Modeling of microbial population responses to time-periodic concentrations of antimicrobial agents

We present the development and first experimental validation of a mathematical modeling framework for predicting the eventual response of heterogeneous (distributed-resistance) microbial populations to antimicrobial agents at time-periodic (hence pharmacokinetically realistic) concentrations. Our mathematical model predictions are validated in a hollow-fiber in vitro experimental infection model. They are in agreement with the threshold levofloxacin exposure necessary to suppress resistance development of Pseudomonas aeruginosa in a murine thigh infection model. Predictions made by the proposed mathematical modeling framework can offer guidance for targeted testing of promising regimens. This can aid the development and clinical use of antimicrobial agents that combat microbial resistance.