D-START: Data Science Track Award for Research Transition (D/START) (R03-Clinical Trial Optional)
Funding Agency:
- National Institutes of Health
D-START seeks to promote the entry of investigators into a program of research that applies cutting edge data science techniques and resources to answer critical questions related to substance use and/or SUD. We encourage pilot and feasibility studies, along with small, self-contained investigations. Additionally, we welcome secondary analyses of existing data, as well as projects based on new data collection, spanning observational, experimental, and clinical trials. Both domestic and international research endeavors are permitted.
The range of topics can include, but are not limited to:
- Developing predictive models using state-of-the-art machine learning techniques to anticipate trajectories of SUD risk, encompassing addiction development through recovery while incorporating end-user feedback at each stage of research to ensure applicability and relevance.
- Utilizing data science methodologies to enhance accessibility, utilization, efficiency, and quality of prevention interventions, treatment implementation, and service delivery for SUD and associated disorders (e.g., HIV), across diverse settings including traditional treatment centers, criminal justice systems, schools, and primary care facilities.
- Employing clustering algorithms to identify common subtypes of SUD based on genetics, comorbidities, psychosocial factors, and environmental exposures and utilizing these subtypes for targeted intervention strategies and mechanistic investigations.
- Conducting analyses using data science techniques to elucidate neurobiological mechanisms underlying complex aspects of substance use and/or SUD, such as polysubstance use and co-occurrence with other neuropsychiatric disorders as well as exploring transdiagnostic risk factors contributing to SUD.
- Developing and applying whole-brain computational models integrating multimodal data (e.g., structural imaging, fMRI, PET) to deepen understanding of substance use and/or SUD mechanisms and evaluating the impact of behavioral and pharmacological interventions.
- Creating innovative computational tools and artificial intelligence algorithms tailored for complex datasets to unravel the multifaceted nature and progression of substance use and/or SUD, with a focus on analyzing large-scale longitudinal data and multimodal datasets incorporating brain imaging, behavioral assessments, and genetic information.
Secondary datasets are accessible via the National Addiction & HIV Data Archive Program, NIDA Center for Genetic Studies, or other NIDA-funded initiatives such as the Adolescent Brain Cognitive Development (ABCD) Study and NIDA Clinical Trials Network. Additional data repositories or platforms of potential interest include, but not limited to, database of Genotypes and Phenotypes (dbGaP), Mouse Phenome Database (MPD), Rat Genome Database (RGD), All of Us Research Program, UK Biobank, ScHARe, SCORCH (Single Cell Opioid Responses in the Context of HIV) Program, Gene Expression Omnibus (GEO), and HEAL Platform. Of particular interest are analyses of data that have been harmonized and merged across data sets, such as those using PhenX and NIH Toolbox measures; public/restricted-use longitudinal data from the Population Assessment of Tobacco and Health (PATH) Study; or imaging datasets, such as the Human Connectome Project. We also strongly encourage utilization of the National Addiction & HIV Data Archive Program (NAHDAP) hosted by ICPSR, as well as data from NIDA Data Share for clinical trials. Additional NIH data repositories can be found at https://www.nlm.nih.gov/NIHbmic/domain_specific_repositories.html and sources of public health policy information include the Opioid Policy Tools and Information Center (OPTIC), NIAAA’s Alcohol Policy Information System (APIS), and LawAtlas.
Budgets for direct costs of up to $100,000 per year for up to 2 years, may be requested.
October 16, 2024; February 16, 2025
Susan N. Wright, Ph.D.
National Institute on Drug Abuse (NIDA)
Division of Neuroscience and Behavior (DNB)
Phone: 301- 402-6683
Email: susan.wright@nih.gov
Janet Kuramoto-Crawford, Ph.D.
National Institute on Drug Abuse (NIDA)
Division of Epidemiology, Services and Prevention Research (DESPR)
Phone: 301-443-8856
E-mail: janet.kuramoto-crawford@nih.gov