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population, not just one.” The phenomenon Cohen is describ-
ing is “pleiotropy,” the capacity of a single gene to have multiple,
seemingly unrelated effects. It is one of the complexities of dis-
ease that has repeatedly frustrated medical researchers in their
quest for therapies for the most stubborn illnesses.
Cohen not only appreciates pleiotropy’s significance: He be-
lieves that Pharnext and other drugmakers may soon exploit it—
with a powerful boost from artificial intelligence. By embracing
the body’s complexity, and by using A.I. to more methodically
analyze and map the way the chain reactions of disease sweep
through the body, he hopes to develop combinations of drugs
tuned to attack a plethora of medical conditions.
Cohen and his team are also applying A.I. to search for
therapies that leverage “repurposing”—combining existing drugs
in ways that give them therapeutic powers that each lacks in
isolation. Their long-term goal is a drug pipeline that is far more
efficient than Big Pharma’s notoriously slow R&D departments—
streamlined by machine learning. Cohen’s sleepy gaze widens with
enthusiasm when he describes how it’s all coming along. “Très
bien,” he says. “Très économique.”
Running in the same race as Pharnext are companies rang-
ing from giants like Google and IBM to startups such as Insilico
Medicine, Recursion Pharmaceuticals, and BenevolentAI. All are
deeply invested in the tools of A.I., using them to analyze mil-
lions of examples of drug and patient data and tease out patterns
of significance. But Pharnext, founded in 2007, predates most
of those competitors by several years—and has a longer head
start when one factors in Cohen’s decades of earlier research in
genomics and pleiotropy.
And perhaps most important, Pharnext’s application of A.I.
to medical problems over the course of more than a decade has
finally reached a critical inflection point. In October, Pharnext
reported positive results for a Phase III trial in humans of one of
its drug combinations. The compound is PXT3003, a treatment
for a neurodegenerative condition called Charcot-Marie-Tooth
disease (CMT), a rare disorder for which no cure has been found.
The primary cause of CMT is duplication of a single gene, but
a whole cascade of bad things ensues “downstream” from that
mutation. Schwann cells, which protect nerves, regress into stem
cells that don’t do their job. Axons in the nerves begin to die off.
Muscles can’t be controlled, and they shrink as a consequence.
According to Pharnext, its Phase III results (which have not
yet been peer-reviewed) showed CMT not merely stabilizing un-
der PXT3003 but also being reversed, as cells began regenerat-
ing. Previous treatments, Cohen says, had managed only to slow
patients’ decline. Under PXT3003, patients showed statistically
significant improvement on two measures of disability. Based onIN THE ELEGANT QUIET of the café at the Church
of Sweden, a narrow Gothic-style building in
Midtown Manhattan, Daniel Cohen is taking
a break from explaining genetics. He moves
toward the creaky piano positioned near the
front door, sits down, and plays a flowing, flaw-
less rendition of “Over the Rainbow.”
If human biology is the scientific equivalent
of a complicated score, Cohen has learned
how to navigate it like a virtuoso. Cohen was
the driving force behind Généthon, the French
laboratory that in December 1993 produced
the first-ever “map” of the human genome. He
essentially introduced Big Data and automa-
tion to the study of genomics, as he and his
team demonstrated for the first time that it
was possible to use super-fast computing to
speed up the processing of DNA samples.
Scientists worldwide have built on Cohen’s
insights, and Cohen himself, an MD with a
Ph.D. in immunology, has gone on to suc-
cess as a researcher and pharma executive.
But a quarter-century later, genomics has
yielded few of the kinds of paradigm-changing
medical breakthroughs that many of its early
innovators hoped for. Today, as chief execu-
tive and founder of Paris-based drug startup
Pharnext, Cohen is striving to understand why
that rainbow hasn’t led to a pot of gold.
“Any protein in the body has many different
functions, not only one,” he says, returning
from the piano to talk with me, “just as you
are a person who has many functions in the
In theory, with repurposing “you don’tneed to design new drugs,” says Cohen.“With 50 drugs, we can treat everything.”