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Federal Grant · National Institutes of Health

Computational Approaches to Curation at Scale for Biomedical Research Assets (R01 Clinical Trial Not Allowed)

Last verified by NonDilute: 2026-04-29. Official notice and agency instructions control.

AI/MLHealthcare Tech small-teamstartupuniversity-researcher
The pitch

Build AI-powered curation tools for biomedical research data and compete for up to $250K from NIH's National Library of Medicine.

Award range
Up to $250K
Closes
Apr 15, 2027 · 351d left
Open date
Oct 29, 2024
Difficulty
Medium
Source
Grants.gov
Agency
National Institutes of Health
Last verified
2026-04-29
Fit language
Possible fit only
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What this is

The National Library of Medicine is seeking innovative computational approaches that can curate biomedical datasets and research materials at scale, addressing the bottleneck of manual data organization in modern life sciences research. Applicants should propose automated or AI-assisted methods to accelerate data mining, metadata tagging, quality control, and knowledge extraction from growing biomedical data repositories. This is ideal for teams building software or computational pipelines that can handle the administrative and organizational overhead of large research datasets. Awards up to $250,000 are available; clinical trials are explicitly not allowed.

Who can apply

Broad eligibility: nonprofits (501(c)(3) and non-501(c)(3)), small businesses, universities, government entities, and for-profit organizations all qualify. No clinical trials allowed. US-based organizations only (implied by agency structure).

Eligible applicant types

Full description — from the agency

NLM wishes to accelerate access to, and availability of, secure, complete datasets and computational models that can serve as the basis for transformative biomedical discoveries. Innovative at-scale computational approaches that increase the speed and scope of curation processes are needed for data mining and knowledge discovery from growing quantities of biomedical data being produced from ongoing data science advances.

Topics: biomedical data curation · computational data mining · automated metadata extraction · research data organization · nlm funding · biodata pipeline

Public-source funding discovery only. This summary is generated from public agency data and may be incomplete or stale. NonDilute is not affiliated with, endorsed by, or acting on behalf of any government agency. Official notices and agency instructions control. NonDilute does not determine eligibility, provide grant-writing advice, or guarantee funding.