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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.
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Search similar grants →Based on current listing details, eligibility includes: Only U.S. institutions of higher education including two-year and four-year accredited colleges and community colleges may submit. No PI or co-PI can lead more than one proposal. Each proposal must include a minimum of two collaborating senior personnel representing both mathematical sciences and at least one domain area such as biomedical sciences or computer science with cyberinfrastructure expertise. Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates Up to $1,000,000 per collaborative project over up to 3 years. Total annual program budget of $4,000,000 to $5,000,000 with 6 to 10 awards anticipated per year. Always verify allowable costs, matching requirements, and funding caps directly in the sponsor documentation.
The current target date is May 4, 2026. Build your timeline backwards from this date to cover registrations, approvals, attachments, and final submission checks.
Federal grant success rates typically range from 10-30%, varying by agency and program. Build a strong proposal with clear objectives, measurable outcomes, and a well-justified budget to improve your chances.
Requirements vary by sponsor, but typically include a project narrative, budget justification, organizational capability statement, and key personnel CVs. Check the official notice for the complete list of required attachments.
Yes — AI tools like Granted can help research funders, draft proposal sections, and check compliance. However, always review and customize AI-generated content to reflect your organization's unique strengths and the specific requirements of the solicitation.
Review timelines vary by funder. Federal agencies typically take 3-6 months from submission to award notification. Foundation grants may be faster, often 1-3 months. Check the program's timeline in the official solicitation for specific dates.
Many federal programs offer multi-year funding or allow competitive renewals. Check the official solicitation for continuation and renewal policies. Non-competing continuation applications are common for multi-year awards.
NSF-NIH-FDA Foundations for Digital Twins as Catalyzers of Biomedical Technological Innovation is sponsored by National Science Foundation with NIH and FDA. 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 Foundations for Digital Twins as Catalyzers of Biomedical Technological Innovation (FDT-BioTech) program is a tri-agency initiative by NSF, NIH, and FDA supporting inherently interdisciplinary research that underpins the mathematical and engineering foundations behind the development and use of digital twins and synthetic data in biomedical and healthcare applications. The program funds advances in mathematics, statistics, computational sciences, and engineering required to develop responsive digital twin models incorporating artificial intelligence capabilities. Research areas include in silico models for medical device evaluation, synthetic human generation, and emerging challenges in biomedical technology development and assessment. Awards are up to $1,000,000 for collaborative projects from multiple organizations over 3 years, with the program issuing 6 to 10 awards per cycle. The next deadline is May 4, 2026, with annual cycles on the first Monday of May thereafter. This program specifically targets the foundational computational methods that make biomedical digital twins possible rather than application-specific implementations.
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.
NSF SaTC 2.0 (Security Privacy and Trust in Cyberspace) is the largest open solicitation for university-led cybersecurity research in the federal portfolio now expanded with AI security as an explicit priority area. The 2.0 reboot added generative AI security open-source software security quantum computing security and supply chain security as topics of interest addressing the bidirectional role of AI as both a cybersecurity threat and a defensive tool. Research awards support adversarial machine learning and attacks on AI systems AI weaponization against people information and systems privacy-preserving machine learning and responsible AI use for detecting and responding to cyber threats. The program funds three award types: Research awards up to $1.2M for four years Education awards up to $500K for three years and Seedling awards up to $300K for two years through Dear Colleague Letters. Proposals are accepted on a recurring annual basis with two windows per year. This is distinct from NSF CyberAICorps which focuses on scholarship and workforce development and from NSF AIMing which focuses on AI formal methods and mathematical reasoning.
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.