MSF Foundation, a specialized entity created by Doctors Without Borders/Médecins Sans Frontières (MSF) and dedicated to innovation, has been awarded a $1.3 million Google Artificial Intelligence Impact Challenge grant to develop a smartphone app that would help doctors and clinicians diagnose antibiotic resistance in low-resource settings.
The app, known as ASTapp, would use image processing and artificial intelligence technology to make it easier for non-expert microbiologists to interpret tests that measure resistance to antibiotics. This will help guide clinicians on the best course of treatment and better ensure that patients are receiving the most appropriate antibiotics.
Antibiotic resistance (ABR) has been recognized as an international public health challenge and is expected to be the leading cause of death globally in 50 years. One of the main problems fueling resistance is the difficulty in identifying it in parts of the world lacking diagnostic laboratories or the capacity to read and interpret antibiogram tests. These tests determine the susceptibility of bacteria to available antimicrobial medicines and require interpretation by microbiologists—specialists who are often hard to find in low-resource settings. This means that antibiogram results given to clinicians often do not accurately reflect a patient’s sensitivity or resistance to antibiotics. This leads to use of broad spectrum antibiotics and inadequate treatment that is not adapted to a patient’s specific sensitivity and resistance profile.
MSF Foundation—an MSF entity which initiates, funds, and manages technology and innovation projects to improve care for patients—began an app-based project a year ago to provide health care workers in low-resource settings better options to treat infections. This app would offer MSF staff and other health professionals an offline method to read and interpret antibiotic resistance. Specifically, the app would allow non-ABR expert staff to analyze antibiogram pictures on smartphones or tablets and provide advice for appropriate patient treatment.