The growing threat of antimicrobial resistance (AMR), exacerbated by the COVID-19 pandemic, highlights the urgent need for alternative treatments such as bacteriophage (phage) therapy. Phage therapy offers a targeted approach to combat bacterial infections, particularly those resistant to conventional antibiotics. This study aimed to standardize an agar plate method for high-mix, low-volume phage production, suitable for personalized phage therapy. Plaque assays were conducted with the double-layer agar method, and plaque sizes were precisely measured using image analysis tools. Regression models developed with Minitab software established correlations between plaque size and phage production, optimizing production while minimizing resistance development. The resulting Plaque Size Calculation (PSC) model accurately correlated plaque size with inoculum concentration and phage yield, establishing specific plaque-forming unit (PFU) thresholds for optimal production. Using phages targeting pathogens such as Escherichia, Salmonella, Staphylococcus, Pseudomonas, Chryseobacterium, Vibrio, Erwinia, and Aeromonas confirmed the model’s accuracy across various conditions. The model’s validation showed a strong inverse correlation between plaque size and minimum-lawn cell clearing PFUs (MCPs; R² = 98.91%) and identified an optimal inoculum density that maximizes yield while minimizing the evolution of resistant mutants. These results highlight that the PSC model offers a standardized and scalable method for efficient phage production, which is crucial for personalized therapy and AMR management. Furthermore, its adaptability across different conditions and phages positions it as a potential standard tool for rapid and precise phage screening and propagation in both clinical and industrial settings.
