Artificial Intelligence in Pre-clinical Drug Development for AD/ADRD (R01 Clinical Trial Not Allowed)

Ceiling: $1,000,000
Applications Due: Closed
Federal
U.S. Department of Health & Human Services (National Institutes of Health)

This funding opportunity supports researchers and organizations in developing innovative artificial intelligence and machine learning methods to accelerate drug discovery and preclinical development for Alzheimer's disease and related dementias.

Description

The National Institute on Aging (NIA) is inviting applications for its funding opportunity, "Artificial Intelligence in Pre-clinical Drug Development for Alzheimer’s Disease (AD) and AD-related Dementias (ADRD)" (RFA-AG-24-049). This initiative focuses on utilizing artificial intelligence (AI) and machine learning (ML) to expedite drug discovery and preclinical drug development for AD/ADRD. Applicants may propose new or existing AI/ML methods to improve drug candidate identification, optimization, and selection. The program also seeks the development of advanced open-source tools for the broader research community. Applications for this R01 funding opportunity may not include clinical trials.

The purpose of the program is to advance the discovery and preclinical development of drugs targeting the complex biology of AD/ADRD. By integrating AI/ML with existing scientific approaches, the initiative aims to enhance efficiencies in compound screening, drug design, and candidate evaluation. Projects combining computational tools with experimental validation are strongly encouraged. The program will also complement NIA’s existing TREAT-AD centers by contributing to open-source resources for drug discovery.

The NIA intends to allocate $6 million in FY 2025 to fund three to four awards, each with a maximum project period of five years. Direct costs are capped at $1 million annually. Proposals must be well-justified and align with the program’s objectives. Eligible applicants include higher education institutions, non-profits, small businesses, for-profit organizations, government entities, and foreign institutions. Proposals must include plans to make generated tools, data, and models available through open-source platforms such as the AD Knowledge Portal.

Key dates include a letter of intent due January 28, 2025, and application submission by February 28, 2025. Review and advisory council meetings are scheduled for June and October 2025, with awards anticipated in December 2025. The initiative strictly enforces compliance with application instructions, including page limits and formatting guidelines. Applications must be submitted electronically through NIH ASSIST, Grants.gov Workspace, or an institutional system-to-system solution.

Evaluation criteria include significance, innovation, rigor, feasibility, investigator expertise, and alignment with NIA’s strategic goals. Projects must demonstrate the ability to address key challenges in AD/ADRD drug development and effectively utilize AI/ML for translational research. Applications should include detailed data-sharing and management plans to support the NIH’s open science principles.

Applicants are encouraged to submit applications early to resolve submission issues promptly. Assistance is available from NIH contacts, including scientific/research, financial, and technical support. This funding opportunity represents a significant effort by the NIA to leverage AI/ML innovations for advancing AD/ADRD research and therapeutic development.

Eligibility

States
All
Regions
All
Eligible Entities
State governments, County governments, City or township governments, Special district governments, Independent school districts, Public and State controlled institutions of higher education, Native American tribal organizations, Public housing authorities, Nonprofits

Funding

Program Funding
$1,000,000
Award Ceiling
$1,000,000
Award Floor
Award Count

Timing

Posted Date
December 03, 2024
App Status
No Longer Accepting Applications
Pre-app Deadline
January 13, 2025
Application Deadline
February 28, 2025

Funder

Funding Source
Source Type
Federal
Contact Name
Contact Email
Contact Phone
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