Model-informed development of bacteriophage therapy: bridging <i>in vitro</i> and <i>in vivo</i> efficacy against multidrug-resistant <i>Pseudomonas aeruginosa</i>

Bacteriophages are emerging as promising alternatives to antibiotics for multidrug-resistant (MDR) infections. However, their unique pharmacokinetic and pharmacodynamic (PKPD) properties arising from host-dependent amplification present challenges for dose selection and clinical translation. Here, we present a mechanistic PKPD model informed by <i>in vitro</i> kinetic assays and <i>in vivo</i> mouse studies of phage therapy targeting MDR <i>Pseudomonas aeruginosa</i>. The model extends the classical predator-prey model by addressing dormancy-related bacterial persistence and partitioning bacterial subpopulations based on phage susceptibility profiles. Simulations revealed a non-monotonous dose-exposure curve driven by dose-dependent reduction of phage replication and the importance of cross-resistance in selecting optimal phage cocktails. <i>In vivo</i>, host immunity was identified as a crucial component in inhibiting bacterial regrowth, with bistable outcomes dependent on initial bacterial load and immune competence. Dose-ranging simulations under varying immune statuses suggest that long-term bacterial load is solely determined by host immune function. However, higher doses transiently reduce bacterial load to a greater extent and thereby suppress immune activation. In immunocompetent hosts, phage cocktails can enhance maximal bacterial load reduction when administered at doses higher than a critical threshold. In conclusion, our PKPD framework enables optimal selection of phage cocktails and dosing regimens, supports rational design of first-in-human trials of phage therapy, and potentially advances model-informed drug development for replication-competent biologics.IMPORTANCEIn this study, we construct an integrative model of phage-bacteria dynamics and investigate whether its calibration to <i>in vitro</i> kinetic assay data can inform the rational design of phage therapy regimens and cocktails. Our findings demonstrate a dose range within which lower phage doses yield higher long-term exposure, presenting a fundamentally different framework for dose optimization. Analysis of phage cocktails reveals that combining phages with low cross-resistance delays the regrowth of phage-resistant bacteria <i>in vitro</i>. The extended <i>in vivo</i> model elucidates key differences between <i>in vitro</i> and <i>in vivo</i> outcomes and highlights the importance of the host's immune response in suppressing the growth of phage-resistant bacteria. Phage cocktails to combat phage resistance are therefore of less importance in immune-competent individuals but can enhance bacterial killing when administered at sufficiently high doses. We propose that this modeling framework holds potential for model-informed drug development by quantitatively characterizing bacteria-phage dynamics using preclinical data. Furthermore, it may facilitate the interpretation of <i>in vivo</i> therapeutic outcomes through a mechanistic understanding derived from <i>in vitro</i> observations.