This NIDA grant, D-START, is offered to facilitate the entry of investigators into addiction-related data science, a crucial cross-cutting research approach identified in the NIDA Strategic Plan. It is designed for newly independent data scientists or established investigators seeking to integrate novel data science methodologies into their research for the first time. The grant supports small-scale projects applying emerging data science methods to address critical questions requiring advanced analytic strategies. These projects can answer specific research questions or generate preliminary data for larger initiatives. Applicants are encouraged to utilize existing datasets, adhere to FAIR principles, and consider ethical implications. The ultimate goal is to expedite the development of robust research programs at the convergence of innovative data science and addiction research, with initial projects serving as precursors for more expansive future work.
Opportunity ID: 357733
General Information
| Document Type: | Grants Notice |
| Funding Opportunity Number: | PAS-25-236 |
| Funding Opportunity Title: | D-START: Data Science Track Award for Research Transition (D/START) (R03-Clinical Trial Optional) |
| Opportunity Category: | Discretionary |
| Opportunity Category Explanation: | – |
| Funding Instrument Type: | Grant |
| Category of Funding Activity: | Education Health |
| Category Explanation: | – |
| Expected Number of Awards: | – |
| Assistance Listings: | 93.279 — Drug Use and Addiction Research Programs |
| Cost Sharing or Matching Requirement: | No |
| Version: | Synopsis 1 |
| Posted Date: | Dec 16, 2024 |
| Last Updated Date: | Dec 16, 2024 |
| Original Closing Date for Applications: | Sep 07, 2027 |
| Current Closing Date for Applications: | Sep 07, 2027 |
| Archive Date: | Oct 13, 2027 |
| Estimated Total Program Funding: | $100,000 |
| Award Ceiling: | $100,000 |
| Award Floor: | – |
Eligibility
| Eligible Applicants: | For profit organizations other than small businesses State governments City or township governments Native American tribal governments (Federally recognized) Others (see text field entitled “Additional Information on Eligibility” for clarification) County governments Public and State controlled institutions of higher education 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 Independent school districts Public housing authorities/Indian housing authorities Private institutions of higher education Special district governments Nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education Small businesses |
| Additional Information on Eligibility: | Other Eligible Applicants include the following: Alaska Native and Native Hawaiian Serving Institutions; Asian American Native American Pacific Islander Serving Institutions (AANAPISISs); Eligible Agencies of the Federal Government; Faith-based or Community-based Organizations; Hispanic-serving Institutions; Historically Black Colleges and Universities (HBCUs); Indian/Native American Tribal Governments (Other than Federally Recognized); Non-domestic (non-U.S.) Entities (Foreign Organizations); Regional Organizations; Tribally Controlled Colleges and Universities (TCCUs) ; U.S. Territory or Possession. |
Additional Information
| Agency Name: | National Institutes of Health |
| Description: | Data science is an important cross-cutting research approach in the 2022 – 2026 NIDA Strategic Plan and increasing the capacity of experts in addiction related data science is critical. The purpose of this Notice is to facilitate the entry of investigators to the area of addiction-related data science, including newly independent data scientists or established investigators seeking to incorporate novel and cutting-edge data science methodologies into their research programs for the first time. Through this opportunity, investigators will propose to apply emerging data science methods to answer critical questions requiring advanced data analytic strategies. Projects should be small in scale and answer specific research questions or provide preliminary data for a larger scale project. Applicants are encouraged to use existing datasets, follow FAIR principles, and, when applicable, attend to ethical concerns in the conduct of research involving human subjects. Ultimately, the aim is to expedite the development of robust research programs focused on the convergence of innovative data science techniques and addiction research, with initial projects serving as precursors for subsequent, more expansive research projects. |
| Link to Additional Information: | https://grants.nih.gov/grants/guide/pa-files/PAS-25-236.html |
| Grantor Contact Information: | If you have difficulty accessing the full announcement electronically, please contact:
NIH Grants Information
grantsinfo@nih.gov Email:grantsinfo@nih.gov |
Version History
| Version | Modification Description | Updated Date |
|---|---|---|
Related Documents
Folder 357733 Full Announcement-PAS-25-236 -> PAS-25-236-Full-Announcement.pdf
Packages
| Agency Contact Information: | NIH Grants Information grantsinfo@nih.gov Email: grantsinfo@nih.gov |
| Who Can Apply: | Organization Applicants |
| Assistance Listing Number | Competition ID | Competition Title | Opportunity Package ID | Opening Date | Closing Date | Actions |
|---|---|---|---|---|---|---|
| FORMS-I | Use for due dates on or after January 25, 2025 | PKG00289676 | Jan 16, 2025 | Sep 07, 2027 | View |
Package 1
Mandatory forms
357733 RR_SF424_5_0-5.0.pdf
357733 PHS398_CoverPageSupplement_5_0-5.0.pdf
357733 RR_OtherProjectInfo_1_4-1.4.pdf
357733 PerformanceSite_4_0-4.0.pdf
357733 RR_KeyPersonExpanded_4_0-4.0.pdf
357733 PHS398_ResearchPlan_5_0-5.0.pdf
357733 PHSHumanSubjectsAndClinicalTrialsInfo_3_0-3.0.pdf
Optional forms
357733 RR_Budget_3_0-3.0.pdf
357733 RR_SubawardBudget30_3_0-3.0.pdf
357733 PHS398_ModularBudget_1_2-1.2.pdf
357733 PHS_AssignmentRequestForm_4_0-4.0.pdf
Share This Post, Choose Your Platform!
About the Author: osnqt
