New antibiotic discovered by AI for the first time

pharmafile | February 21, 2020 | News story | Medical Communications AI, AI Clinical Trials, AI Drugs, AI antibiotics, MIT, algorithm, clinical trials 

MIT researchers have identified a new antibiotic compound using a machine-learning algorithm.

In the laboratory tests, the drug killed many of the world’s most problematic disease-causing bacteria, including some strains that have been so far resistant to all known antibiotics. These included Acinetobacter baumannii and Enterobacteriaceae which are two of the three high-priority pathogens that the World Health Organization rank as critical for new antibiotics to target.

The algorithm was purposely designed to pick out potential antibiotics that kill bacteria using different mechanisms than those of existing drugs. To do this, they fed the program information on the atomic and molecular features of nearly 2,5000 drugs and natural compounds, and how well or not the substance blocked the growth of the bug E coli.

Once the algorithm had learned what molecular features made for good antibiotics, the scientist set it to work on a library of more than 6,000 compounds under investigation for treating various human diseases. The algorithm focused on compounds that looked effective but unlike existing antibiotics, boosting the chances that the drugs would work in new ways the bug had not developed a resistance to.

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, said: “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.”

Conor Kavanagh


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