NDLI: Mechanism-based pharmacokinetic–pharmacodynamic modeling of antimicrobial drug effects

Content Provider	Springer Nature Link
Author	Czock, David Keller, Frieder
Copyright Year	2007
Abstract	Mathematical modeling of drug effects maximizes the information gained from an experiment, provides further insight into the mechanisms of drug effects, and allows for simulations in order to design studies or even to derive clinical treatment strategies. We reviewed modeling of antimicrobial drug effects and show that most of the published mathematical models can be derived from one common mechanism-based PK–PD model premised on cell growth and cell killing processes. The general sigmoid Emax model applies to cell killing and the various parameters can be related to common pharmacodynamics, which enabled us to synthesize and compare the different parameter estimates for a total of 24 antimicrobial drugs from published literature. Furthermore, the common model allows the parameters of these models to be related to the MIC and to a common set of PK–PD indices. Theoretically, a high Hill coefficient and a low maximum kill rate indicate so-called time-dependent antimicrobial effects, whereas a low Hill coefficient and a high maximum kill rate indicate so-called concentration-dependent effects, as illustrated in the garenoxacin and meropenem examples. Finally, a new equation predicting the time to microorganism eradication after repeated drug doses was derived that is based on the area under the kill-rate curve.
Starting Page	727
Ending Page	751
Page Count	25
File Format	PDF
ISSN	1567567X
Journal	Journal of Pharmacokinetics and Pharmacodynamics
Volume Number	34
Issue Number	6
e-ISSN	15738744
Language	English
Publisher	Springer US
Publisher Date	2007-09-29
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Pharmacokinetics Pharmacodynamics PK–PD modeling Antimicrobials Antibiotics Resistance Simulation Biochemistry Biomedical Engineering Veterinary Medicine Pharmacy Pharmacology/Toxicology
Content Type	Text
Resource Type	Article
Subject	Pharmacology

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