In studies, the automated microbial susceptibility testing device for smartphone performed with 98.2% accuracy, meeting FDA criteria
Imagine doing antimicrobial susceptibility testing outside a clinical laboratory. That’s the goal of researchers on the West Coast who are developing a smartphone-based diagnostic device with the capability of performing this type of point-of-care testing (POCT).
This new mobile POCT device is under development at the University of California-Los Angeles (UCLA). It promises to bring antimicrobial susceptibility testing—a routine procedure in the most medical laboratories—to remote, resource-limited areas of the world.
The UCLA researchers hope that cost-effective, simple, and reliable diagnostic testing like this smartphone application might one day be a common resource for physicians in developing countries who lack access to medical laboratories.
“This work is extremely important and timely, given that drug-resistant bacteria are increasingly becoming a global threat rendering many of our first-line antibiotics ineffective. Our new smartphone-based technology can help put laboratory-quality testing into much wider adoption, especially in resource-limited regions,” said Aydogan Ozcan, PhD, Chancellor’s Professor of Electrical Engineering and Bioengineering at UCLA Henry Samueli School of Engineering and Applied Science.
Researchers Motivated by Lack of Testing
Ozcan and his colleagues were motivated by a lack of antimicrobial susceptibility testing due to technology challenges, high costs, and no professional training in resource-challenged areas worldwide, according to their published study in Scientific Reports.
These factors “greatly contribute to high mortality and the global spread of multi-drug resistant organisms. The goals of antimicrobial susceptibility testing include detection of possible drug resistance and assurance of susceptibility to drugs of choice for each particular infection,” noted the study authors.
How Does It Work?
The team created an inexpensive attachment for smartphones that can perform automated antimicrobial susceptibility testing. Here’s how the device is designed to work in clinical settings, according to the UCLA news release:
• The device that connects to a smartphone has a plate that holds up to 96 wells for testing;
• Each sample is illuminated by an array of light-emitting diodes (LEDs);
• The smartphone’s camera senses small changes in the light transmission of each well containing a different dose selected from a panel of antibiotics;
• Images go to a server to automatically perform antimicrobial susceptibility testing;
• Results are reported to the smartphone in about one minute.
Results with 98.2% Accuracy
The mobile test reader met the US Food and Drug Administration (FDA) criteria for lab testing with a 98.2% accuracy rate. The UCLA clinical tests targeted Klebsiella pneumonia, a bacterium with highly resistant antimicrobial profiles, noted the researchers.
“This species of bacteria can exhibit highly resistant antimicrobial profiles and contain members of the Carbapenem-resistant Enterobacteriaceae with a very high mortality rate in disease states including sepsis and pneumonia,” the researchers wrote in Scientific Reports.
Study results were depicted as either susceptible to antibiotics or resistant to them. In other words, a susceptible designation implied the organisms causing the disease responded to therapy with the tested concentration of drug, and the resistant tag implied otherwise, noted an article in CrazyEngineers.
“We validated the capability of our cellphone-based antimicrobial susceptibility testing system to perform highly accurate minimum inhibitory concentration determination and drug susceptibility interpretation, greatly exceeding the FDA-defined criteria for susceptibility testing with clinical isolates of the bacterium Klebsiella pneumonia,” the researchers concluded in Scientific Reports.
Broadening Test Use, Reducing Costs, Faster Results
The UCLA smartphone diagnostic device is another example of POCT technology that, were it to become widely available, would greatly affect clinical laboratories and patient care. According to the researchers, in resource-limited settings, a lab technician trained in the use of the device could replace an expert diagnostician. But what about medical laboratories around the world?
“The mobile reader could eliminate the need for trained diagnosticians to perform antimicrobial susceptibility testing, reduce the cost barrier for routine testing, and assist in tracking of bacterial resistance globally,” said Omai Garner, PhD, Health Sciences Assistant Clinical Professor and Associate Director Clinical Microbiology at UCLA Health System. Garner collaborated with Ozcan on the research.
Research partner, Dino Di Carlo, PhD, Professor of Bioengineering in Engineering at UCLA, added another advantage: “There’s a possibility of examining bacterial growth in the presence of a drug at an earlier time point than is currently read [about 24 hours]. This could allow for a more rapid turnaround time of the results to the physician, which might help save lives,” he said in the UCLA news release.
Ozcan Research Worth Watching
This new UCLA study by Ozcan et al appears to be another step in the professor’s pursuit of research addressing worldwide health challenges. Dark Daily readers might recall previous e-briefings about his other innovative developments including:
• Integration of imaging capabilities into a lab-on-a-chip format (see Dark Daily, “Lab-on-a-Chip Diagnostics: When Will Clinical Laboratories See the Revolution?,” September 9, 2016); and
• An inexpensive smartphone device to produce holograph images of tissue samples at the cellular level (see Dark Daily, “UCLA Researchers Develop Lens-Free Smartphone Microscope, Pathologists May Be Able to Take the Clinical Pathology Laboratory Just About Anywhere,” July 12, 2015).
For pathologists and medical laboratory leaders, ongoing research by Ozcan is important to note. Ultimately, access to an easy-to-use automated diagnostic test reader attached to a smartphone could enable more doctors to make earlier diagnoses and begin treatments that could save many lives.
—Donna Marie Pocius