Ensuring Canada’s Leading Role in AI-Driven Biotech

Published on March 18, 2024

I have always been driven by my curiosity. While I am aware that many view the rapid expansion of artificial intelligence with skepticism or even fear, I think the path forward for Canada’s approach to AI and AI-based drug discovery needs to be led, first and foremost, by curiosity. What might we be capable of if we truly rallied our resources?

“Canada’s approach to AI—and AI-based drug discovery—needs to be led, first and foremost, by curiosity.”

Having been exposed to the possibilities of AI early in my career as a computational chemist, I have a perspective on its capabilities, and what I have seen fills me with hope. As both a scientist and a human being, I wake up each day excited by the incredible breakthroughs that AI is bringing. I’m mostly interested in the structure of molecules and how we can optimize their design to treat specific diseases using the latest technological applications. AI is an incredible tool that can help us achieve this aim more quickly—and the interest and acceleration of the AI biotech industry offers Canada an opportunity to build on its history and strengths to play a leading role.

My “Why”: Early Exposure to AI Drug Discovery

Shot of two scientists helping one another in the lab.

During my PhD at Concordia University in theoretical chemistry, I learned how we can change the functions of molecules by manipulating their structures using computational algorithms. After graduating, I witnessed first-hand how scientists leverage these same algorithms to design lifesaving drugs. But, I was always interested in discovering new approaches to improve the drug discovery process—from finding new targets to designing new drugs, using the latest computational tools.

“I learned how we can change the functions of molecules by manipulating their structures using computational algorithms. After graduating, I witnessed first-hand how scientists leverage these same algorithms to design lifesaving drugs.”

When I was introduced to Insilico Medicine, one of the first companies to apply machine learning to the design and development of new drugs, and saw how they were successfully applying AI to better understand the connections between diverse data and how to take advantage of the diversity to design within and beyond the known biological and chemical space, it was a revelation. I was immediately interested in becoming a part of this effort to develop these AI tools further to bring speed and efficiency to the drug discovery process in a way that we had never before imagined.

I knew that the company would benefit tremendously from establishing a research and development center in Montreal. There is talent here, extensive university research programs in AI, government support, and an established tech ecosystem. But while Canada can boast significant achievements when it comes to AI, ranking high globally in such measures as AI academic publications, researchers and students studying AI, and AI startups, now is not the time to become complacent or to let fear guide our decision-making.

Canada’s Early Wins in Bioscience and AI

Science, healthcare and scientist with a laptop for research, innovation and pharmaceutical email. .

We can be proud of Canada’s early innovation in both the biosciences and AI. It was a team of Canadian researchers that discovered insulin more than 100 years ago, and Canadian scientists played a leading role in developing both the polio and Ebola vaccines.

It was also Canada that formed the world’s first national AI organization in the 1970s, as well as the early global research organization CIFAR, which now includes more than 400 researchers from 161 institutions in 18 countries. CIFAR, along with Mila, the Vector Institute, and Amii, are the key pillars behind the Pan-Canadian AI Strategy, which was launched in 2017 and was the world’s first national AI strategy.

Now, we need to build on this foundation and quickly ramp up to ensure that we can keep pace with the growing need for tech talent, particularly in biotech.

The Need for an R&D Focus

Montreal International shared that nearly 20% of foreign investment in the city has been in the life science sector in the past five years. Quebec boasts one of the premier life sciences and health technology hubs in North America, with over 1,000 companies in the sector. In fact, among countries worldwide, Canada ranks fourth for active biotech firms, behind the US, UK, and France, thanks in large part to favourable national policies and investments.

“If we’re going to ensure that Canadian cities continue to develop as true world-class biotech hubs, R&D needs new focus, including policies aimed at generating R&D, more public-private partnerships, and strong tax incentives.”

But when it comes to biotech R&D intensity, Canada slips to 12th place. If we’re going to ensure that Canadian cities continue to develop as true world-class biotech hubs, R&D needs new focus, including policies aimed at generating R&D, more public-private partnerships, and strong tax incentives.

Strengthening the Biotech Talent Pipeline

Like other AI-driven biotechs in Canada, Insilico Medicine is expanding and looking for top talent, including in machine learning, IT security, application science, and business development. While Canada benefits from a strong, interconnected AI ecosystem—including Mila in Quebec, the world’s largest academic research center for deep learning founded by Yoshua Bengio, and the Vector Institute for Artificial Intelligence in Toronto founded by Geoffrey Hinton (one of the godfathers of deep learning)—we need to continue to invest in developing this local pipeline of cutting-edge tech talent. According to a recent poll by KPMG, 80% of Canadian businesses surveyed said they need more workers with digital skills.

“It is essential that we create robust industry and academic partnerships that will ensure students are trained in the latest tools and are ready to become the tech-savvy drug hunters of tomorrow when they graduate.”

With the speed at which biotech tools and capabilities are evolving—we are now incorporating everything from large multi-modal, multi-domain models to quantum computing into our platform—it is essential that we create robust industry and academic partnerships that will ensure students are trained in the latest tools and are ready to become the tech-savvy drug hunters of tomorrow when they graduate.

This can include academic labs adopting AI platform tools to advance their own research and publishing their findings jointly while gaining access and skills for their labs in the process. There can also be training programs developed in collaboration with biotech partners as well as guest speakers and lecturers, internship opportunities, and funded academic research projects dedicated to AI.

With government, academic institutions, industry, and startups working together, we can capitalize on Canada’s leading position in the biosciences and AI to become a world leader in the next generation of AI-driven drug discovery and development.