Deep Genomics nabs $40M round, doubles down on AI and Wilson disease work

TFT-admin | January 7, 2020

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by Ben Adams

Deep Genomics CEO Brendan Frey (Deep Genomics)

Canadian drug development company Deep Genomics has got off a $40 million series B round as it looks to double down on its rare genetic disease and artificial intelligence work.

Deep Genomics is one of an increasing number of biotech and drug development companies delving into AI to help better understand and create new drug targets, specifically those that have been deemed “undruggable,” as well as to design new drugs and animal models.

This approach, the company explained, results in “remarkable clarity and speed,” as, according to its figures, 70% of research projects have led to therapeutic leads, and programs have been taken from target discovery to drug candidate in less than a year.  

The $40 million swag will go toward furthering these efforts as well pushing two early-stage programs to IND this year. Deep Genomics will also be also gathering up phase 1/2 data for its Wilson disease (a rare and potentially fatal genetic disorder characterized by excess copper stored in various body tissues) candidate, slated for next year.

This series B was led by Future Ventures alongside Amplitude Ventures, Khosla Ventures, Magnetic Ventures and True Ventures.

“Therapeutically re-engineering the human genome is the final frontier,” said Brendan Frey, founder and CEO of Deep Genomics. “Doing so requires systems that can predict information pertaining to the genome, and the best technology we have for prediction is AI. We have found that the more we explore the universe of genetic therapies using AI, the more we discover dark regions that can be illuminated only with the development of new technology.

“This financing will enable us to expand our AI technology in the pursuit of new therapeutic opportunities, to advance our Wilson program into the clinic, and to strategically partner assets emerging from our overflowing preclinical pipeline.”

RELATED: In conversation with Brendan Frey: Deep Genomics reveals the first-ever AI-discovered drug candidate

The Toronto-based biotech has been quietly plugging away since 2015 on its AI Workbench. It uses more than 20 machine learning systems that have been “carefully validated and tested” and trained on public and proprietary data to screen disease-causing mutations in search of new drug targets.

“We have built a system that within two hours can scan over 200,000 pathogenic patient mutations and automatically identify potential drug targets,” Frey told FierceBiotech last fall. Instead of chasing known targets or getting into a hot therapeutic area, Deep Genomics is letting the system do the choosing—an approach that saw it land on Wilson disease.

Deep Genomics’ system figured out that a mutation changes an amino acid in ATP7B, a copper-binding protein that is absent in Wilson patients. But it also predicted that this change should not affect how the protein works. The AI eventually discovered that the mutation disrupts an instruction in the genome that tells cells how to make that protein, causing it to not be made at all.

The platform identified a dozen potential drug candidates, and Deep Genomics took them to the lab to make sure they worked the way the AI predicted they would. After some tolerability and pharmacokinetics experiments, the company declared DG12P1 its first pipeline candidate that it would advance toward IND.

“For over twenty years, our team at Future Ventures has backed visionary companies seeking to change the world for the better,” said Steve Jurvetson, co-founder of Future Ventures and board member of Tesla and SpaceX.

“Deep Genomics has pioneered a better way to systematically discover new therapies with a much higher success rate than traditional pharma methods. My partner Maryanna Saenko and I are excited to be joining them on a journey to modernize drug development by using AI to design and de-risk drug development programs up front, instead of relying on trial-and-error experiments that are fraught with time delays and high cost.”