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AHRQ PA-24-261 funds research to determine (1) whether and how breakthrough uses of AI systems affect patient safety in real clinical environments and (2) how AI systems can be safely implemented and used in healthcare delivery.
The R18 mechanism funds evaluation - this NOFO explicitly does not support development of new AI systems but rather the rigorous post-deployment evaluation of AI in live clinical settings, complementing AHRQ's broader digital healthcare portfolio. Topics include AI failure mode analysis, alert fatigue from clinical AI, AI-driven diagnostic safety, equity impacts of clinical AI, and human-AI team performance in care delivery.
Strong fit for health services researchers, patient safety researchers, and health systems studying AI deployment outcomes.
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Or search similar grants →According to the current listing, eligibility includes: U.S. organizations including academic medical centers, universities, nonprofits, health systems, federal and state agencies, hospitals, and tribal organizations. Multiple PIs encouraged. AHRQ priority populations encouraged. Confirm the full requirements in the official notice before applying.
The current listing shows AHRQ R18 demonstration awards typically up to $400,000 direct costs per year for up to 3 years ($1.2M direct costs, ~$2M total with indirects). Multiple awards anticipated. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for AHRQ Examining the Impact of Artificial Intelligence AI on Healthcare Safety R18 PA-24-261 for Evaluating Deployed Clinical AI Systems are due December 8, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
AHRQ Examining the Impact of Artificial Intelligence AI on Healthcare Safety R18 PA-24-261 for Evaluating Deployed Clinical AI Systems is funded by Agency for Healthcare Research and Quality (AHRQ). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
NCI ITCR Sustained Support U24 (RFA-CA-27-021) sustains widely-adopted cancer informatics technologies in production use by the cancer research community. Funds operational support, user experience improvement, security and accessibility hardening, and continued community engagement for mature AI/ML tools. Examples include cBioPortal, AI cancer imaging platforms, genomic data commons tools, and clinical informatics platforms. Up to $600K direct costs per year for up to 5 years. Strong fit for teams maintaining open-source cancer AI infrastructure with broad user communities.
The NCI ITCR Early-Stage Development U01 funds the design, prototype, and pilot of novel AI/ML-driven informatics technologies that improve acquisition, management, and/or analysis of data across the cancer research continuum. Funded projects include foundation models for cancer pathology, multimodal cancer foundation models, AI-driven clinical decision support, deep learning tumor microenvironment analysis, and AI clinical trial matching tools. Awards provide up to $300K direct costs per year for up to 3 years. Strong fit for academic medical centers, cancer centers, and informatics labs building open-source AI cancer tools. RFA-CA-27-019 reissues the long-running ITCR program through 2027 with multiple receipt dates.
NCI ITCR Advanced Development U24 (RFA-CA-27-020) funds the maturation, enhancement, validation, and dissemination of emerging informatics technologies for cancer research and clinical care. Awards support AI/ML platforms ready to move beyond prototype, including deep learning cancer imaging tools, AI clinical decision support systems, multimodal cancer foundation models, AI-driven genomics pipelines, and digital pathology AI. Up to $600K direct costs per year for up to 5 years allows substantial software engineering, validation, and community adoption activities. Strong fit for established cancer informatics teams with mature AI prototypes ready for production deployment.
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