This Article Full Text (PDF) Other Versions of this Article: AAC.00604-06v1 51/1/128    most recent Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Reprints and Permissions Copyright Information Books from ASM Press MicrobeWorld Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Nielsen, E. I Articles by Sandström, M. Search for Related Content PubMed PubMed Citation Articles by Nielsen, E. I Articles by Sandström, M.

 Previous Article  |  Next Article 

Antimicrob. Agents Chemother. doi:10.1128/AAC.00604-06
Copyright (c) 2006, American Society for Microbiology and/or the Listed Authors/Institutions. All Rights Reserved.

A Semi-Mechanistic Pharmacokinetic/Pharmacodynamic Model for the Assessment of Activity of Antibacterial Agents from Time-Kill Curve Experiments

Division of Pharmacokinetics and Drug Therapy, Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden; Hospital Pharmacy, University Hospital, Uppsala, Sweden; Department of Infectious Diseases, University Hospital, Uppsala, Sweden

^* To whom correspondence should be addressed. Email: elisabet.nielsen{at}farmbio.uu.se,

	Abstract

Dosing of antibacterial agents is generally based on point estimates of the effect even though bacteria exposed to antibiotics shows a complex kinetic behaviour. More advantageous would be to use the whole time course of observed effects. The aim of the present study was to develop a semi-mechanistic pharmacokinetic-pharmacodynamic model characterizing the events seen in a bacterial system when exposed to antibacterial agents with different mechanism of action. Time-kill curve experiments were performed with a strain of Streptococcus pyogenes exposed to a wide range of concentrations of the following antibiotics; benzylpenicillin, cefuroxime, erythromycin, moxifloxacin and vancomycin. Bacterial counts were followed with frequent sampling during the experiment. A simultaneous fit of all data was accomplished. Degradation of the drugs were monitored and corrected for in the model and a link model was used to account for an effect delay. In the final PK/PD model the total bacterial population was divided into two subpopulations, one growing drug-susceptible population and one resting insusceptible population. The drug effect was included as an increase of the killing rate of bacteria being in the susceptible state according to an Emax model. An internal model validation showed the model to be robust and to have good predictability. In conclusion, for all drugs, the final PK/PD model successfully described the bacterial growth and kill kinetics when exposed to different antibiotic concentrations. The developed semi-mechanistic model might after further refinement serve as a tool in the development of optimal dosing strategies for antibacterial agents.

This article has been cited by other articles:

• Schmidt, S., Rock, K., Sahre, M., Burkhardt, O., Brunner, M., Lobmeyer, M. T., Derendorf, H. (2008). Effect of Protein Binding on the Pharmacological Activity of Highly Bound Antibiotics. Antimicrob. Agents Chemother. 52: 3994-4000 [Abstract] [Full Text]  
• Viberg, A., Cars, O., Karlsson, M. O., Jonsson, S. (2008). Estimation of Cefuroxime Dosage Using Pharmacodynamic Targets, MIC Distributions, and Minimization of a Risk Function. J Clin Pharmacol 48: 1270-1281 [Abstract] [Full Text]  
• Venisse, N., Gregoire, N., Marliat, M., Couet, W. (2008). Mechanism-Based Pharmacokinetic-Pharmacodynamic Models of In Vitro Fungistatic and Fungicidal Effects against Candida albicans. Antimicrob. Agents Chemother. 52: 937-943 [Abstract] [Full Text]  
• Tam, V. H., Schilling, A. N., Poole, K., Nikolaou, M. (2007). Mathematical modelling response of Pseudomonas aeruginosa to meropenem. J Antimicrob Chemother 60: 1302-1309 [Abstract] [Full Text]