“With an effective cure for the coronavirus yet to be found and fears of antibiotic resistance on the rise, the use of AI in drug discovery comes at the right time. Instead, it will work in unison with clinicians and other medical staff, unburdening them from hours of manual processes by saving them vital time to treat patients. “That being said, it will by no means make human doctors redundant. “The technology is now more accurate than humans in diagnosing brain tumours, and its use in discovering new antibiotics is a sign of its widening scope,” he said. ![]() They believe the model could also be used to design new drugs, based on what it has learned about chemical structures that enable drugs to kill bacteria.ĭata scientist Mark Frankish at SAS UK & Ireland said the discovery marks a “huge step forward” for the applications of AI in healthcare. The researchers also identified several other promising antibiotic candidates, which they plan to test further. Using a different machine-learning model, the researchers also showed that this molecule would likely have low toxicity to human cells. Once the model was trained, the researchers tested it on a library of about 6,000 compounds and picked out one molecule that was predicted to have strong antibacterial activity, and had a chemical structure different from any existing antibiotics. The researchers train the algorithm on about 2,500 molecules that are already known to be effective at killing E. The new machine learning method could make it easier to find new drugs in future. Over the past few decades, very few new antibiotics have been developed, and most of those newly approved antibiotics are slightly different variants of existing drugs.Ĭurrent methods for screening new antibiotics are often prohibitively costly, require a significant time investment, and are usually limited to a narrow spectrum of chemical diversity. They hope to eventually be able to use the drug on humans. 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. “Our approach revealed this amazing molecule which is arguably one of the more powerful antibiotics that has been discovered.” He added: “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. “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 antibiotic drug discovery firm EnBiotix. It was trained specifically to track down possible antibiotic molecules known for being effective against E.coli growth. The group of researchers from Massachusetts Institute of Technology (MIT) claim the technology is able to work more quickly and efficiently than existing efforts, because it checks more than a hundred million chemical compounds in a matter of days to pick out potential antibiotics that kill bacteria. It also cleared infections in two different mouse models. ![]() ![]() In laboratory tests, the drug killed many of the world’s most problematic disease-causing bacteria, including some strains that are resistant to all known antibiotics.
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