IVADO is supporting this research program with $1.2M as part of our Strategic Research Funding Program launched in 2021. We invite you to visit the program’s main page to view its objectives and better understand the process that supported this project.
Designing molecules with desired properties is a fundamental problem in drug, vaccine, and material discovery. Traditional approaches to designing a new drug can take over 10 years and a billion US dollars. Materials have been developed solely based on their performance characteristics leading to materials composed of rare, often toxic elements, which can inflict significant environmental damage. Artificial intelligence (AI) has the potential to revolutionize drug and material discovery by analyzing evidence from large amounts of data accumulated and learning how to search in the compositional space of molecules, and hence significantly accelerate and improve the process.
This program aims to build an efficient and effective machine learning framework for searching molecules with designed properties. It will be crucial to build upon, and extend, ongoing collaborations (i) between Mila and IRIC, aimed at optimizing the algorithms to discover new antibiotics and (ii) between Mila and materials experts at McGill and Université de Montréal, on the development of materials with environmental applications like fighting climate change. This multidisciplinary project also raises exciting fundamental challenges in AI regarding learning to search, modeling and sampling complex data structures like graphs, and may have applications to scientific discovery more broadly.
Université de Montréal, Mila
Université de Montréal, IRIC
Université de Montréal
Resources related to this program will appear here.
Articles and interviews related to this program will appear here.
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