Mechanism-based pharmacokinetic–pharmacodynamic modeling of antimicrobial drug effects

被引:9
作者
David Czock
Frieder Keller
机构
[1] University Hospital Ulm,Division of Nephrology, Medical Department
来源
Journal of Pharmacokinetics and Pharmacodynamics | 2007年 / 34卷
关键词
Pharmacokinetics; Pharmacodynamics; PK–PD modeling; Antimicrobials; Antibiotics; Resistance; Simulation;
D O I
暂无
中图分类号
学科分类号
摘要
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.
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页码:727 / 751
页数:24
相关论文
共 232 条
[1]
Mueller M(2004)Issues in pharmacokinetics and pharmacodynamics of anti-infective agents: kill curves versus MIC Antimicrob Agents Chemother 48 369-377
[2]
de la Pena A(2005)Pharmacokinetic/pharmacodynamic evaluation of anti-infective agents Expert Rev Anti Infect Ther 3 361-373
[3]
Derendorf H(2004)Antimicrobial pharmacodynamics: critical interactions of ’bug and drug’ Nat Rev Microbiol 2 289-300
[4]
Schuck EL(2005)Dose adjustment of ciprofloxacin in renal failure: reduce the dose or prolong the administration interval Eur J Med Res 10 145-148
[5]
Derendorf H(2005)Evaluating ciprofloxacin dosing for Pseudomonas aeruginosa infection by using clinical outcome-based Monte Carlo simulations Antimicrob Agents Chemother 49 4009-4014
[6]
Drusano GL(1994)Mechanism-based pharmacodynamic modeling Clin Pharmacol Ther 56 356-358
[7]
Czock D(1996)Dosage regimens of antibacterials Clin Drug Invest 11 229-239
[8]
Rasche FM(2005)Pharmacodynamic modeling of ciprofloxacin resistance in Staphylococcus aureus Antimicrob Agents Chemother 49 209-219
[9]
Zelenitsky S(1998)Comparisons between antimicrobial pharmacodynamic indices and bacterial killing as described by using the Zhi model Antimicrob Agents Chemother 42 1731-1737
[10]
Ariano R(1997)pharmacokinetic–pharmacodynamic modeling of the in vitro antiinfective effect of piperacillin-tazobactam combinations Int J Clin Pharmacol Ther 35 426-433