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NIAMS P30 Centers Program (P30 - Clinical Trial Not Allowed)

The overall goal of this program is to accelerate scientific discovery, improve research efficiency, and enhance the translation of research findings into improved health outcomes.

FromNational Institutes of Health
Who can applystate governments, counties, cities and townships, special districts (water, fire, parks, etc.), school districts, public colleges and universities and 9 more types
Eligibility notesOther Eligible ApplicantsIndian/Native American Tribal Governments (Other than Federally Recognized);Eligible Agencies of the Federal Government;U.S.
How muchup to $500K per award; about 30 awards; $17 million total
DeadlineThu, Mar 1, 2029 (860 days left)
CategoryHealth
TypeGrant
Opportunity #RFA-AR-28-001
Assistance listing93.313, 93.846
PostedFri, Oct 9, 2026

Open the official posting

From the notice

The overall goal of this program is to accelerate scientific discovery, improve research efficiency, and enhance the translation of research findings into improved health outcomes. Centers funded under this program will also foster multidisciplinary collaboration, support workforce development across career stages, and promote training in emerging areas such as data science, artificial intelligence, and implementation research. The National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) requests applications for the NIAMS P30 Centers Program to support integrated research Centers within its mission areas of skin biology and diseases; bone, muscle, and orthopaedic research; and rheumatic diseases.The NIAMS P30 Centers Program supports Centers that provide coordinated research infrastructure, shared resources, and methodological expertise to advance basic, translational, and clinical research.These Centers are expected to integrate state-of-the-art research resources with capabilities that support clinical and translational research, including the development, testing, and dissemination of novel analytical methods, study designs, outcome measures, and data-driven approaches.

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