Toronto , Canada – 22 May 2019; Daphne Koller, CEO & Founder, Insitro, on day two of Collision 2019
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When it comes to biotech company Insitro, it’s not the machine learning platform or the cutting-edge biology that lures in investors: it’s the founder and CEO, Daphne Koller. Koller has an impressive resume; a cofounder of online education platform Coursera, a computer science professor at Stanford, and a MacArthur Fellowship recipient.
Investors are confident, however, that Koller has the chops to bridge the world of biology and machine learning in her relatively new pharma company. The proof is in the numbers. The San Francisco-based company announced Tuesday that it’s raised a $143 million round of funding, bringing the total amount of venture capital its raised to $243 million.
Koller is “exactly the type of entrepreneur we’re looking for,” says Vijay Pande, a general partner at Andreessen Horowitz who recently joined the Insitro board of directors, “a pioneer at the intersection of machine learning and biopharma.” Andreessen led the funding round, which included new investors T. Rowe Price Associate, BlackRock, Casdin Capital and CPP Investments. Current investors including ARCH Venture Partners, GV and Third Rock Ventures also participated. “It’s a bet on Daphne,” says Robert Nelsen of ARCH Venture Partners, “she’s just exceptional.”
Koller founded the San Francisco-based startup two years ago with a goal of meshing data science and life science. “There are not enough people who are able to straddle both worlds,” she says, “bringing these tools together is absolutely critical.” Its accomplishments in a short period of time was enough to land Insitro on Forbes’ inaugural AI 50 list last fall as one of the most promising artificial intelligence companies.
In order to discover new drugs, Insitro starts with biology. Using cells from humans, the company induces them into pluripotent stem cells which can turn into almost any cell in the body. Researchers then create models of genetic diseases, and use machine learning to figure out what the difference is between healthy cells and sick cells. These subtle differences are “often lost on a person because of the sheer volume of data,” Koller says, “and that’s where machine learning really shines.” The goal, she says, is to find “the interventions that revert the disease state back to the healthy state.”
Insitro hasn’t discovered any new medications yet, but last year it inked a deal with Gilead to work on a drug for liver disease with $15 million up front and the potential for $1 billion down the road. The deal allows Insitro to use data from Gliead’s clinical trials to train its machine learning platform. The company also focuses heavily on neuroscience, and hopes that using human cells instead of animal models will help find new drugs for neurological diseases.
Some of the new capital from the funding round will go towards building up the company’s capabilities to develop drugs, including eventually hiring regulatory experts and other staff that have experience with drug development. Seeing as how the company hasn’t yet found its first drug, however, those particular hires are still a long ways off. Money will also go towards scaling up the company in other ways, like continuing to develop its liver disease research.
The field of using machine learning to aid drug development is becoming increasingly crowded. Other startups including Recursion Pharma and Verge Genomics are also using machine learning to speed up drug development, and major pharmaceutical companies like Novartis and Merck have partnered with companies to improve machine learning capabilities.
One thing that makes Insitro different from the rest is that it produces massive amounts of new data to train its machine learning platform. Many other companies have taken the shortcut of relying on existing datasets to teach their machine learning, Koller says, but some of those data sets are messy and will result in poorly functioning platforms. “My experience is that machine learning is really only as good as the data you feed it,” she says.
Another difference with Insitro: while some other startups have the goal of partnering with larger companies, Insitro aims to become a fully functioning pharma company on its own, bringing drugs all the way from discovery through development and regulatory approval. Koller says that she will still consider some partnerships, but “we will take some of our drugs all the way through.”
Of course, perhaps the biggest difference between companies is that Insitro is led by the ambitious Koller herself. “That’s why people are willing to invest in this company vs. other companies,” says Nelsen, “we’re not trying to build a small company, we’re building a drug company that’s trying to turn the industry on its head.”