importance, novelty, reproducibility, feasibility of proposed approaches, adequacy of study design, inclusion plans, and institutional resources. Additional considerations include protections for human subjects, vertebrate animal welfare, biohazard safety, authentication of biological resources, and budget justification. The funding opportunity is a one-time announcement and does not explicitly state a recurring annual cycle, although NIH diabetes technology initiatives have historically reappeared periodically through related programs. Scientific inquiries regarding the funding opportunity may be directed to the Division of Diabetes, Endocrinology and Metabolic Diseases at NIDDK_DEM@nih.gov. Peer review questions may be directed to the Center for Scientific Review at NOFOReviewContact@csr.nih.gov, while financial and grants management questions may be sent to NIDDKGMBManagementTeam@niddk.nih.gov. The agency encourages early submission to allow time for correction of application errors identified during the electronic validation process. Applications that are incomplete, noncompliant, or nonresponsive to the scope of the funding announcement will not be reviewed.

Emphasize innovative AI and ML integration with diabetes technologies; clearly demonstrate scientific rigor and feasibility; provide strong justification for study design and inclusion plans; develop multidisciplinary collaborations; address usability and personalization for diverse populations; include robust data management and reproducibility strategies