point-of-care diagnostics
Creative Minds: Rapid Testing for Antibiotic Resistance
Posted on by Dr. Francis Collins
Ahmad (Mo) Khalil
The term “freeze-dried” may bring to mind those handy MREs (Meals Ready to Eat) consumed by legions of soldiers, astronauts, and outdoor adventurers. But if one young innovator has his way, a test that features freeze-dried biosensors may soon be a key ally in our nation’s ongoing campaign against the very serious threat of antibiotic-resistant bacterial infections.
Each year, antibiotic-resistant infections account for more than 23,000 deaths in the United States. To help tackle this challenge, Ahmad (Mo) Khalil, a researcher at Boston University, recently received an NIH Director’s New Innovator Award to develop a system that can more quickly determine whether a patient’s bacterial infection will respond best to antibiotic X or antibiotic Y—or, if the infection is actually viral rather than bacterial, no antibiotics are needed at all.
Portable System Uses Light to Diagnose Bacterial Infections Faster
Posted on by Dr. Francis Collins
Caption: PAD system. Left, four optical testing cubes (blue and white) stacked on the electronic base station (white with initials); right, a smartphone with a special app to receive test results transmitted by the electronic base station.
Credit: Park et al. Sci. Adv. 2016
Every year, hundreds of thousands of Americans acquire potentially life-threatening bacterial infections while in the hospital, nursing home, or other health-care settings [1]. Such infections can be caused by a variety of bacteria, which may respond quite differently to different antibiotics. To match a patient with the most appropriate antibiotic therapy, it’s crucial to determine as quickly as possible what type of bacteria is causing his or her infection. In an effort to improve that process, an NIH-funded team is working to develop a point-of-care system and smartphone app aimed at diagnosing bacterial infections in a faster, more cost-effective manner.
The portable new system, described recently in the journal Science Advances, uses a novel light-based method for detecting telltale genetic sequences from bacteria in bodily fluids, such as blood, urine, or drainage from a skin abscess. Testing takes place within small, optical cubes that, when placed on an electronic base station, deliver test results within a couple of hours via a simple readout sent directly to a smartphone [2]. When the system was tested on clinical samples from a small number of hospitalized patients, researchers found that not only did it diagnose bacterial infections about as accurately and more swiftly than current methods, but it was also cheaper. This new system can potentially also be used to test for the presence of antibiotic-resistant bacteria and contamination of medical devices.
Shining Light on Ebola Virus for Faster Diagnosis
Posted on by Dr. Francis Collins
Caption: A rapid Ebola detection system consisting of a microfluidic chip (left) and an optofluidic chip (right), connected by a curved tube (center).
Credit: Joshua Parks, University of California, Santa Cruz
Many lessons were learned during last year’s devastating outbreak of Ebola virus disease in West Africa. A big one is that field clinics operating in remote settings desperately need a simple, rapid, and accurate test that can tell doctors on the spot—with just a drop of blood—whether or not a person has an active Ebola infection.
A number of point-of-care tests are under development, and it’s exciting to see them moving in the right direction to fill this critical need [1]. As a recent example, a paper published in Nature Scientific Reports by a team of NIH-supported researchers and colleagues shows early success in rapid Ebola detection with an automated lab on a chip [2]. The hybrid system, which combines microfluidics for sample preparation with optofluidics for viral detection, identifies Ebola at concentrations that are typically seen in the bloodstream of an infected person. It also distinguishes between Ebola and the related Marburg and Sudan viruses, suggesting it could be used to detect other infectious diseases.
