Leveraging Big Data Science to Elucidate the Mechanisms of HIV Activity and Interaction with Substance Use Disorder (R01 - Clinical Trials Not Allowed) | RFA DA 21 040

Opportunity Information: Apply for RFA DA 21 040

The National Institutes of Health (NIH) published this discretionary grant funding opportunity, RFA-DA-21-040, titled "Leveraging Big Data Science to Elucidate the Mechanisms of HIV Activity and Interaction with Substance Use Disorder (R01 - Clinical Trials Not Allowed)." It uses the R01 research project grant mechanism and sits in the Education and Health funding activity category under CFDA 93.279. The core aim is to bring data and computational scientists into HIV and addiction research by encouraging proposals that use big data methods to better explain how HIV behaves biologically and how that biology intersects with substance use disorder (SUD). A key restriction is that clinical trials are not allowed under this announcement, meaning the work should focus on computational, analytical, and related research approaches rather than running intervention studies in humans.

The scientific emphasis is on creating and applying novel ways to integrate data that differ in both type and scale, with the idea that important signals are currently buried across disconnected datasets. The FOA is looking for projects that go beyond routine analyses and instead develop or substantially advance computational, bioinformatics, statistical, and other analytical approaches that can combine heterogeneous data sources in a meaningful way. In practice, that could involve integrating multi-omic data with clinical and behavioral data, linking longitudinal health records with molecular measurements, or developing methods that can reconcile population-level patterns with cellular or tissue-level mechanisms. The expectation is that these innovations in data integration and analysis will open up lines of inquiry that were previously out of reach and will uncover new insights into addiction biology in the context of HIV, including mechanistic pathways that may explain why outcomes differ across individuals or subgroups with different substance use profiles.

Because the FOA is framed around "big data science," it is essentially prioritizing methodological innovation and cross-cutting analytics over narrowly scoped, single-dataset studies. Successful projects would typically propose a clear plan for handling complex data challenges such as harmonizing variables across studies, addressing missingness and bias, scaling computation, improving reproducibility, and validating findings across independent datasets. The underlying theme is that the combination of sophisticated computational approaches with rich, multi-source data can clarify HIV activity and host response in ways that also reflect the real-world biological and behavioral complexities introduced by substance use disorder.

Eligibility is broad and intentionally inclusive. Eligible applicants include state, county, and city or township governments; special district governments; independent school districts; public and state-controlled institutions of higher education; private institutions of higher education; Native American tribal governments that are federally recognized; tribal organizations other than federally recognized tribal governments; public housing authorities and Indian housing authorities; nonprofit organizations with or without 501(c)(3) status (as long as they are not institutions of higher education); for-profit organizations (other than small businesses); small businesses; and other entities. The FOA 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 agencies of the federal government; regional organizations; U.S. territories or possessions; tribal governments other than federally recognized; and non-domestic (non-U.S.) entities, meaning foreign organizations can apply as well.

From an administrative standpoint, the opportunity was created on 2020-12-28 and originally closed on 2021-02-09. The listed award ceiling is $350,000, and the number of expected awards is not specified in the provided source data. Overall, the announcement is best understood as NIH signaling a strong interest in high-impact computational research that can fuse diverse data streams into coherent biological insight, specifically to illuminate the intertwined mechanisms of HIV and substance use disorder, without conducting clinical trials.

• The National Institutes of Health in the education, health sector is offering a public funding opportunity titled "Leveraging Big Data Science to Elucidate the Mechanisms of HIV Activity and Interaction with Substance Use Disorder (R01 - Clinical Trials Not Allowed)" and is now available to receive applicants.
• Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.279.
• This funding opportunity was created on 2020-12-28.
• Applicants must submit their applications by 2021-02-09. (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 $350,000.00 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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