A simple, inexpensive attachment could help to expand testing to regions with limited resources. A team of UCLA researchers has developed an automated diagnostic test reader for antimicrobial resistance using a smartphone. The technology could lead to routine testing for antimicrobial susceptibility in areas with limited resources.
Antimicrobial-resistant bacteria are posing a severe threat to global public health. They are becoming more common in bacterial pathogens responsible for high-mortality diseases such as pneumonia, diarrhea and sepsis. Part of the challenge in combatting the spread of these organisms has been the limited ability to conduct antimicrobial susceptibility testing in regions that do not have access to labs, testing equipment and trained diagnostic technicians to read such tests.
The UCLA researchers have developed a simple and inexpensive smartphone attachment that could run automated antimicrobial susceptibility testing in regions that do not have access to labs, testing equipment and trained diagnostic technicians to read them.
The Project:
“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,” said Aydogan Ozcan, Chancellor’s Professor of Electrical Engineering and Bioengineering at the UCLA Henry Samueli School of Engineering and Applied Science. “Our new smartphone-based technology can help put laboratory-quality testing into much wider adoption, especially in resource-limited regions.”
This collaborative interdisciplinary project involved the UCLA research labs of three professors — Ozcan; Omai Garner, an assistant professor of pathology and laboratory medicine in Health Sciences; and Dino Di Carlo, a professor of bioengineering in Engineering.
The Device:
The UCLA device connects to a smartphone and has a plate that can hold up to 96 wells for testing. An array of LEDs illuminates the sample and then the phone’s camera is used to sense small changes in light transmission of each well containing a different dose selected from a panel of antibiotics. Images are sent to a server to automatically perform antimicrobial susceptibility testing and the results are returned to the smartphone in a minute.
The lowest concentration of antibiotic that prevented the growth of bacteria is used to track drug resistance. A criterion — that is susceptible to antibiotics or resistant to them — is assigned to each bacteria/drug combination to guide the physician in treatment decisions. A susceptible result indicates that the organisms that have infected the patient should respond to therapy, while a resistant organism will not be inhibited by the concentrations of antibiotic achieved with normal dosages used for that drug.
This could eliminate the need for trained personnel to interpret the result, Garner said. Di Carlo added that, “An additional advantage of this technology is the 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.”