Computational Approaches to Curation at Scale for Biomedical Research Assets (R01 Clinical Trial Not Allowed)
Grant funds computational methods to enhance curation processes for biomedical data, facilitating rapid access to datasets for transformative research.
Funder: National Institutes of Health
Due Dates: May 15, 2025 (New) | June 13, 2025 (Renewal/Resubmission/Revision) | August 15, 2025 (AIDS) | September 15, 2025 (New) | October 15, 2025 (Renewal/Resubmission/Revision) | December 15, 2025 (AIDS) | January 15, 2026 (New) | February 13, 2026 (Renewal/Resubmission/Revision) | April 15, 2026 (AIDS) | May 15, 2026 (New) | June 15, 2026 (Renewal/Resubmission/Revision) | August 14, 2026 (AIDS) | September 15, 2026 (New) | October 15, 2026 (Renewal/Resubmission/Revision) | December 15, 2026 (AIDS) | January 15, 2027 (New) | February 17, 2027 (Renewal/Resubmission/Revision) | April 15, 2027 (AIDS)
Funding Amounts: Up to $250,000 direct costs per year (max 4 years); actual budget must reflect project needs.
Summary: Supports innovative computational methods to automate and scale curation of biomedical research data assets, enabling rapid access to high-quality datasets and models.
Key Information: Clinical trials are not allowed; projects must focus on computational, at-scale curation of biomedically relevant digital assets and result in open-access datasets or tools.
Description
This opportunity, offered by the National Library of Medicine (NLM) at NIH, funds research to develop, test, and disseminate computational approaches for curation at scale of biomedical research assets. The goal is to accelerate access to secure, complete, and well-curated datasets and computational models that underpin transformative biomedical discoveries. The program specifically seeks innovative, automated, and scalable computational methods that improve the speed, quality, and scope of curation processes for a wide range of biomedical digital assets.
Projects must focus on automating curation, annotation, integration, and management of digital biomedical assets, supporting FAIR (Findable, Accessible, Interoperable, Reusable) data principles. The resulting datasets, models, or tools should be openly accessible and broadly useful to the biomedical research community.
Manual curation projects, projects not focused on biomedical data, or those duplicating existing NLM products are not eligible. Clinical trials are not permitted under this funding opportunity.
