Accelerating the Pace of Substance Use Research Using Existing Data (R01 Clinical Trial Not Allowed)

The Accelerating the Pace of Substance Use Research Using Existing Data (R01 Clinical Trial Not Allowed) grant, offered by the National Institute on Drug Abuse (NIDA), a component of the National Institutes of Health (NIH), is a reissue of funding announcement RFA-DA-22-037. This Notice of Funding Opportunity (NOFO), now labeled RFA-DA-26-055, supports innovative research projects that utilize existing social science, behavioral, administrative, and neuroimaging data to study various aspects of substance use and related disorders. The primary aim is to enhance understanding of the etiology, trajectories, prevention, and treatment of substance use and its related health outcomes, including HIV/AIDS. It emphasizes the use of already collected datasets, avoiding primary data collection, to provide new insights into the complex nature of substance use and addiction. NIDA is particularly interested in leveraging rich datasets such as the Adolescent Brain Cognitive Development (ABCD) Study, as well as other NIDA-supported sources like the National Addiction & HIV Data Archive Program (NAHDAP), and public datasets such as the Population Assessment of Tobacco and Health (PATH) Study and the Human Connectome Project. These datasets can help researchers analyze developmental trajectories, risk and protective factors, and service utilization. Proposals must demonstrate novelty in analytical approach or research question and cannot simply continue ongoing analyses of existing grants. Studies can also include data from local governments, private data holders, or publicly accessible administrative records, provided they do not involve new data collection. Projects may explore topics such as the impact of state-level policies on overdose mortality, disparities in health outcomes across population subgroups, trajectories of substance use disorders (SUD), neurocognitive development, and health service access. Special interest is given to projects that apply innovative methodologies, big data analytics, artificial intelligence, and computational modeling to analyze these datasets. Analyses should be rigorous, predictive, and translatable into actionable strategies for service delivery, prevention programs, and policy development. Applications analyzing HIV-related datasets are also encouraged to further understanding of the dynamics between substance use and HIV pathogenesis, treatment, and prevention. The funding mechanism is a research project grant (R01), and the award budget is not capped but should be commensurate with the scope of the project. The project duration may be up to five years. NIDA anticipates awarding $2 million in FY 2026 to fund two to four applications, with an additional $2 million reserved for HIV-related research under this NOFO and its R21 companion (RFA-DA-26-056). Applications may be submitted as new, renewal, resubmission, or revision types, provided they do not involve clinical trials. This funding opportunity is open to a broad array of applicants, including institutions of higher education, nonprofits, for-profit organizations, government entities, tribal governments, and foreign institutions. All applicants must ensure they have the appropriate registrations completed through SAM.gov, eRA Commons, and Grants.gov. Program Directors/Principal Investigators must also have valid eRA Commons accounts prior to submission. Foreign components are permitted. Applications must adhere strictly to NIH's application guidelines, and must be submitted electronically via ASSIST, Grants.gov Workspace, or institutional system-to-system platforms. The NOFO includes multiple submission deadlines through December 3, 2027. The first available application date is June 17, 2025. The review process includes scientific merit review and advisory council review, with the earliest potential start date for awards being April 2026. Letters of intent are encouraged but not mandatory and should be submitted at least 30 days prior to the chosen submission deadline. For questions, applicants may contact Marsha F. Lopez, Ph.D., M.H.S., at marsha.lopez@nih.gov or 301-443-6504.

Follow NIH guidance precisely. Include innovative analysis and avoid primary data collection.