Superbugs are microorganisms that have developed resistance to antibiotics and other medicines used to treat the infections they cause. These bacteria can cause serious diseases that are difficult to cure, such as pneumonia, tuberculosis or septicemia. According to some experts, superbugs could be the new pandemic of the 21st century, causing millions of deaths a year.
The problem of superbugs is due to the excessive and inappropriate use of antibiotics, both in humans and in animals. This causes the bacteria to be exposed to these drugs and mutate in order to survive. In addition, the rate of discovery of new antibiotics is very slow, making it difficult to find effective treatments for resistant infections .
However, a possible way out of this could be on the way thanks to AI, since researchers from McMaster University used this technology to find the elements capable of killing the Acinetobacter baumanniiwhich can infect wounds and cause pneumonia.
It is one of three superbugs that the World Health Organization has identified as a “critical” threat.
Dr Jonathan Stokes of McMaster University describes the bug as “public enemy number one” as it is “really common” to find cases where it is “resistant to almost all antibiotics.”
To create this antibiotic, they took thousands of drugs where the precise chemical structure was known, and manually tested them on Acinetobacter baumannii to see which one might slow him down or kill him. This information was fed into the AI so that it could learn the chemical characteristics of drugs that could attack the troublesome bacteria.
The AI was unleashed on a list of 6,680 compounds whose effectiveness was unknown. The results, published in Nature Chemical Biologyshowed that it took the AI an hour and a half to produce a shortlist.
The researchers tested 240 in the lab and found nine potential antibiotics. One of them was the incredibly powerful antibiotic abaucin.
Laboratory experiments showed that it could treat infected wounds in mice and was able to kill samples of A. baumannii of patients.
However, Dr. Stokes told me, “This is where the work begins.”
The next step is to refine the drug in the laboratory and then conduct clinical trials. He expects the first AI antibiotics could take until 2030 before they become available to prescribe.
“AI improves the rate, and in a perfect world, decreases the cost, with which we can discover these new classes of antibiotics that we desperately need,” Dr. Stokes told me.
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