Artificial intelligence and molecule machine join forces to generalize automated chemistry
Artificial intelligence, “building-block” chemistry and a molecule-making machine teamed up to find the best general reaction conditions for synthesizing chemicals important to biomedical and materials research – a finding that could speed innovation and drug discovery as well as make complex chemistry automated and accessible.
With the machine-generated optimized conditions, researchers at the University of Illinois Urbana-Champaign and collaborators in Poland and Canada doubled the average yield of a special, hard-to-optimize type of reaction linking carbon atoms together in pharmaceutically important molecules. The researchers say their system provides a platform that also could be used to find general conditions for other classes of reactions and solutions for similarly complex problems. They reported their findings in the journal Science.
“Generality is critical for automation, and thus making molecular innovation accessible even to nonchemists,” said study co-leader Dr. Martin D. Burke, an Illinois professor of chemistry and of the Carle Illinois College of Medicine, as well as a medical doctor. “The challenge is the haystack of possible reaction conditions is astronomical, and the needle is hidden somewhere inside. By leveraging the power of artificial intelligence and building-block chemistry to create a feedback loop, we were able to shrink the haystack. And we found the needle.”