Scientists have discovered that the right combinations of antibiotics can significantly slow the development of bacterial drug resistance. A study published in The Lancet Microbe showed that certain pairs of drugs can exploit a feature of microbial evolution: when a bacterium becomes resistant to one antibiotic, it may simultaneously become more sensitive to another. This phenomenon, known as collateral sensitivity, could become an important tool in the fight against antibiotic resistance.

Antibiotic resistance is considered one of the most serious threats to global health. Bacteria gradually evolve and acquire defense mechanisms against drugs, making infections increasingly difficult to treat. In some cases, even common bacterial illnesses become hard to manage. For this reason, researchers are looking not only for new drugs but also for ways to use existing antibiotics more effectively.

In the new study, scientists analyzed massive datasets on bacterial infections and their susceptibility to various antibiotics. They used national databases containing test results from hundreds of thousands of bacterial samples collected in medical laboratories. This large scale allowed researchers to identify patterns: in some cases, resistance to one drug was accompanied by increased sensitivity to another.

These findings enabled the creation of a map of potentially useful antibiotic combinations. Some of the identified pairings were already known from laboratory experiments, but the analysis of clinical data revealed new combinations that had not been previously considered. According to the researchers, the correct sequencing or combining of such drugs could reduce the likelihood that bacteria will adapt and develop resistance.

The researchers emphasize that these results still require further validation—both in laboratory models and clinical trials. Nevertheless, the work demonstrates that large medical databases can be valuable not only for monitoring the rise of bacterial resistance but also for identifying new strategies to treat infections. If these approaches prove effective, they could extend the lifespan of existing antibiotics and slow the spread of resistant bacterial strains.