Home Artificial Intelligence for Global Health Artificial intelligence for drug discovery: An international partnership for public health

Artificial Intelligence for Global Health

Artificial intelligence for drug discovery: An international partnership for public health

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This project focuses on the fight against rarer diseases that pose major health risks on a global scale, such as antimicrobial resistance (AMR) or certain tropical diseases.

It aims to provide government public health agencies with a common mechanism to rapidly develop appropriate drugs and deploy them effectively on a global scale. This will be done by leveraging the many benefits of artificial intelligence, science and open data practices.

Harnessing the potential of artificial intelligence and open science to revolutionise drug research and development.

Antimicrobial resistance or tropical diseases are important public health issues. However, these are not prioritised by the pharmaceutical industry’s research and development (R&D) investments, as they are not very lucrative.

This issue represents a major challenge for which international and innovative collaboration is essential. To address this challenge, collaboration must bring together players from each step of the R&D process for new drugs.

Experts on the GPAI Working Group on Responsible AI identified challenges and opportunities conducive to using responsible AI to accelerate drug discovery. The initiative therefore brings governments together to develop new incentive and funding structures, as well as data sharing frameworks that enable a cultural and capacity shift toward more open data use among academic and industry stakeholders.

The impact of this project will be through the creation of an international non-profit partnership to manage an actionable, rapid, and cost-effective drug discovery pipeline, leveraging AI and promoting open data and open science practices.

This partnership will have the capacity to produce new drugs quickly, and at low cost to fight neglected diseases around the world. Ultimately, it will equip public health to effectively manage neglected and emerging diseases for the benefit of all.


Arnaud Quenneville-Langis


Project Manager

Stephanie King


Director of AI Initiatives

Alice H. Oh

KAIST School of Computing

Project co-lead

Yoshua Bengio


Project co-lead


Allison Cohen

AI for Humanity, Mila

Elliot Layne

School of Computer Science, McGill University and Mila

Invited Specialists

Anurag Agrawal

Alan Aspuru-Guzik

Regina Barzilay

Joanna Bryson

Carlo Casonato

Raja Chatila

Enrico Coiera

Payel Das

Marc-Antoine de La Vega

Aled Edwards

Marc-André Gagnon

Yeong Zee Kin

Hiroaki Kitano

Gary Kobinger

Pierre Larouche

Tze Yun Leong

Kim McGrail

Dewey Murdick

Richard Naiberg

Ziad Obermeyer

Alan Paic

Alejandro Pisanty

Daniele Pucci

Margarita Sordo

Mirjana Stankovich

Gaël Varoquaux

Collaborative opportunities with CEIMIA

Collaborating with CEIMIA means contributing to the development of responsible AI. For this project, we welcome organisations (both public or private, from any sector!) who are interested in improving the current state of existing drug discovery pipelines and markets: if your organisation is aligned with our project’s recommendations on means of improving drug discovery methods for social good, and believe you have a tangible solution, we’d love to hear from you!