You are here
New System Detects Patient’s Antibiotic Resistance in 30 Minutes
Researchers at St. George’s University in London are working on a system that will reduce the time it takes to detect antibiotic resistance in patients from several days to just half an hour, according to a report from the university. The system consists of disposable cartridges used on a small desk-top device, which can sample urine and vaginal swabs, identify an infection, and detect resistance within 30 minutes of a patient visiting a hospital or clinic.
“This process of diagnosis has already been shown to be very reliable, and so we are confident that we will be able to identify which drugs to use to successfully treat the infection,” lead investigator Dr. Tariq Sadiq said. “Within one short visit, patients will get their diagnosis and a bespoke treatment. We believe that this test-and-treat method will reinforce patient and doctors’ confidence in the antibiotics chosen for treatment.”
Antibiotic resistance is a huge challenge to current medical practices, which rely heavily on the use of antibiotics, the researchers noted. Bacteria can become resistant to antibiotics in a number of ways through mutations of their own genes or by “ingesting” new resistant genes.
Increasing antibiotic resistance not only leads to treatment failure, but is also driving doctors towards using increasingly more potent antibiotics for simple infections. This cycle escalates the risk of bacteria developing resistance to these antibiotics, potentially reducing their use for the future.
The researchers at St. George’s have been testing the accuracy of identifying specific genetic mutations that indicate resistance for guiding appropriate treatment, and are ready to use their method in collaboration with rapid-testing technology developed by Atlas Genetics, a U.K.-based diagnostics company.
Atlas is integrating the new method of detection onto its point-of-care diagnostic device (the ioTM system) to provide both bacterial identification and antibiotic resistance data in a single 30-minute test. The project includes input from both health care professionals and patients regarding the design of the test and will conclude with a 1,000-patient clinical study, which is expected to be completed in 2017.
Source: St. George’s University of London; June 11, 2015.