Computational Approaches to Curation at Scale for Biomedical Research Assets (R01 Clinical Trial Not Allowed) | PAR 18 796

Opportunity Information: Apply for PAR 18 796

The National Library of Medicine (NLM), part of the National Institutes of Health (NIH), is seeking research projects that develop and test computational methods to improve biomedical data curation at scale. The central aim is to make biomedical research assets, especially high-value datasets and computational models, available faster and in more complete and usable forms. This opportunity is built around the idea that curation is often a major bottleneck in turning raw or semi-structured biomedical information into secure, well-documented, interoperable resources that researchers can reliably discover, access, and reuse. By funding new computational approaches, NLM is trying to expand both the speed and breadth of curation so that curated assets can better support downstream biomedical discovery.

This funding opportunity is offered as an NIH R01 research project grant and is explicitly labeled “Clinical Trial Not Allowed,” meaning the proposed work should not include clinical trial activities as defined by NIH. The activity category is listed under Education and Health, and the relevant CFDA number is 93.879. The opportunity is identified as PAR-18-796 and was created on May 22, 2018, with an original closing date of January 31, 2020. The listed award ceiling is $250,000 (as provided in the source text). While the expected number of awards is not specified in the provided details, the mechanism and ceiling indicate support for research-grade efforts aimed at advancing methods, tools, or frameworks rather than small pilot-only projects.

The program emphasis is on computational approaches that can strengthen curation processes for biomedical research assets. In practical terms, this points to methods that can help curate large volumes of data more efficiently, improve data quality and completeness, standardize metadata, support secure handling of sensitive information, and facilitate broader access and reuse. The phrasing highlights “secure, complete data sets and computational models,” which suggests interest in both data resources and the models derived from or used with them, along with the documentation and metadata needed to make those assets trustworthy and reusable. The overall theme is scalability: proposals should address curation challenges that arise when data and models are too large, too complex, or too heterogeneous for traditional manual curation workflows to keep up.

Eligibility is broad across the U.S. research and public service landscape. Eligible applicants include state, county, and local governments (including cities/townships and special districts), independent school districts, public and state-controlled institutions of higher education, private institutions of higher education, federally recognized Native American tribal governments, and Native American tribal organizations (including those other than federally recognized tribal governments). The opportunity also allows public housing authorities/Indian housing authorities, nonprofits (both 501(c)(3) and non-501(c)(3), as long as they are not institutions of higher education in those nonprofit categories), for-profit organizations (other than small businesses), and small businesses. The announcement also explicitly calls out additional eligible applicant types such as Alaska Native and Native Hawaiian Serving Institutions, Asian American Native American Pacific Islander Serving Institutions (AANAPISIs), Hispanic-serving Institutions, Historically Black Colleges and Universities (HBCUs), Tribally Controlled Colleges and Universities (TCCUs), faith-based or community-based organizations, eligible federal agencies, regional organizations, and U.S. territories or possessions. This framing is consistent with NIH’s intent to encourage participation from a wide variety of institutions, including those that serve historically underrepresented communities.

Foreign participation is restricted. Non-domestic (non-U.S.) entities (foreign institutions) are not eligible to apply, and non-domestic components of U.S. organizations are also not eligible to apply. In addition, foreign components, as defined in the NIH Grants Policy Statement, are not allowed. In other words, the work must be led and carried out in eligible U.S.-based organizational contexts without foreign components as part of the proposed project structure.

In summary, this NLM R01 opportunity supports U.S.-based research efforts that create or improve computational approaches to biomedical curation at scale, with the goal of accelerating the production of secure, complete, and accessible datasets and computational models that can power transformative biomedical research. It combines a clear programmatic goal (speeding and broadening curation) with broad U.S. applicant eligibility, while drawing a firm boundary against clinical trials and against foreign institutional participation or foreign components.

• 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 2018-05-22.
• Applicants must submit their applications by 2020-01-31. (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.

Apply for PAR 18 796

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