As data availability, technology advances, and increasingly sophisticated algorithms have brought expanded applications of artificial intelligence (AI) to the fore, modern medicine has become increasingly adept at putting machine learning into practice. Among the many AI-driven precision medicine research projects is one aimed at a common, intractable infectious disease: C. difficile.
The hospital-acquired intestinal pathogen affects 500,000 Americans each year—and its ranking as a significant cause of morbidity, mortality, and avoidable health care spending makes it a key target for health care quality improvement measures at Partners HealthCare and beyond. A core challenge as researchers seek better prevention, diagnosis, and treatment methods for the bacterium is the ever-changing ecosystem of trillions of microbes in the human microbiome.
“It’s not only the number of variables we’re measuring but also the complexity,” says Georg Gerber, MD, PhD, MPH, FASCP, chief of computational pathology in the Brigham and Women’s Hospital Department of Pathology and co-director of the Massachusetts Host-Microbiome Center.
Dr. Gerber has designed sophisticated AI models to circumvent this complexity and shed light on how the microbiota in the gut—beneficial microbes that colonize our bodies—may enable or thwart C. difficile infections in patients.
With that targeted data in hand, Dr. Gerber, with Lynn Bry, MD, PhD, director of the Partners Massachusetts Host-Microbiome Center, and Jessica Allegretti, MD, MPH, director of clinical trials in the Brigham’s Crohn’s and Colitis Center, identified which microbes in the gut prevent and treat C. difficile in animal models. “The set of bacteria we found can cure C. difficile in mice. It’s amazing—mice who are very sick fully recover,” says Dr. Gerber. “The next step will be clinical trials in people to see how well this works.”
More on the AI-fueled research into C. difficile and other conditions here.