Quantitative assessment of combination antimicrobial therapy against multidrug-resistant bacteria in a murine pneumonia model.

Abstract

Combination antimicrobial therapy is clinically used as a last-resort strategy to control multidrug-resistant bacterial infections. However, selection of antibiotics is often empirical, and conventional assessment of combined drug effect has not been correlated to clinical outcomes. Here, we report a quantitative method to assess combined killing of antimicrobial agents against 2 multidrug-resistant bacteria. Combined time-kill studies were performed using clinically achievable concentrations for each 2-agent combination against clinical isolates of Acinetobacter baumannii and Pseudomonas aeruginosa. Bacterial burden observed at 24 h was mathematically modeled using a 3-dimensional response surface. Subsequently, a neutropenic murine pneumonia model with simulated clinical dosing exposures was used to validate our quantitative assessment of combined killing. Different antimicrobial combinations were found to have varying efficacy against the multidrug-resistant bacteria. As predicted by our quantitative method, cefepime plus amikacin was found to be the most superior combination, which was evidenced by a reduction in tissue bacterial burden and prolonged survival of infected animals. The consistency between the predictions of the mathematical model and in vivo observations substantiated the robustness of our quantitative method. These data highlighted a novel and promising method to guide rational selection of antimicrobial combination in the clinical setting.