Computational Approaches to Curation at Scale for Biomedical Research Assets (R01 Clinical Trial Not Allowed) | PAR 20 304

Opportunity Information: Apply for PAR 20 304

The National Library of Medicine (NLM), part of the National Institutes of Health (NIH), is offering an R01 grant opportunity titled "Computational Approaches to Curation at Scale for Biomedical Research Assets (Clinical Trial Not Allowed)" under funding opportunity number PAR-20-304. The central purpose of this program is to strengthen and modernize biomedical data curation by supporting computational approaches that make curation faster, broader in scope, and more scalable. In practical terms, the opportunity is aimed at methods and tools that help turn biomedical research outputs into secure, complete, well-structured datasets and computational models that are easier to access and reuse, with the larger goal of enabling new and potentially transformative biomedical discoveries. Because the focus is on improving curation processes and the infrastructure or methods around them, applications proposing clinical trials are not permitted under this announcement.

The program sits within NIH's broader health and education-related research mission (CFDA 93.879) and uses the standard NIH research project grant mechanism (R01). NLM is explicitly trying to accelerate how quickly high-quality research assets become available to the scientific community and how reliably those assets can be discovered, accessed, and trusted. The emphasis on "curation at scale" signals that NLM is looking for approaches that can handle large volumes of data or models, reduce manual bottlenecks, improve consistency across curators and repositories, and increase coverage across diverse biomedical domains. The description highlights curation as a gateway function: if the inputs are curated well, downstream analysis, replication, integration, and model-building become more feasible and more secure.

A key outcome NLM is pushing for is improved availability and access to "secure, complete" datasets and computational models. That wording suggests projects should take seriously issues like data completeness and integrity, metadata quality, provenance, standardization, and potentially privacy- and security-aware handling of sensitive biomedical information. Although the provided text does not list specific technical topics, the opportunity title and goal strongly indicate interest in computational methods that can automate, assist, or quality-check curation tasks, potentially including approaches such as machine learning or natural language processing for metadata extraction, entity normalization, annotation support, consistency checking, de-identification support, ontology-assisted labeling, automated validation, and workflow systems that improve throughput while maintaining or improving quality.

Eligibility is broad and includes many common government, academic, nonprofit, and commercial applicant types. Eligible applicants include state, county, and city or township governments; special district governments; independent school districts; and public housing authorities/Indian housing authorities. Higher education institutions are eligible, including public and state-controlled institutions of higher education as well as private institutions of higher education. Tribal entities are eligible, including federally recognized Native American tribal governments and Native American tribal organizations other than federally recognized tribal governments. The opportunity also allows nonprofit organizations both with and without 501(c)(3) IRS status (as long as they are not institutions of higher education), and it permits for-profit organizations (other than small businesses) and small businesses as applicants. In addition, NLM lists "Other Eligible Applicants" categories that explicitly include Alaska Native and Native Hawaiian Serving Institutions; Asian American Native American Pacific Islander Serving Institutions (AANAPISI); Hispanic-serving Institutions; Historically Black Colleges and Universities (HBCUs); Tribally Controlled Colleges and Universities (TCCUs); faith-based or community-based organizations; eligible agencies of the federal government; regional organizations; Indian/Native American tribal governments other than federally recognized; and U.S. territories or possessions.

Restrictions related to non-U.S. participation are important. Non-domestic (non-U.S.) entities, described as foreign organizations or foreign institutions, are not eligible to apply as the primary applicant. Non-domestic components of U.S. organizations are also not eligible to apply. At the same time, the announcement allows "foreign components" as defined in the NIH Grants Policy Statement, meaning a U.S.-based applicant may include certain foreign activities or collaborations when they meet NIH's definition and requirements for a foreign component, even though a foreign institution cannot serve as the applicant organization.

From an administrative standpoint, the opportunity is categorized as discretionary funding and uses the grant funding instrument. The original closing date listed for this opportunity is 2024-05-07. The source data lists an award ceiling of 250,000, and the expected number of awards field is present but not populated in the provided text. The opportunity record indicates a creation date of 2020-09-15, which aligns with the PAR number format and suggests it has been available over multiple cycles or receipt dates.

Overall, this funding opportunity is designed for applicants who can bring computational innovation to biomedical curation workflows in a way that measurably improves speed, scalability, and coverage while maintaining high standards for completeness, usability, and security. Competitive projects under this announcement would generally be expected to demonstrate how their approach will reduce friction in turning research outputs into well-curated, reusable biomedical assets, and how those improvements could enable broader access and more reliable reuse of data and models across the biomedical research ecosystem, without involving clinical trial activities.

• The National Institutes of Health in the education, health sector is offering a public funding opportunity titled "Computational Approaches to Curation at Scale for Biomedical Research Assets (R01 Clinical Trial Not Allowed)" and is now available to receive applicants.
• Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.879.
• This funding opportunity was created on 2020-09-15.
• Applicants must submit their applications by 2024-05-07. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
• Each selected applicant is eligible to receive up to $250,000.00 in funding.
• Eligible applicants include: State governments, County governments, City or township governments, Special district governments, Independent school districts, Public and State controlled institutions of higher education, Native American tribal governments (Federally recognized), Public housing authorities/Indian housing authorities, Native American tribal organizations (other than Federally recognized tribal governments), Nonprofits having a 501 (c) (3) status with the IRS, other than institutions of higher education, Nonprofits that do not have a 501 (c) (3) status with the IRS, other than institutions of higher education, Private institutions of higher education, For-profit organizations other than small businesses, Small businesses, Others.

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