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Short description:

The model describes the growth and killing of Streptococcus pyogenes exposed to a wide range of concentrations of the following antibiotics: benzylpenicillin, cefuroxime, erythromycin, moxifloxacin, and vancomycin. The model consist of a PK-part describing the drug degradation and effect delay and a PD part describing the drug effect and the growth and drug-induced killing of the bacteria. The model is implemented in the NONMEM software as a differential equation system solved by the ADVAN 9 solver. The drug effect is implemented as a sigmoidal Emax function of the active drug concentration. Two subpopulations of bacteria (actively growing drug susceptible (S) and resting drug insusceptible (R)) are modeled and the mixture module was used to allow for a variation in the fraction of bacteria being resting cells in the starting inocula.

Format:	Original code
Related Publication:	Semimechanistic pharmacokinetic/pharmacodynamic model for assessment of activity of antibacterial agents from time-kill curve experiments. Nielsen EI, Viberg A, Löwdin E, Cars O, Karlsson MO, Sandström M Antimicrobial agents and chemotherapy, 1/2007, Volume 51, Issue 1, pages: 128-136 Affiliation: Division of Pharmacokinetics and Drug Therapy, Uppsala University, Box 591, SE-751 24 Uppsala, Sweden. elisabet.nielsen@farmbio.uu.se Abstract: Dosing of antibacterial agents is generally based on point estimates of the effect, even though bacteria exposed to antibiotics show complex kinetic behaviors. The use of the whole time course of the observed effects would be more advantageous. The aim of the present study was to develop a semimechanistic pharmacokinetic (PK)/pharmacodynamic (PD) model characterizing the events seen in a bacterial system when it is exposed to antibacterial agents with different mechanisms 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 monitored with frequent sampling during the experiment. A simultaneous fit of all data was accomplished. The degradation of the drugs was 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 in the susceptible state, according to a maximum-effect (E(max)) model. An internal model validation showed that the model was robust and had good predictability. In conclusion, for all drugs, the final PK/PD model successfully described bacterial growth and killing kinetics when the bacteria were exposed to different antibiotic concentrations. The semimechanistic model that was developed might, after further refinement, serve as a tool for the development of optimal dosing strategies for antibacterial agents.
Contributors:	Anders Kristoffersson

Validation Status:	Annotations are correct.
Certification Comment:	This model is not certified.

DDMODEL00000055: Nielsen2007_semimech_PKPD_antibiotics_original

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