Smartphone device can diagnose bacterial infections
MGH researchers are testing a system for identifying bacterial infections that could save lives, speed recovery and reduce healthcare costs.
Ralph Weissleder, MD, PhD, director of the Massachusetts General Hospital Center for Systems Biology, and Hakho Lee, PhD, also a principal investigator at the centre, are leading a team of researchers that has created such a device. Called Polarization Anisotropy Diagnostics (PAD), it has shown promising results in a small study.
‘We developed a system that is practical and easy to use,’ Dr. Weissleder says. ‘PAD takes the guesswork out of treating patients for bacterial infections.’
The PAD device is about the size of a Rubik’s Cube. And it can make a diagnosis within two hours of receiving a patient sample. By comparison, getting similar results back from a testing lab, can take anywhere from a couple of days to a few weeks. In the meantime, doctors must make a diagnosis based on the patient’s symptoms.
Dr. Weissleder gives this example: A patient comes to the hospital shivering, short of breath and in extreme pain. Healthcare providers suspect a bacterial infection is causing sepsis, a life-threatening infection. They immediately begin treatment, which includes antibiotics-but they don’t know yet which bacteria are making the patient sick. So they prescribe the antibiotic most likely to help or give several types of antibiotics.
When the lab results return two weeks later, the healthcare providers learn if they suspected the right bug. If they were wrong, they must change the course of antibiotics.
But if PAD identifies the bacteria within two hours, physicians can prescribe the right antibiotics sooner. Patients can recover faster, with fewer side effects.
To use the PAD device, a sample from the patient is placed into a tiny vial along with a special detection probe. The vial is slid into a box that snaps onto the PAD cube.
Inside the box, probes search the patient sample for matching bacterial DNA. When a match is detected, the probes glow, sending a signal that specific genes are present. The system uses those genes to identify the bacteria. That data is sent to a smartphone.
On the smartphone screen, PAD identifies whether a bacterial infection is present. The researchers’ current device can already specifically identify nine common infections and determine whether the one involved is resistant to antibiotics.
‘I think over the next couple of years, there will be a switch to rapid diagnostics like our new device.’
In a small study, the team tested its device against the gold standard of having a lab grow a bacteria culture to identify it. PAD did just as well as a lab culture in testing for the presence of the bacteria E. coli, Klebsiella, Acinetobacter, Pseudomonas and Staphylococcus aureus, and in reporting how much bacteria was present and whether it was antibiotic-resistant.
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