PERSPECTIVE article
Front. Cell. Infect. Microbiol.
Sec. Antibiotic Resistance and New Antimicrobial drugs
Volume 15 - 2025 | doi: 10.3389/fcimb.2025.1611857
This article is part of the Research TopicAdvances in Bacteriophage Research & Development with Therapeutic ApplicationsView all 5 articles
Optimizing Phage Therapy with Artificial Intelligence: A Perspective
Provisionally accepted
- 1Department of Medicine, Division of Infectious Diseases and Global Public Health, University of California, San Diego, La Jolla, United States
- 2Department of Ecology, Behavior and Evolution, University of California, San Diego, La Jolla, United States
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Phage therapy is emerging as a promising strategy against the growing threat of antimicrobial resistance, yet phage and bacteria are incredibly diverse and idiosyncratic in their interactions with one another. Clinical applications of phage therapy often rely on a process of manually screening collections of naturally occurring phages for activity against a specific clinical isolate of bacteria, a labor-intensive task that is not guaranteed to yield a phage with optimal activity against a particular isolate. Herein, we review recent advances in artificial intelligence (AI) approaches that are advancing the study of phage-host interactions in ways that might enable the design of more effective phage therapeutics. In light of concurrent advances in synthetic biology enabling rapid genetic manipulation of phages, we envision how these AI-derived insights could inform the genetic optimization of the next generation of synthetic phages.
Keywords: phage therapy, artificial intelligence, Phage specificity, Gene discovery, Phage engineering, machine learning, Synthetic Biology
Received: 14 Apr 2025; Accepted: 30 Apr 2025.
Copyright: © 2025 Doud, Robertson and Strathdee. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Steffanie Strathdee, Department of Medicine, Division of Infectious Diseases and Global Public Health, University of California, San Diego, La Jolla, United States
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.