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Many of the processes carried out in traditional chemistry labs searching for new drugs or drug targets can be sped up through factory-style automation—and in fact, “combinatorial chemistry” was a big boost for the field. But Alán Aspuru-Guzik, a theoretical chemist in the departments of chemistry and computer science at the University of Toronto, says “the transition to autonomy is what we really want.” Think of a “self-driving chemical lab” that uses big data, AI, and robotics to explore chemical space through a cycle of synthesis, characterization, and testing: that’s what happening both at Aspuru-Guzik’s Cambridge, MA-based startup Kebotix, in cooperation with commercial partners, and at his lab in Toronto, where he holds the Canada 150 Research Chair in Theoretical Chemistry. “We’re trying to put together the molecular Lego pieces, with a finite set of reactions and fragments,” Aspuru-Guzik says. “The art of being successful is not getting lost in an infinite forest of possibilities.”

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