Health innovation in Canada has always been strong, but the sector is now experiencing growth at a pace we haven’t seen before. While COVID-19 helped accelerate change, new technologies like OpenAI’s ChatGPT are also having an impact. Plus, Canadian companies are leveraging machine learning to develop new therapies, diagnostics and patient platforms.
“There’s a lot of really interesting drivers out there for innovation,” says Jacki Jenuth, partner and chief operating officer at Lumira Ventures. “We’re starting to better define some of the underlying mechanisms and therapeutics approaches for diseases that up until now had no options, such as neurodegenerative diseases. And researchers are starting to define biomarkers to select patients more likely to respond in clinical settings — that’s really good news.”
This week, the annual MaRS Impact Health conference will bring together healthcare professionals, entrepreneurs, investors, policymakers and other stakeholders. Here’s a sneak preview of some of the emerging trends in the healthcare and life sciences space they’ll be exploring.
Women’s health funding isn’t where it should be, says Annie Thériault, managing partner at Cross-Border Impact Ventures. Bayer recently announced it’s stopping R&D for women’s health to focus on other areas. Other pharmaceutical companies such as Merck have made similar decisions in recent years. “It’s hard to imagine why groups are moving in that direction, because we’re seeing huge revenue opportunities in these markets,” says Thériault. “A lot of exciting things are happening.”
One area that Thériault has been watching closely has been personalized medicine that uses artificial intelligence, machine learning or sophisticated algorithms to tailor treatment for women and children. For instance, there are tools that provide targeted cancer treatments that use gender as a key input. “In the past, that maybe wouldn’t have been thought of as an important variable,” she says.
In prenatal care, there are new tools related to diagnosing anomalies in pregnancies through data. “What we see in maternal health is a lot of inequalities,” Thériault says. “But if the exam is performed with the same level of care, accuracy, and specificity, then analyzed through AI to spot problems, you can make positive health outcomes and hopefully a less unequal health system.”
New technologies like ChatGPT have shown the potential of not just getting AI and machine learning to take large data sets and make sense of them, but also to create efficiencies when it comes to doing paperwork with that information.
“I always thought we’d get to this point, but I just didn’t think we’d get to here so soon where we are talking about AI really changing the nature of jobs,” says Frank Rudzicz, a faculty member at the Vector Institute for Artificial Intelligence. “And it’s just getting started.”
There are a lot of inefficiencies in healthcare that AI can help with. Doctors, for instance, spend up to half their time working on medical records and filling out forms. (A recent study from the Canadian Federation of Independent Business found that collectively they are spending some 18.5 million hours on unnecessary paperwork and administrative work each year — the equivalent of more than 55 million patient visits.) “That’s not what they signed up for,” he says. “They signed up to help people.”
While people are becoming more comfortable with using technology to track and monitor their health — whether that be through smartwatches, smartphone apps or genetic testing — there aren’t as many connection points for them to use that data with their family doctor. There is an opportunity, Rudzicz says, to use data and technologies such as machine learning, with proper guardrails and patient consent, to sync the data with your doctor’s records to help with diagnosis and prescribing.
“Ultimately, doctors are trained professionals and they need to be the ones who make the diagnosis and come up with treatment plans with the patients,” he says. “But once you get all the pieces together, the results could be more accurate and safer than they have been.”
Plus, there are a lot of possible futures for technologies like ChatGPT in healthcare, such as automating repetitive tasks like filling out forms or writing requisitions and referral letters for doctors to review before submitting. “The barrier to entry for anything that will speed up your workflow is going to be very low and easily integrated,” Rudzicz says.
While there’s been a slowdown in venture capital funding, with fewer dollars available as markets become more rational after the record highs of the last few years, there’s still funding to be found, says Lumira’s Jenuth. Management teams in the life sciences space just have to be more resourceful and explore all possible avenues of funding, including corporations, non-dilutive sources, foundations and disease specific funders, she adds.
“It helps to build deep relationships with investors who want to make an impact in the health sectors,” she says. “The pitch needs to be targeted for each one of these groups. You’ll hear a lot of nos, so you need to be tenacious. It’s not easy.”
Discover more of the technologies and ideas that will transform healthcare at the MaRS Impact Health conference on May 3 and 4.
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