Accelerating the Pace of Drug Abuse Research Using Existing Data (R01 Clinical Trial Optional)

The National Institute on Drug Abuse (NIDA) invites applications for the R01 grant program, “Accelerating the Pace of Drug Abuse Research Using Existing Data.” This funding opportunity encourages the innovative analysis of existing data sets, particularly from social, behavioral, neuroimaging, and administrative studies, to further understand substance use behavior, substance use disorder (SUD) etiology, epidemiology, prevention, treatment, and related HIV issues. Projects using this grant may explore data related to alcohol, tobacco, prescription, and other substance use disorders and are expected to avoid primary data collection in favor of leveraging public and private data sources to answer novel questions in SUD research. NIDA aims to maximize the potential of data already collected, such as those from the Adolescent Brain Cognitive Development (ABCD) study and other NIDA-funded sources. NIDA seeks to advance knowledge on how biological, psychological, social, and environmental factors contribute to substance use patterns, risks, and disorder development. This opportunity is open to studies aiming to characterize SUD trajectories, identify resilience factors, improve treatment and intervention efficiency, and understand barriers to care. Researchers may use various public-use datasets, including neuroimaging, brain development cohorts, and databases tracking substance use in vulnerable populations (e.g., adolescents, those with co-occurring mental health issues, racial and ethnic minorities). Collaborative projects, as well as projects that apply innovative statistical methods, computational modeling, and big data analytics, are particularly encouraged. NIDA stresses that projects should consider the risk of spurious findings when analyzing large data sets and should include strategies to mitigate these risks, including effect size calculations where applicable. Eligible applicants include U.S.-based and foreign higher education institutions, non-profits, for-profit organizations, government agencies, and Native American tribal entities. For entities outside the U.S., compliance with NIH policies for non-domestic institutions is required. Institutions may submit multiple applications provided they are scientifically distinct. Each project can request budgets without a pre-set limit but must align with the needs of the project, and the total project period cannot exceed five years. NIDA intends to commit $2 million in fiscal year 2022 to fund 3-5 awards, depending on funding availability and project merit. Submission requirements include standard NIH grant proposal guidelines and compliance with specific NIDA requirements for this R01 opportunity. Applicants using the ABCD dataset must demonstrate dataset access and adhere to strict guidelines for data security and sharing, including the submission of derived data to the National Institute of Mental Health (NIMH) Data Archive. Applicants are encouraged to include a Resource Sharing Plan and follow specific data handling protocols for ABCD or similar datasets. Applications are due by 5:00 PM local time of the applicant’s organization on the listed due dates, with a recommended letter of intent submitted 30 days prior. Upcoming due dates include November 15, 2024, with additional due dates extending through 2025. Applicants can submit their materials through NIH ASSIST, Grants.gov, or institutional system-to-system solutions, and should verify application completion in the eRA Commons portal before the due date to ensure timely submission. Projects will undergo review by NIDA using NIH peer review criteria, emphasizing significance, investigator qualifications, innovation, approach, and environment. Additional review considerations include the protection of human subjects, inclusion plans for diversity across age, gender, and ethnicity, and the use of animals or biohazard materials where applicable. Compliance with NIH’s data-sharing policies will be factored into the review process.