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Integration of artificial intelligence and drug discovery to treat Alzheimer’s disease

Award Number: R01AG098153
ORGANIZATION: NATIONAL INSTITUTE ON AGING
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 02/15/2026
PERIOD OF PERFORMANCE END DATE: 01/31/2031

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Integration of artificial intelligence and drug discovery to treat Alzheimer’s disease - Project Summary/Abstract Alzheimer’s disease (AD) is a devastating neurodegenerative disorder affecting approximately 44 million people worldwide. Due to the lack of a clear understanding of its underlying mechanisms, hypothesis-driven AD drug discovery remains a high-risk challenge. The NIA/NIH-supported Accelerating Medicines Partnership in Alzheimer’s Disease (AMP-AD) initiative has made significant progress in identifying and prioritizing a comprehensive list of novel AD-associated targets. However, the discovery of viable chemical probes for these targets remains difficult due to the inherent complexity of traditional screening methods and the challenging nature of these targets. Recent advancements in AI-driven computational methodologies have the potential to transform drug discovery by enabling more efficient hit identification and optimization. However, even the most sophisticated computational approaches are ineffective without seamless integration into a well-defined experimental pipeline. Without rigorous experimental validation and iterative refinement, AI-driven methods risk failing to translate their predictions into meaningful therapeutic outcomes. To address this limitation, we will develop and apply a tightly integrated AI-driven computational and experimental workflow to accelerate the discovery of small-molecule modulators of proteins well known to influence Alzheimer’s disease through the regulation of phagocytosis by microglia. Specifically, we will screen seven sites across four proteins: PLC2, moesin, GEF-H1, and SHIP1. Our approach will involve: 1) developing and apply AI-driven methods to design DNA-encoded libraries that target these sites; 2) implementing an integrative AI-driven computational and experimental pipeline for hit discovery and validation; and 3) performing AI-assisted hit optimization to enhance the efficacy of promising leads in cellular and animal models. Through this approach, we anticipate delivering potent small-molecule leads for the proposed targets while also developing and openly sharing highly innovative, rigorously validated AI-driven methodologies to advance drug discovery to treat Alzheimer’s disease.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $1,250,191 )
2026	2026	UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL	104 AIRPORT DR STE 2200	CHAPEL HILL	NC	27599	ORANGE	USA	Aging Research	000	1	2/13/2026	NEW	$1,250,191
														Subtotal = $1,250,191

Grand Total All Awards = $1,250,191

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Integration of artificial intelligence and drug discovery to treat Alzheimer’s disease

Award Number: R01AG098153

ORGANIZATION: NATIONAL INSTITUTE ON AGING

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 02/15/2026

PERIOD OF PERFORMANCE END DATE: 01/31/2031

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