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COVID-19: How Canada can reap the benefits of AI-accelerated clinical trials

COVID-19: How Canada can reap the benefits of AI-accelerated clinical trials

Global drug companies have a stronger incentive than ever to move more of what they do from the lab to the virtual world.


 In the interest of sharing information on topics related to COVID-19, here is an excerpt from a recent report on health trends from MaRS Corporate Innovation Programming.

Even before the novel coronavirus pandemic, there was widespread acknowledgement that artificial intelligence can and will bring substantial benefits to drug discovery and development. AI facilitates unprecedented speed and capacity that can lead to huge advances in health care, where researchers often struggle to make sense of vast quantities of complex and often messy data.

AI and other computational tools are being used to help design custom drugs, to accelerate the repurposing of existing treatments, and to test and validate research throughout the long drug development process.

COVID-19 has also created a new sense of urgency, generating even more appetite for AI. It’s also highlighted the need to get drugs to patients much faster, and to combat new and little-known diseases.

For example, AI is enabling subject identification, analysis and drug development even as many traditional experimental labs have been shut down in the pandemic, but demand from the biopharma industry to develop new drugs and get treatments to market continues unabated. Global drug companies have a stronger incentive than ever to move more of what they do from the lab to the virtual world.

“The spotlight has turned from AI being the future to AI is now,” says Naheed Kurji, president and chief executive of Toronto-based Cyclica. “These advanced methods are no longer next-generation. They’re current.”

The good news is that Canada is well-positioned to reap the benefits of the renewed focus on AI in the health sector. There are at least 17 Canadian companies involved in AI drug discovery and development, employing nearly 500 people – but there are many more firms working in the health sector and advanced industries, and there may be potential for AI applications in the clinical trials process. Canada ranks third behind the United States and Britain in the proliferation of AI drug startups, according to data compiled by BenchSci Analytics Inc., a Toronto startup that uses AI to research reagents and scan research papers for potential disease-fighting antibodies.

Several of these companies, including Cyclica and Deep Genomics, are among the roughly 80 health AI companies actively supported by MaRS Discovery District. The Ontario Centres of Excellence funded nearly 800 “advanced health technology” projects between 2013 and 2018. Of those, at least seven involve the use of AI in drug discovery and clinical trials.

Data compiled by MaRS shows that the advanced industry sectors in which AI drug companies and other tech startups operate have experienced faster GDP growth and added jobs at a faster pace than the broader economy over the past decade. In Ontario, for example, GDP growth has averaged 14 per cent per year in the software sector since 2009, and 5.1 per cent in computer system design and medical equipment manufacturing. That compares to average GDP growth of just 2.3 per cent per year across the economy over that period. Employment in Canada’s software sector has grown four times faster than overall private sector job creation, and similar outsized gains have occurred in other sectors where AI startups tend to cluster, including computer design and services, data processing, medical equipment and information services.

 

Source: The Post-Viral Pivot: How Canada’s Tech Startups Can Drive the Recovery from COVID-19, MaRS

 

Still, developing new drugs is a costly and high-risk business. It can take a decade or more to get a drug from the lab to patients. That includes up to six years for drug discovery and five more for clinical trials.

And the odds of success are long. Only one in 1,000 drugs gets to the clinical trial stage. Even fewer — one in 10,000 — is approved for use in people. Many trials are set up for failure from the start because they target the wrong group of subjects — their disease might be too advanced, or not enough, skewing the results. These statistics highlight the significant potential for AI. If we can accelerate even one element of the clinical trials process, such as subject selection, we can drive more efficiency, cost savings and healthier outcomes.

The cost of getting a new drug to market has nearly doubled in the past decade, rising to $2-billion (U.S.) in 2019 from $1.2-billion in 2010, according to Intelligent Clinical Trials: Transforming Through AI-Enabled Engagement, a February report by Deloitte.

 

Source: Intelligent clinical trials: Transforming through AI-enabled engagement, Deloitte

 

Big Pharma and hospitals are embracing AI

The promise of AI and rising drug development costs has triggered a surge of investment in AI companies. Between 2013 and 2018, the sector attracted $4.3-billion (U.S.) worth of investment globally, spread over more than 300 deals, according to Growth Insight: Role of AI in the Pharmaceutical Industry, 2018-2022, a September report by Texas-based market research company Frost & Sullivan. The report forecasts that the combined revenues of AI drug companies is expected to more than double by 2022 — rising to $2.2-billion from $1-billion in 2018. Those who are experimenting now are positioned to reap the financial and impact rewards as investment and revenues continue to grow.

Hospitals and health-care providers are increasingly turning to AI to help diagnose and assess patients, and to track records. And some are already using AI to treat patients with COVID-19. For example, computers are being used to check chest x-rays and CT scans for early signs of disease, to monitor patients’ oxygen levels and to steer doctors toward the best treatment options.

“Having machines to help us build these disease biomarkers is a remarkably powerful thing,” says Shelley Boyd, president and chief executive of Toronto-based Tracery Opthalmics, which uses AI to image and handle data in patients with macular degeneration, a massively underserviced market. “We now have the ability to string together what were disparate aspects of the entire spectrum of drug development and treatment.”

For further insights on this topic — including Canadian artificial intelligence ventures impacting drug discovery and development — please contact MaRS Partner Solutions: partnerships@marsdd.com.