How AI can slow the rise of antibiotic-resistant “superbugs”
How AI can slow the rise of antibiotic-resistant “superbugs”
César de la Fuente-Núñez,Henry Skinner,Christina F Yen
TLDR
Artificial intelligence, machine learning, and related technologies have the potential to accelerate antimicrobial drug discovery and development—and improve clinical care for patients suffering with AMR infections.
Abstract
ABSTRACT Antimicrobial-resistant (AMR) “superbugs” contribute to more than 4.5 million deaths globally per year and threaten to make common medical procedures such as surgery and chemotherapy less safe. Despite the burden of AMR, very few innovative antibiotics, antifungals, and other antimicrobial therapies are in development, and private investment is insufficient. Artificial intelligence, machine learning, and related technologies have the potential to accelerate antimicrobial drug discovery and development—and improve clinical care for patients suffering with AMR infections. To fully reap the benefits, however, policy and market dynamics must evolve alongside the technology.