AI discovers antibiotic to treat drug-resistant diseases for first time

Researchers used computer model that can screen more than a hundred million chemical compounds in a matter of days

Microbiologist explains global threat of antibiotic resistance

Scientists have used artificial intelligence to uncover new types of antibiotics in the face of growing concerns about resistance to the drugs.

A group of researchers from Massachusetts Institute of Technology (MIT) say their machine-learning algorithm was able to identify a powerful new antibiotic compound, capable of killing some of the world’s most problematic disease-causing bacteria.

They claim the technology is able to work more quickly and efficiently than existing systems, because it checks more than a hundred million chemical compounds in a matter of days to pick out potential antibiotics that kill bacteria.

The AI was trained specifically to track down possible antibiotic molecules known for being effective against E.coli growth.

“We’re facing a growing crisis around antibiotic resistance, and this situation is being generated by both an increasing number of pathogens becoming resistant to existing antibiotics, and an anaemic pipeline in the biotech and pharmaceutical industries for new antibiotics,” said MIT’s Professor James Collins, who is also co-founder of an antibiotic drug discovery firm EnBiotix.

“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.”

The molecule, named halicin, proved effective against E.coli, which did not develop any resistance to it during a 30-day treatment period on mice.

Researchers, who published their paper in the Cell journal, say they want to study halicin further in hope of developing it for use in humans.

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