A group of scientists claims to have found, thanks to the help of Artificial Intelligence, a new type of antibiotic able to face one of the three drug resistant superbugs that the WHO identifies as “critical threats”. It should be noted that resistance to antibiotics has become one of the main causes of death in the world. Along these lines, a study published in The Lancet highlights horrifying facts, such as that antimicrobial resistance was the direct cause of at least 1.27 million deaths worldwide in 2019.
It does not seem that the situation is going to improve. The UN anticipates that if we do not solve this problem, the number of deaths caused by superbugs it could increase to 10 million in 2050. That is why a large number of research teams are working to find a remedy against this threat. In this case, through new technologies such as AI applied to science.
In this study published in Nature Chemical Biology, the team of researchers from Canada and the United States claims that AI has “the power to greatly accelerate the discovery of new drugs.” And so, during his research, this artificial intelligence allowed reduce a list of thousands of chemical compounds until leaving a few that were analyzed in the laboratory. The result was a powerful experimental antibiotic called abaucin, which will need to undergo further testing before it can be used as a treatment.
Scientists say that when tested this new antibiotic on the skin of mice experimentally infected with the superbug, this drug controlled the growth of the bacteria, suggesting that the method could be used to create antibiotics tailored to combat other drug-resistant pathogens.
This superbug is the “public enemy number one”
The researchers focused on one of the most problematic species of bacteria: the Acinetobacter baumannii. This species causes difficult-to-treat skin, blood, or respiratory infections (pneumonia).
For this reason, the United States Centers for Disease Control and Prevention stated in 2019 that conditions due to Acinetobacter baumanii they were the ones who “needed the most” new types of antibiotics to deal with them. In fact, a recent study of hospitalized patients with infections with this bacterium resistant to even powerful carbapenem antibiotics found that 1 in 4 had died within a month of their diagnosis.
Dr. Jonathan Stokes, a researcher at McMaster University in Canada and co-author of the study, describes this superbug as the “public enemy number one”since it is “really common” to find cases in which it is “resistant to almost all antibiotics”.
Finding the medicine to defeat her
To find the new antibiotic, the first thing the researchers did was “train” the AI. In this way, they fed it information from thousands of drugs whose precise chemical structures were known and which they had manually tested on Acinetobacter baumannii, to identify which could slow down or kill the superbug. The AI thus learned the chemical characteristics of the drugs that could attack the bacteria.
Later, the Intelligence elaborated a list of 6,680 compounds whose efficacy was unknown. It took an hour and a half for the tool to narrow down the list, after which the researchers tested 240 substances in the lab and found nine potential antibiotics. One of them was abaucin, whose tests showed that can treat infected wounds in mice and kill samples of A. baumannii in patients.
“This is where the work begins,” Stokes continues, as the next step will be to refine the drug in the laboratory and then conduct clinical trials. The scientist warns that for the first antibiotics discovered with the help of AI may be prescribed, perhaps we will have to wait until 2030. Interestingly, this experimental antibiotic had no effect on other species of bacteria and only works on A. baumannii.
This does not usually happen. Typically, many antibiotics block and kill pathogens indiscriminately. Including beneficial bacteria that live in the gut or on the skin. Thus, the researchers believe that the precision of abaucin will make it difficult for drug resistance to emerge by having a very specific target. If there were more antibiotics that worked with this precision, the researchers say, “it could prevent bacteria from becoming resistant”. They would also cause fewer side effects.