Zahra Zahid Piracha, Umar Saeed
The rapid rise of multidrug-resistant and extensively drug-resistant bacterial infections has renewed interest in bacteriophages as adaptable, targeted antimicrobials. Recent advances in phage engineering, including CRISPR-based approaches, now make it possible to refine host range, strengthen lytic performance, and deliver genetic payloads that target clinically important resistance determinants such as blaNDM , mecA , and mcr-1 . In parallel, jumbo phages with large genomes often encode additional functions that support replication and biofilm disruption, offering practical advantages in densely structured infections where antibiotics perform poorly. A second limitation in phage translation has been measurement: in most settings, dosing and treatment duration remain guided by indirect endpoints rather than real-time information on distribution and activity. Near-infrared bioimaging addresses this gap by enabling noninvasive tracking of infection burden and phage kinetics in vivo through bacteriophytochrome-derived reporters, including iRFPs, miRFPs, and PAiRFPs. In this review, we bring these developments together and discuss how CRISPR-enabled phage engineering, jumbo-phage biology, and near-infrared readouts can be integrated into a precision framework that is measurable, adaptable, and clinically interpretable. We examine evidence across major drug-resistant pathogens, including Pseudomonas aeruginosa , Acinetobacter baumannii , Klebsiella pneumoniae , methicillin-resistant Staphylococcus aureus , vancomycin-resistant enterococci, Burkholderia cepacia , and Mycobacterium abscessus . We also summarize practical constraints that remain central to clinical translation, manufacturing quality, host immune neutralization, and regulatory variability, and outline a realistic development pathway in which engineered phages and companion diagnostics progress from animal models to carefully defined clinical indications. Together, these advances support a shift from empirical phage use toward a more standardized, data-driven approach to treating drug-resistant infections.