Abstract Multi-drug resistant bacterial infections are an increasing threat to the efficacy of currently used antibiotics worldwide. When designing rational antibiotic therapies, a comprehensive understanding of the complex interplay between the antibiotic and the bacteria, the pharmacodynamics (PD), is a prerequisite. The most often-used metric to assess the PD of antibiotics is the minimum inhibitory concentration (MIC). However, the MIC is a summary metric based on a single timepoint observation and does not reflect bacterial dynamics. This work aims to summarize published antibiotic PD metrics and their respective applications to encourage researchers and healthcare professionals to use the most informative metrics for their specific objectives. This review is structured based on the data needed to derive the PD metrics, e.g. single timepoint or longitudinal data. In addition, this review highlights how pharmacometric modelling can maximize the knowledge obtained from the reported metrics and how modelling can serve as an important approach to aid the design of rational antibiotic treatments, aiming to maximize their benefit–risk ratio.
Andersson et al. (Tue,) studied this question.