How Artificial Intelligence helped biomedical engineers discover a new antibiotic
The AI community is buzzing this week at the news that a team of researchers at MIT we’re able to use machine-learning algorithms to identify a powerful new antibiotic compound.
The algorithm, which screened more than a hundred million chemical compounds in just a few short days, is said to kill some of the world’s most serious bacteria– those species which are resistant to all currently known antibiotics.
This is believed to be the first time that artificial intelligence has been used in this way to discover a new potential pharmaceutical treatment, and it’s a true testament to the possibilities of machine-learning technologies for solving new health crises.
“We wanted to develop a platform that would allow us to harness the power of artificial intelligence to usher in a new age of antibiotic drug discovery. Our approach revealed this amazing molecule which is arguably one of the more powerful antibiotics that has been discovered,” says James Collins, the Termeer Professor of Medical Engineering and Science in MIT’s Institute for Medical Engineering and Science (IMES) and Department of Biological Engineering.
“The machine learning model can explore, in silico, large chemical spaces that can be prohibitively expensive for traditional experimental approaches,” says Regina Barzilay, the Delta Electronics Professor of Electrical Engineering and Computer Science in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL).
Researchers used a machine-learning algorithm to identify a drug called halicin that kills many strains of bacteria. Halicin (top row) prevented the development of antibiotic resistance in E. coli, while ciprofloxacin (bottom row) did not.
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