This grant is for developing innovative Artificial Intelligence (AI) and Machine Learning (ML) methodologies to significantly advance environmental health research and decision-making. Specifically, it seeks to improve the accuracy of toxicity prediction, enable efficient prioritization of chemicals for targeted testing, and effectively identify and bridge data or knowledge gaps in toxicity assessment. Furthermore, the developed approaches should enhance the comprehensive understanding of human exposures, susceptibility, and adverse health outcomes. This opportunity targets small business concerns for Phase I SBIR applications, fostering the creation of validated tools to propel environmental health sciences forward.
Opportunity ID: 330302
General Information
| Document Type: | Grants Notice |
| Funding Opportunity Number: | RFA-ES-21-003 |
| Funding Opportunity Title: | Application of Artificial Intelligence and Machine Learning for Advancing Environmental Health Sciences (R41 Clinical Trial Not Allowed) |
| Opportunity Category: | Discretionary |
| Opportunity Category Explanation: | – |
| Funding Instrument Type: | Grant |
| Category of Funding Activity: | Environment Health |
| Category Explanation: | – |
| Expected Number of Awards: | – |
| Assistance Listings: | 93.113 — Environmental Health |
| Cost Sharing or Matching Requirement: | No |
| Version: | Synopsis 1 |
| Posted Date: | Dec 10, 2020 |
| Last Updated Date: | Dec 10, 2020 |
| Original Closing Date for Applications: | Mar 29, 2021 |
| Current Closing Date for Applications: | Mar 29, 2021 |
| Archive Date: | May 04, 2021 |
| Estimated Total Program Funding: | – |
| Award Ceiling: | – |
| Award Floor: | – |
Eligibility
| Eligible Applicants: | Small businesses |
| Additional Information on Eligibility: | Other Eligible Applicants include the following: Non-domestic (non-U.S.) Entities (Foreign Institutions) are not eligible to apply. Non-domestic (non-U.S.) components of U.S. Organizations are not eligible to apply. Foreign components, as defined in the NIH Grants Policy Statement, may be allowed. |
Additional Information
| Agency Name: | National Institutes of Health |
| Description: | This Funding Opportunity Announcement (FOA) solicits Phase I (R43) SBIR grant applications from small business concerns (SBCs) to develop promising methodologies using Artificial Intelligence (AI) and Machine Learning (ML) approaches to advance environmental health research and decisions. When developed and validated, these methodologies or approaches will further advance the accuracy of toxicity prediction, help in prioritizing chemicals for more relevant or targeted testing, identify and/or fill data or knowledge gaps in toxicity assessment, promote more comprehensive understanding of human exposures, susceptibility and adverse health outcomes. |
| Link to Additional Information: | http://grants.nih.gov/grants/guide/rfa-files/RFA-ES-21-003.html |
| Grantor Contact Information: | If you have difficulty accessing the full announcement electronically, please contact:
NIH OER Webmaster
FBOWebmaster@OD.NIH.GOV Email:FBOWebmaster@OD.NIH.GOV |
Version History
| Version | Modification Description | Updated Date |
|---|---|---|
Related Documents
There are no related documents on this grant.
Packages
| Agency Contact Information: | NIH OER Webmaster FBOWebmaster@OD.NIH.GOV Email: FBOWebmaster@OD.NIH.GOV |
| Who Can Apply: | Organization Applicants |
| Assistance Listing Number | Competition ID | Competition Title | Opportunity Package ID | Opening Date | Closing Date | Actions |
|---|---|---|---|---|---|---|
| FORMS-F | Use for due dates on or after May 25, 2020 | PKG00264432 | Feb 28, 2021 | Mar 29, 2021 | View |
Package 1
Mandatory forms
330302 RR_SF424_2_0-2.0.pdf
330302 PHS398_CoverPageSupplement_5_0-5.0.pdf
330302 RR_OtherProjectInfo_1_4-1.4.pdf
330302 PerformanceSite_2_0-2.0.pdf
330302 RR_KeyPersonExpanded_2_0-2.0.pdf
330302 RR_Budget_1_4-1.4.pdf
330302 RR_SubawardBudget30_1_4-1.4.pdf
330302 PHS398_ResearchPlan_4_0-4.0.pdf
330302 SBIR_STTR_Information_1_3-1.3.pdf
330302 PHSHumanSubjectsAndClinicalTrialsInfo_2_0-2.0.pdf
Optional forms
330302 PHS_AssignmentRequestForm_3_0-3.0.pdf
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