Grants and Contributions:

Title:

Machine Learning for Efficient and Effective Molecule Discovery

Agreement Number:

999240

Agreement Value:

$979,440.00

Agreement Date:

Mar 30, 2023 - Mar 31, 2026

Description:

Designing molecules with desired properties in drug, vaccine, and materials discovery is a challenge. Accurately identifying lead candidate molecules early on can significantly reduce the time and cost involved. Artificial Intelligence (AI) has the potential to revolutionize drug and material discovery by analyzing evidence from a large amount of previously accumulated data, thereby significantly accelerating the process. This Project will examine searching for molecules with optimized properties in the presence of different types of oracles, corresponding to estimators of the desired properties at varying degrees of computational cost and fidelity. The Project aims to build an efficient and effective machine learning framework for searching molecules with designed properties, and showcase its applications on antibiotic and materials discovery, thereby enabling AIempowered candidate discovery. This presents a solution for reducing a resource intensive and time consuming design bottleneck, which is a core design challenge across many industrial domains.

Organization:

National Research Council Canada

Expected Results:

In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.

Location:

Montreal, Quebec, CA H3N 1X7

Reference Number:

172-2022-2023-Q4-999240

Agreement Type:

Grant

Report Type:

Grants and Contributions

Recipient Business Number:

108160995

Recipient Type:

Academia

Recipient's Legal Name:

UNIVERSITÉ DE MONTRÉAL

Federal Riding Name:

Papineau

Federal Riding Number:

24055

Program:

Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives

Program Purpose:

Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.

NAICS Code:

541710