Simulation-Based Evaluation of PK/PD Indices for Meropenem Across Patient Groups and Experimental Designs

ABSTRACT Purpose Antibiotic dose predictions based on PK/PD indices rely on that the index type and magnitude is insensitive to the pharmacokinetics (PK), the dosing regimen, and bacterial susceptibility. In this work we perform simulations to challenge these assumptions for meropenem and Pseudomonas aeruginosa . Methods A published murine dose fractionation study was replicated in silico . The sensitivity of the PK/PD index towards experimental design, drug susceptibility, uncertainty in MIC and different PK profiles was evaluated. Results The previous murine study data were well replicated with f T > MIC selected as the best predictor. However, for increased dosing frequencies f AUC/MIC was found to be more predictive and the magnitude of the index was sensitive to drug susceptibility. With human PK f T > MIC and f AUC/MIC had similar predictive capacities with preference for f T > MIC when short t 1/2 and f AUC/MIC when long t 1/2 . Conclusions A longitudinal PKPD model based on in vitro data successfully predicted a previous in vivo study of meropenem. The type and magnitude of the PK/PD index were sensitive to the experimental design, the MIC and the PK. Therefore, it may be preferable to perform simulations for dose selection based on an integrated PK-PKPD model rather than using a fixed PK/PD index target.