Peer-Reviewed Publication
Phys Rev Lett2025;135(3):030001.July 18, 2025Journal Article
Essay: Using Machine Learning for Antibiotic Discovery.
Cesar de la Fuente-Nunez1,2,3,4, James J Collins5,6,7
1University of Pennsylvania, Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, Philadelphia, Pennsylvania 19104, USA.
2University of Pennsylvania, Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, Philadelphia, Pennsylvania 19104, USA.
3University of Pennsylvania, Department of Chemistry, School of Arts and Sciences, Philadelphia, Pennsylvania 19104, USA.
4University of Pennsylvania, Penn Institute for Computational Science, Philadelphia, Pennsylvania 19104, USA.
5Massachusetts Institute of Technology, Institute for Medical Engineering and Science and Department of Biological Engineering, Cambridge, Massachusetts 02139, USA.
6Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts 02115, USA.
7Broad Institute of MIT and Harvard, Infectious Disease and Microbiome Program, Cambridge, Massachusetts 02142, USA.
Abstract
Antimicrobial resistance is a critical global health challenge and one of the World Health Organization's top ten public health threats. The alarming rise of drug-resistant pathogens threatens to usher in a postantibiotic era where common infections could once again become fatal. Despite the urgency, traditional discovery methods are time-consuming, expensive, and insufficient to keep pace with ra…
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