Artificial intelligence is involved in the process.
Scientists from McGill University have created a diagnostic system capable of identifying the type of bacteria and selecting effective antibiotics against them in just 36 minutes. This is a significant breakthrough in the fight against antibiotic resistance, as traditional laboratory methods take two to three days, forcing doctors to prescribe treatment without accurate data.
According to the researchers, the development comes at a particularly important time – amid the growing crisis of bacterial resistance to antibiotics, as more infections become difficult to treat.
The system, created by the teams and named QolorPhAST, is a compact automated device based on the color change of nanosensors in response to the metabolic activity of live bacteria.
Thanks to the rapid color reaction and image analysis using AI algorithms, the system can simultaneously determine the type of bacteria and their sensitivity to antibiotics without the need for prolonged cultivation. In a blind clinical trial involving 54 urine samples, QolorPhAST demonstrated high accuracy compared to traditional laboratory tests, significantly reducing the time to obtain results.
The device is compact, low-cost, and easy to use, opening up possibilities for widespread application – for example, in the diagnosis of urinary tract infections and sexually transmitted infections. The developers are already working on commercializing the technology and expect to bring it to market.
Leave a comment