Closed · RFA-ES-21-003 · CFDA 93.113 · Discretionary

Application of Artificial Intelligence and Machine Learning for Advancing Environmental Health Sciences (R41 Clinical Trial Not Allowed)

Federal grant opportunity posted by National Institutes of Health, cataloged on Grants.gov.

Varies
Award range
Closed
Status
March 29, 2021
Close date
-
Expected awards

The verdict

Application of Artificial Intelligence and Machine Learning for Advancing Environmental Health Sciences (R41 Clinical Trial Not Allowed) is a closed discretionary listing from National Institutes of Health that offered Varies by applicant. Future funding cycles may be published under the same CFDA number. PlainGrants indexes 12,419 other opportunities from National Institutes of Health.

Varies
award range
Closed
application status
93.113
CFDA program
12,419
other opportunities from National Institutes of Health

Archived opportunity record

Application of Artificial Intelligence and Ma… is closed (last close March 29, 2021). The parent program page for CFDA 93.113 is the reliable place to catch re-announcements. National Institutes of Health still indexes 12,419 other opportunities here.

According to Grants.gov (extract vintage 2026-08-10), this record reflects the officially published listing. See methodology.

Deadline tracker

Application window closed

Closed March 29, 2021

Posted Dec 10 Closes Mar 29

Instrument

Grant

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.

Small-business / for-profit corridor · RFA-ES-21-003

Application of Artificial Intelligence and Ma… prints a for-profit / small-business applicant door (Small businesses). Treat the listing as business-facing unless the full Grants.gov announcement narrows it further. The extract does not mark applicant cost-sharing as required. Instrument: Grant. Funding-activity codes span Environment · Health (ENV;HL). 789 other National Institutes of Health listings share this eligibility-code string (6% of 12,420).

Code 23
Small businesses

Codes are Grants.gov eligibility category values from the extract vintage 2026-08-10. Confirm the full eligibility statement on the official listing or the Grants.gov eligibility reference.

Official Listing on Grants.gov

View full details, application forms, and submission instructions.

View on Grants.gov

Parent Grant Program

CFDA 93.113

Biological Response to Environmental Health Hazards

National Institutes of Health

View program →

Agency Contact

NIH OER Webmaster FBOWebmaster@OD.NIH.GOV

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What to do next

Application of Artificial Intelligence and Ma… is closed; use the parent program and agency catalog for the next funding cycle.

  • Parent CFDA 93.113 may publish future NOFOs under the same assistance listing. Open program
  • Biological Response to Environmental Health H… indexes 83 Grants.gov listings in this extract. Program profile
  • National Institutes of Health lists 12,419 other indexed opportunities on PlainGrants. Agency catalog

Opportunity deadlines and eligibility change on Grants.gov; PlainGrants mirrors the extract and is not the submission system.

Disclaimer: This information is sourced from Grants.gov and SAM.gov and is for informational purposes only. Opportunity details, deadlines, and eligibility requirements change frequently. Always verify current information directly on Grants.gov before applying. PlainGrants is not affiliated with any federal agency.

Read our methodology - how this data is sourced, computed, and verified.

Data sourced from the SAM.gov Assistance Listings and Grants.gov. See our methodology for details. Retrieved and formatted by PlainGrants