Jillian
D'Onfro Forbes Staff Nov 11,
2019, 06:30am
This
story appears in the November 30, 2019 issue of Forbes Magazine.
Not many
scientists get solicited for photo ops, but for Daphne Koller
it’s a regular occurrence. “It happens at pretty much any event that has tech
people,” Koller says when asked about one recent snapshot. “It’s a little
awkward. It’s not like I feel like this is something I deserve.”
Selfie
requests are just one sign of Koller’s stardom, earned from more than 20 years
bridging computer science, biology and education. She chalked up a string of
accolades along the way: getting a master’s degree from Jerusalem’s Hebrew
University at 18; becoming a Stanford University professor focused on machine
learning at 26; winning, nearly a decade later, a MacArthur “genius grant” for
research that combined artificial intelligence and genomics; cofounding $1 billion (valuation)
Coursera, an early platform to let people around the world take
university classes for free.
The
next act for this 51-year-old innovator: Insitro, a firm in South San Francisco
that aims to find new drugs by sorting through masses of data. If it succeeds,
it will have overturned how drugs get discovered.
Lab
biologists typically focus on a few specific proteins as drug targets. If those
fail, data scientists make suggestions for others to try. Insitro, on the other
hand, wants to collect much more data before the biologists go off on their
hunt. It will leverage advances in bioengineering (such as Crispr gene editing)
and in software that enables computers to see things that escape humans.
Koller
describes her aha moment this way: “Machine learning is now doing amazing
things if you give it enough data. We finally have the opportunity to create
biological data at scale.”
“There are very few individuals who understand
both sides of the beast,” says Mani Subramanian, who heads liver disease
clinical research at Gilead. “The biology as well as the deep learning.”
Insitro’s
computational experts and
biologists work together to create lab experiments to produce
massive custom data sets. Machine learning models then find patterns to suggest
new tests and potential therapies. Robotics like automated pipetting machines
reduce human error. With all this, Insitro can do “experiments in a matter of
weeks instead of years,” Koller says.
AI plus
biology, her background, was a “marriage made in heaven” for investors, she
says. Within six months Koller raised $100 million from ARCH Ventures,
Andreessen Horowitz, Foresite Capital, Alphabet’s venture fund GV and Third
Rock, with Jeff Bezos and others joining later. In April, she landed a deal
with Gilead Sciences that gives Insitro $15 million now with $1 billion to
follow if it helps find a treatment for a deadly form of nonalcoholic fatty
liver disease. The disease is expected to soon become the leading cause of
liver transplants.
“There
are very few individuals who understand both sides of the beast,” says Mani
Subramanian, who heads liver disease clinical research at Gilead. “The biology
as well as the deep learning.”
Insitro’s
future payouts from Gilead hang on whether it can identify five proteins that
could be targets for drugs and then whether targeting those proteins leads to
approved therapies for the liver disease. The contingent payments, which
include revenue sharing from successful drugs, helped Insitro earn a spot on Forbes’ inaugural AI 50 list
of the most promising artificial intelligence companies.
More
than 20 other startups are chasing the dream of faster, cheaper drug discovery
through AI. Among them are Notable Labs, with $55 million of venture capital,
and Verge Genomics, with $36 million. Novartis has announced a five-year AI
collaboration with Microsoft, and Merck and GSK have startup partnerships as
well.
Artificial
intelligence does not make biology easy. “I don’t think the platform can be
magic,” Koller says.
Before
Insitro can reap rewards, a few hundred thousand lab tests need to happen.
Koller has the energy. Bouncing around Insitro’s office—she gave away her desk
chair to one of her 53 employees because she never used it—she moves from a
room named Macrophage (a white blood cell) to one named Elastic Net (a
data-modeling technique) to show off the latest lab equipment.
Big
Pharma’s interest would seem to make Insitro a likely acquisition target if it
hits pay dirt. But Koller says she doesn’t want to see Insitro “swallowed into
the maw” of a larger organization. She wants it to make its own branded drugs.
The ultimate goal is that the people asking for photos ops will be
healthier thanks to Insitro. Koller says she hopes they come up to her and say,
“Because of you, I have my life back.”
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