Antibiotic resistance is one of the greatest challenges plaguing modern medicine. More than a hundred thousand people die every year because doctors cannot treat bacterial infections. However, there is an unexpected ally in this fight for lives, which can help to solve the problem of bacterial resistance to existing drugs. This ally is neural networks. Scientists from the Massachusetts Institute of Technology demonstrated that well-trained neural networks can successfully identify new antibiotics from millions of candidate molecules.
Why Many Antibiotics Are Becoming Ineffective
Simply put, the mechanism of bacterial adaptation to antibiotics can be described as follows: random mutations constantly occur in bacterial DNA, and due to their huge number, there is always a probability that some of these mutations will help particular bacteria survive in new conditions. The rest of the population might die, but the surviving ones will quickly multiply and take their place. Bacteria are unlikely to survive boiling or intense irradiation, but many of them no longer respond to antibiotics. Developing resistance requires a certain period of time, and with each year, less and less time is needed. For example, by the early 1970s, most of the gonococcus bacteria had developed high-level resistance to antibiotics of the penicillin group.
