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

Source-based overview

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. The official record contains the controlling eligibility, budget, attachment and submission requirements for opportunity RFA-DK-28-116.

Eligibility

Eligible applicant types listed by the agency: Special district governments; Public and State controlled institutions of higher education; Native American tribal governments (Federally recognized); Nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education; Independent school districts; Private institutions of higher education; Native American tribal organizations (other than Federally recognized tribal governments); Nonprofits having a 501(c)(3) status with the IRS, other than institutions of higher education; Small businesses; State governments; Public housing authorities/Indian housing authorities; Others (see text field entitled "Additional Information on Eligibility" for clarification); County governments; For profit organizations other than small businesses; City or township governments. Applicants must also satisfy every programme-specific condition in the official notice.

Funding and benefits

Estimated programme funding: USD 5,000,000

Expected number of awards: 1

Themes and supported activities

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.

Opportunity number: RFA-DK-28-116

Deadline and timeline

Forecast notice: deadline to be announced: Forecast notice: deadline to be announced.

Applicants should confirm the exact deadline time, time zone, required documents, portal steps and any institutional approvals on the official call page before submitting.

How to apply

Open the official Grants.gov record, review the full notice and attachments, and use the application package or agency route stated there.

Before applying, check eligibility rules, budgets, attachments, page limits, partner requirements, cost-share conditions and whether the opportunity uses an expression of interest, full proposal, registration or nomination stage.