Tuesday, July 8, 2025 7/8/2025

Generative AI for retrosynthesis libraries

Award Number: R01LM014385
ORGANIZATION: NATIONAL LIBRARY OF MEDICINE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 01/09/2024
PERIOD OF PERFORMANCE END DATE: 11/30/2027

Group Awards By:

View Award Description

Generative AI for retrosynthesis libraries - Project Summary Over the past 30 years, the synthesis of small molecules has become commonplace to facilitate drug discovery and development efforts. Retrosynthesis reduces a structurally complex target molecule into increasingly structurally simpler intermediates and commercially available starting materials, facilitating the preparation of a target molecule (also referred to as product) through a series of logical synthetic reactions (i.e., a multi-step synthetic route) from readily available starting materials or building blocks (referred to as reactants). Retrosynthetic analysis has become the cornerstone of modern synthetic endeavors and has revolutionized drug design. The goal of this project is to develop innovative generative AI – the type of AI that can create new content, to generate synthetic reaction libraries with diverse and feasible reactant molecules to synthesize given molecules via one-step synthetic reactions, and to evaluate and validate the libraries in laboratories thoroughly and rigorously. To achieve the goal, we have the following Aims. Aim 1 is to generate diverse and high-quality synthetic reaction libraries by developing innovative deep graph generative methods for retrosynthesis prediction. Novel graph neural networks will be developed to best capture and represent molecular structures for downstream retrosynthesis analysis. Innovative graph-based generative methods will automate step-by-step modification of target molecules toward their reactants. Aim 2 is to generate diverse and high-quality synthetic reaction libraries by developing innovative sequence-based methods for retrosynthesis prediction. Novel sequence-based methods include pre-training strategies, SMILES editing and a reinforcement learning framework will be developed. Aim 3 is to evaluate the generated synthetic reactions by domain expertise and laboratory experiments. Successful completion of this project will enable diverse and high-quality synthetic reaction libraries for any given drug-like molecule, which will be highly significant to accelerating drug development (e.g., lead generation). More importantly, the project will enable new AI capacity and infrastructure far beyond the conventional methodologies in synthetic route design. Successful application of the new methodology is ultimately expected to facilitate rapid retrosynthetic analysis of newly discovered or complex molecules as well as those with limited availability, enabling chemical synthesis for subsequent biological evaluations.


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: 2025 ( Subtotal = $330,004 )
2025	2025	OHIO STATE UNIVERSITY, THE	1960 KENNY RD	COLUMBUS	OH	43210	FRANKLIN	USA	Medical Library Assistance	001	2	6/23/2025	NON-COMPETING CONTINUATION	$33,000
2025	2025	OHIO STATE UNIVERSITY, THE	1960 KENNY RD	COLUMBUS	OH	43210	FRANKLIN	USA	Medical Library Assistance	000	2	12/3/2024	NON-COMPETING CONTINUATION	$297,004
														Subtotal = $330,004

Issue Date FY: 2024 ( Subtotal = $330,713 )
2024	2024	OHIO STATE UNIVERSITY, THE	1960 KENNY RD	COLUMBUS	OH	43210	FRANKLIN	USA	Medical Library Assistance	000	1	1/9/2024	NEW	$330,713
														Subtotal = $330,713

Grand Total All Awards = $660,717

Top

All Categories

About

Search

Reports

Data Submission

Award Information

Generative AI for retrosynthesis libraries

Award Number: R01LM014385

ORGANIZATION: NATIONAL LIBRARY OF MEDICINE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 01/09/2024

PERIOD OF PERFORMANCE END DATE: 11/30/2027

Federal Websites

Department of Health & Human Services

HHS Operating Divisions

HHS Staff Divisions

Download A Document Viewer