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NIH Bridge2AI Stage 2 represents the next phase of the NIH Common Fund Bridge to Artificial Intelligence program building on $130 million invested in Stage 1 to create ethically sourced AI-ready biomedical datasets. Stage 2 shifts focus from data generation to building tools devices and safety frameworks that translate those datasets into clinical and research applications.
Two interconnected initiatives are funded: Innovation Funnels supporting teams that use Stage 1 AI-ready datasets to create practical tools including diagnostic algorithms drug discovery platforms and clinical decision support systems that demonstrate measurable health impact and a Network for AI Health Science developing safety measures validation protocols and responsible-use frameworks for AI in health research.
The program values interdisciplinary teams combining computational scientists with domain experts in specific disease areas. Stage 2 Requests for Applications are expected by mid-2026. This is distinct from ARPA-H programs which fund specific high-risk clinical AI applications and from AHRQ healthcare AI safety grants which examine existing AI impact on healthcare systems.
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Search similar grants →Based on current listing details, eligibility includes: Researchers with expertise in both AI/ML methods and specific disease areas at US institutions of higher education research institutes and eligible nonprofits. Bridge2AI explicitly values interdisciplinary teams. Stage 2 RFAs have not yet been posted but are expected by mid-2026. Monitor commonfund.nih.gov/bridge2ai/funding for announcements. Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates $130 million over four years for Stage 2 pending availability of funds. Stage 1 invested $130 million to create ethically sourced AI-ready datasets. Stage 2 will fund Innovation Funnels translating those datasets into clinical tools and a Network for AI Health Science developing safety and validation protocols. Individual award amounts will be specified in forthcoming RFAs. Always verify allowable costs, matching requirements, and funding caps directly in the sponsor documentation.
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The FDT-BioTech program is a joint NSF NIH and FDA initiative that catalyzes biomedical technological innovation through foundational development of methods and algorithms relevant to digital twins and synthetic humans. The program supports inherently interdisciplinary research projects that underpin the mathematical and engineering foundations behind the development and use of digital twins and synthetic data in biomedical and healthcare applications with a particular focus on digital in silico models used in the evaluation of medical devices and to advance regulatory sciences. Priority research areas include computational representations of physiological systems verification validation and uncertainty quantification transferability and generalizability across populations ethics security and privacy considerations and validation mechanisms for digital twin models. The program incorporates AI and machine learning as key enabling technologies for creating responsive digital twin models. All proposals must address regulatory science benefits and ethical implications. This program is distinct from the NSF SCH Smart Health program which focuses broadly on AI for health research and from ARPA-H programs which target specific clinical applications.
NSF TechAccess AI-Ready America is a major new initiative to establish AI-ready Coordination Hubs in every U.S. state and territory to expand access to AI knowledge tools training and capacity building. Announced March 25 2026 the initiative is a joint effort of NSF USDA National Institute of Food and Agriculture (NIFA) Department of Labor and Small Business Administration (SBA). Each Hub will connect local partners and coordinate AI deployment scale proven approaches based on state and local priorities and address three key gaps: workforce AI literacy small business and local government AI adoption and hands-on learning pathways. Up to 56 Hubs will be funded at up to $1 million per year for three years selected through three rounds of competition. An informational webinar is scheduled for April 14 2026. This is distinct from NSF ExpandAI which focuses on institutional AI research capacity building and from NSF Expanding AI Career which targets skilled technical workforce opportunities.
NIFA Adoption of Precision Agriculture program addresses implementation barriers in precision agriculture including site-specific management precision livestock farming and AI-enabled sensing and information technologies. The program funds research and extension projects that help producers overcome the three main obstacles to precision agriculture adoption: initial cost uncertain economic returns and technology complexity. The program particularly emphasizes support for small- and medium-sized producers who have distinct needs compared to large producers by encouraging knowledge-sharing to help them access technology benefits. Funded projects include AI-powered crop monitoring soil health sensing remote sensing for crop stress detection autonomous robots for harvesting and targeted herbicide application weed detection algorithms combining computer vision with robotic sprayers and smart packaging systems for food safety. The program falls under Agriculture Systems and Technology and Advanced Technologies topics within NIFA competitive grant framework. This is distinct from the USDA NIFA AFRI AI-Enabled Agricultural Science program which specifically funds data science and AI foundational research and from NSF AI-ENGAGE which funds international agricultural AI partnerships.