Quantitative Assessment of Combination Antimicrobial Therapy against Multidrug‐Resistant Bacteria in a Murine Pneumonia Model
Abstract
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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…
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