Antibiotics have revolutionized healthcare, allowing routine surgical procedures to continue without the excessive fear of devastating infections and ending a huge variety of nasty diseases that would previously have killed or disabled millions of people each year. . However, these advances are being eliminated slowly but surely by antibiotic resistance, which increases every year.
“Many types of bacteria are constantly evolving to develop antibiotic resistance. This is an urgent issue for hospitals around the world, while diagnostic and sensor technology has been slow to adapt, “Mohammad Zarifi, a researcher involved in the study, said in a press release.
The main problem is the inappropriate use of antibiotics and part of the solution is to choose the right antibiotic for each patient. After all, it is useless to prescribe an antibacterial agent for an infection caused by bacteria that are already resistant to that agent. This is where personalized antibiotic therapy comes in, which is to test a sample of disease-causing bacteria for a specific patient to determine their antibiotic susceptibility before prescribing a suitable antibiotic.
The problem is that this process is time consuming and expensive, often taking 48 hours, which is no joke if you have a serious infection. “Longer waiting times can significantly delay the treatments patients receive, which can lead to medical or even fatal complications. This method demonstrates the requirement for a reliable, fast and cost-effective screening tool,” he said. Zarifi.
This new technology is based on the detection of microwaves as a means to control the growth of the bacterial sample in the presence of different concentrations of antibiotic. The system is sensitive enough that it can detect differences in bacterial growth that are invisible to the human eye, and achieves this through a split-ring microwave resonator. The charged substances released by bacterial cells, when affected by antibiotics, can help with the measurement, but in essence, the resonant response of the split ring is affected by the growth of a bacterial sample on agar.
Ultimately, researchers hope to incorporate an element of artificial intelligence into the technology to help detect and predict personalized antibiotic treatment.
“Our ultimate goal is to reduce the inappropriate use of antibiotics and improve the quality of patient care,” Zarifi said. “The more quality tools health professionals have at their disposal, the greater their ability to fight bacteria and viruses.”