Pharmacokinetic-Pharmacodynamic Modelling for Antibiotics: Static and Dynamic In Vitro Time-Kill Curve Experiments
Elisabet I. Nielsen (1), Otto Cars (2) Lena E. Friberg (1)
(1) Department of Pharmaceutical Biosciences, Uppsala University, Sweden; (2) Department of Medical Sciences, Uppsala University, Sweden
Objectives: In vitro time-kill studies are commonly conducted with the aim to assess efficacy of antimicrobial agents. Previously a general semi-mechanistic PK-PD model describing the time course of antimicrobial effects has been developed based on data from in vitro time-kill curve experiments with static antibiotic concentrations (1). The aim of the present study was to investigate the ability of the developed PK-PD model to describe and predict data from time-kill curve experiments with dynamic concentrations.
Methods: In vitro time-kill curves were performed in which cultures of Streptococcus Pyogenes were exposed to five different antibiotics; benzylpenicillin, cefuroxime, erythromycin, moxifloxacin, and vancomycin. In the experiments with dynamic concentrations an in vitro kinetic model (2) was used to simulate a half-life of the drug. In total 187 experiments with a range of concentrations for each drug were included in the analysis (static n=135, dynamic n=52). The previously developed PK-PD model based on static time-kill curve experiments was applied to the dynamic experiments. Observations from the dynamic time-kill experiments were compared to model predictions based on parameter estimation using a) only static data, b) only dynamic data and c) combined static and dynamic data.
Results: Differences in experimental settings between static and dynamic time-kill curve experiments did not have a significant effect on the growth kinetics of the bacteria. The dynamic experiments were well predicted using the earlier developed structural model with parameter re-estimation. For the majority of the antibiotics, the dynamic experiments were also adequately predicted using parameter estimates based on only the static experiments. However, adding data from dynamic experiments in the estimation, did improve the model fit for cefuroxime and vancomycin, indicating some differences in sensitivity to experimental design for these antibiotics.
Conclusions: The previously developed PK-PD model could well characterize the data from dynamic time-kill curve experiments. Further, for most antibiotics, the parameter estimates based on data from static time-kill curve experiments provided a good prediction of data from dynamic experiments implying a limited need to perform labour intensive dynamic experiments.
References:
[1] Nielsen EI, et al. Antimicrob Agents Chemother. 2007 Jan; 51(1):128-36.
[2] Löwdin E, et al. Antimicrob Agents Chemother. 1996 Nov; 40(11):2478-82
