Modeling Phage–Antibiotic Synergy, Innate Immunity, and Phage Resistance in Multidrug-Resistant Acinetobacter baumannii

Background/Objectives: Antimicrobial resistance has been recognized as a major global health threat, with multidrug-resistant Acinetobacter baumannii identified as one of the most critical pathogens. To address the limitations of conventional antibiotics, phage therapy has been proposed as a complementary or alternative intervention. In this study, experimental data were integrated into a deterministic differential-equation-based model to capture phage–bacteria–antibiotic–host immune system interactions. Methods: The model extended a previous phage–host immune system synergy framework by incorporating phage–antibiotic synergy and a time-dependent reduction in phage adsorption as a phenomenological representation of population-level reduction in phage susceptibility. This formulation does not explicitly model the molecular mechanisms or evolutionary emergence of resistance. In vitro observations of phage-induced resensitization to ceftazidime informed model parameterization, while remaining parameters were estimated from experimental observations or literature values. Simulations evaluated bacterial dynamics under phage-only, antibiotic-only, and immunity-only conditions, as well as combined therapeutic scenarios. Results: Model predictions indicated the greatest bacterial reduction when phages, antibiotics, and host innate immunity acted together. Phage–antibiotic synergy further enhanced predicted bacterial clearance, particularly for ceftazidime-resistant populations, while a population-level reduction in phage susceptibility was predicted approximately 4 h post-infection, consistent with experimental observations. Combined scenarios involving continuous antibiotic infusion, phage plus host immunity, or low-dose antibiotic regimens predicted accelerated bacterial declines when synergistic interactions were active. Conclusions: This framework integrates experimental observations with mathematical modeling to explore therapeutic interactions and temporal changes in phage susceptibility, while assessing parameter sensitivity and guiding future experimental and preclinical studies.