Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
Pharmacol Rev. 2013 Jun 26;65(3):1053-90. doi: 10.1124/pr.111.005769. Print 2013 Jul.
Pharmacokinetic-pharmacodynamic (PKPD) modeling and simulation has evolved as an important tool for rational drug development and drug use, where developed models characterize both the typical trends in the data and quantify the variability in relationships between dose, concentration, and desired effects and side effects. In parallel, rapid emergence of antibiotic-resistant bacteria imposes new challenges on modern health care. Models that can characterize bacterial growth, bacterial killing by antibiotics and immune system, and selection of resistance can provide valuable information on the interactions between antibiotics, bacteria, and host. Simulations from developed models allow for outcome predictions of untested scenarios, improved study designs, and optimized dosing regimens. Today, much quantitative information on antibiotic PKPD is thrown away by summarizing data into variables with limited possibilities for extrapolation to different dosing regimens and study populations. In vitro studies allow for flexible study designs and valuable information on time courses of antibiotic drug action. Such experiments have formed the basis for development of a variety of PKPD models that primarily differ in how antibiotic drug exposure induces amplification of resistant bacteria. The models have shown promise for efficacy predictions in patients, but few PKPD models describe time courses of antibiotic drug effects in animals and patients. We promote more extensive use of modeling and simulation to speed up development of new antibiotics and promising antibiotic drug combinations. This review summarizes the value of PKPD modeling and provides an overview of the characteristics of available PKPD models of antibiotics based on in vitro, animal, and patient data.
药代动力学-药效学（PKPD）建模和模拟已成为合理药物开发和药物使用的重要工具，所开发的模型既能描述数据中的典型趋势，又能量化剂量、浓度与预期效果和副作用之间关系的可变性。与此同时，抗生素耐药菌的迅速出现给现代医疗保健带来了新的挑战。能够描述细菌生长、抗生素对细菌的杀灭作用和免疫系统以及耐药性选择的模型，可以为抗生素、细菌和宿主之间的相互作用提供有价值的信息。从开发的模型进行模拟可以预测未测试场景的结果，改进研究设计，并优化给药方案。如今，通过将数据总结为具有有限外推到不同给药方案和研究人群可能性的变量，大量关于抗生素 PKPD 的定量信息被丢弃了。体外研究允许灵活的研究设计，并提供有关抗生素药物作用时间过程的宝贵信息。此类实验为开发各种 PKPD 模型奠定了基础，这些模型主要区别在于抗生素药物暴露如何诱导耐药菌的扩增。这些模型在预测患者疗效方面显示出了前景，但很少有 PKPD 模型描述抗生素药物在动物和患者中的作用时间过程。我们提倡更广泛地使用建模和模拟，以加快新抗生素和有前途的抗生素药物组合的开发。本综述总结了 PKPD 建模的价值，并概述了基于体外、动物和患者数据的抗生素 PKPD 模型的特点。
