Phage Genomics and Bioinformatics in Therapeutic Development: Evidence Limits, Validation Gates, and Translational Decision-Making

Abstract

Background/Objectives: Antimicrobial resistance has renewed interest in live therapeutic phages, including engineered candidates and defined phage cocktails, as antibacterial strategies. However, clinical translation requires evidence extending beyond phage isolation and computational prediction. This review examines how phage genomics and bioinformatics can support phage-based antibacterial development while remaining aligned with pharmaceutical requirements for safety, quality, pharmacology, and clinical validation. Methods: This narrative review synthesizes the literature on the generation, interpretation, and experimental validation of genomic and bioinformatic evidence for live therapeutic phages. Representative approaches for viral identification, genome-quality assessment, annotation, comparative genomics, lytic–temperate lifestyle classification, host prediction, receptor analysis, antiphage-defence profiling, and artificial-intelligence-assisted prioritization were evaluated according to their outputs, principal failure modes, validation requirements, and supported development decisions. Results: Current tools address distinct analytical tasks. Examples include VIBRANT and geNomad for viral identification, CheckV and PhageTerm for genome-quality and termini assessment, Pharokka, PHANOTATE, and PHROGs for gene prediction and annotation, PhageAI, BACPHLIP, and PhaTYP for lytic–temperate lifestyle prediction, iPHoP and CRISPR spacer matching for host prioritization, and PADLOC and DefenseFinder for bacterial defence profiling. Their outputs differ in taxonomic resolution, reference coverage, training-data dependence, and biological interpretation. The review maps these outputs to proportionate validation requirements while integrating formulation and PK/PD context, sequence-to-product traceability, intellectual-property documentation, minimum-information reporting, and resistance-responsive redesign. Conclusions: This review presents a practical sequence-to-product framework for interpreting contemporary phage-bioinformatics methods. By separating computational discovery from isolate-level activity, product quality, pharmacological evidence, and clinical monitoring, it clarifies the decisions supported at each stage and the additional evidence required before candidate progression, product use, or redesign.