ReviewFrontiers in cellular and infection microbiology2025
Optimizing phage therapy with artificial intelligence: a perspective.
Review in Frontiers in cellular and infection microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
29 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Evolutionary dynamics and research hotspots of phage applications againstFrontiers in microbiology · 2026Pooled it
- Precision phage therapy in the AI/ML era: a systematic review of discovery-to-clinical translation evidence.Frontiers in microbiology · 2026Pooled it
- Innovative Applications of Artificial Intelligence in Bacteriophage Research: A New Chapter in Future Medicine.Microorganisms · 2026Review
- Approaching the post-antibiotic era: phage therapy current practices and future horizons.mBio · 2026Review
- Structural Receptors and Host Adaptations Affecting the Bacteriophage Targeting ofMicroorganisms · 2026Review
- Bacteriophages AgainstViruses · 2026Review
- Phage as a prospective arsenal against superbugs.Molecular biology reports · 2026Review
- Artificial Intelligence in Bacteriophage Science: A Comprehensive Narrative Review of Applications, Challenges, and Translational Opportunities.Antibiotics (Basel, Switzerland) · 2026Review
- Bacteriophage therapy for multidrug-resistant bacterial infections: recent advances, clinical evidence, and translational challenges.Archives of microbiology · 2026Review
- AI-programmable therapeutics via metagenomic foundation models for rare phage-mediated autoimmune modulations: early translational risks and benefits.Annals of medicine and surgery (2012) · 2026Article
- Molecular Insights into Phage-Hydrogel Polymer Interactions Through Docking, Molecular Dynamics, and Machine Learning.Polymers · 2026Article
- From structure to design: experimental and AI-driven approaches in receptor-binding protein engineering for reprogramming phage host range.Archives of microbiology · 2026Review
- Nano-Enabled Delivery of Phage-Based Antibacterials Against ESKAPE Pathogens.Pharmaceutics · 2026Review
- Synthetic Biology of Plants and Microbes for Agriculture, Environment, and Future Applications.Chemical reviews · 2026Review
- Phage-Based Approaches to ChronicAntibiotics (Basel, Switzerland) · 2026Review
- Vancomycin resistance in gram-positive infections: evolutionary strategies of survival.Archives of microbiology · 2026Review
- Antimicrobial Resistance: How Can We Overcome the Problem?Antibiotics (Basel, Switzerland) · 2026Review
- Biofilm-associated antibiotic tolerance in the era of multidrug resistance: quorum-sensing mechanisms and emerging therapeutic strategies.Frontiers in cellular and infection microbiology · 2026Review
- Isolation and characterization of a novelFrontiers in cellular and infection microbiology · 2026Article
- Phage therapy againstFrontiers in microbiology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.