D-START: Data Science Track Award for Research Transition (D/START) (R03-Clinical Trial Optional) | PAS 25 236

Opportunity Information: Apply for PAS 25 236

D-START: Data Science Track Award for Research Transition (D/START) (R03-Clinical Trial Optional) is a National Institutes of Health funding opportunity (NIDA-focused) designed to help researchers break into addiction-related data science or make a first major pivot into modern data science methods within an addiction research program. It sits within the priorities of NIDA's 2022-2026 Strategic Plan, which treats data science as a cross-cutting capability needed to speed discovery and improve the quality, scale, and impact of addiction research. The main idea is capacity-building: bringing more investigators into the addiction data science ecosystem and helping them generate early, credible results that can grow into larger, longer-term projects later.

The award uses the R03 mechanism, meaning it is intended for small, focused studies rather than large multi-year research programs. Projects are expected to be limited in scope and targeted at answering a specific, well-defined question that truly benefits from advanced analytic approaches, or at producing preliminary results that justify a future, larger application. The emphasis is not on building a full data platform from scratch, but on demonstrating that an emerging or cutting-edge data science approach can be applied to an addiction-related problem in a way that is rigorous, informative, and scalable. Clinical trials are optional under this announcement, so applicants may propose a clinical trial if it fits the goals, but they are not required to do so.

A defining feature of this opportunity is its focus on innovative data science methodologies applied to addiction research questions that require more than standard statistical approaches. While the announcement does not restrict applicants to particular techniques, the intent is clearly to encourage modern strategies such as machine learning and predictive modeling, natural language processing, causal inference at scale, network and systems modeling, multimodal data integration, advanced computational phenotyping, or other approaches that can handle complex, high-dimensional, messy, or longitudinal data typical of real-world addiction research. In other words, the funding is meant for applicants who can credibly show why a data science approach is necessary for the question and how the work will move the field forward.

Applicants are encouraged to rely on existing datasets whenever feasible, which aligns with the R03's small-project design and helps teams move quickly to analysis and proof-of-concept results. In practical terms, this could include analysis of previously collected clinical, epidemiological, administrative, electronic health record, claims, wearable, digital behavior, social media, imaging, genomic, or other datasets, depending on the research question and data access. The opportunity also highlights FAIR data principles (Findable, Accessible, Interoperable, Reusable), signaling that strong data stewardship, documentation, and reuse-oriented practices are valued. If human subjects are involved, the notice also calls attention to ethical considerations, which in data science contexts often include privacy and confidentiality protections, bias and fairness in models, explainability and transparency, consent and data use limitations, risks of re-identification, and appropriate governance for sensitive addiction-related information.

The broader programmatic goal is to accelerate the formation of robust, sustainable research programs at the intersection of data science and addiction science. These R03 projects are positioned as launchpads: a way for newly independent data scientists to establish credibility in addiction research, or for established addiction or health researchers to demonstrate competence with a novel analytic toolkit for the first time. Success is effectively measured by whether the project produces actionable findings, validated analytic pipelines, or strong preliminary evidence that can support a more expansive follow-on application.

In terms of basic administrative details, the opportunity is listed as PAS-25-236, a discretionary grant program in the Education and Health activity area, associated with CFDA number 93.279. The award ceiling is $100,000, reinforcing the expectation of a small, sharply scoped project. The original closing date is September 7, 2027. The sponsoring agency is NIH, and the scientific framing points specifically to NIDA priorities.

Eligibility is broad and includes many organization types across the public, private, and nonprofit sectors. Eligible applicants include state, county, city, and special district governments; independent school districts; public and state-controlled institutions of higher education; private institutions of higher education; federally recognized Native American tribal governments; tribal organizations and other tribal governments that are not federally recognized; public housing authorities and Indian housing authorities; nonprofits with or without 501(c)(3) status (other than institutions of higher education); for-profit organizations (other than small businesses); small businesses; and other entities. The notice also explicitly calls out additional eligible applicants 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, non-U.S. (foreign) organizations, and U.S. territories or possessions. This wide eligibility list reflects an interest in expanding the pool of addiction data science contributors and encouraging participation from a diverse range of institutions and communities.

Overall, this grant opportunity is best understood as an on-ramp: it funds compact, methodologically forward projects that use advanced data science to answer important addiction-related questions, ideally leveraging existing data, producing reusable outputs, and setting up investigators for larger, more comprehensive research efforts afterward.

• The National Institutes of Health in the education, health sector is offering a public funding opportunity titled "D-START: Data Science Track Award for Research Transition (D/START) (R03-Clinical Trial Optional)" 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 2024-12-16.
• Applicants must submit their applications by 2027-09-07.
• Each selected applicant is eligible to receive up to $100,000.00 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 PAS 25 236

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