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重新审视药代动力学概念——基础与应用。

Pharmacokinetic concepts revisited--basic and applied.

机构信息

The School of Pharmacy, The University of Queensland, Pharmacy Australia Centre of Excellence, St Lucia, 4072 Brisbane, Australia.

出版信息

Curr Pharm Biotechnol. 2011 Dec;12(12):1983-90. doi: 10.2174/138920111798808400.

Abstract

Pathophysiological changes are common in critically ill patients, and can alter the time course of drug concentrations following dosing. The latter is termed pharmacokinetics (PK), and describes the relationship between dose administered and drug concentrations in plasma. Thus, modifications in PK necessitate dose adjustment, to optimize drug therapy in critical care. An understanding of basic PK principles is therefore required, to improve dosage guidelines in the population treated. Here, we define the key PK parameters, with specific application to critically ill patients. We then overview the methods used for PK analysis, in both research and in the clinical setting. Traditionally, non-compartmental and standard two-stage approaches have been used in small groups of patients with similar demographics and pathophysiology. However, these methods require intensive sampling, and do not explicitly describe inter-individual variability, or errors associated with measurement or sampling. Population PK (POPPK) modelling is advantageous in this regard, and can use both sparse and rich datasets to provide accurate estimates for between-subject variability (BSV). In addition, POPPK can explore patient parameter-covariate relationships, to account for some of the BSV in PK. This information is useful with assisting individualized dosing in the clinic. While the above methods are suitable for research, they are too time-consuming in the clinical setting, and Bayesian approaches have been adopted to optimize dosing. These methods, together with POPPK and appropriate study design are recommended for improved dosing in critical care.

摘要

病理生理学变化在危重症患者中很常见,并且会改变给药后药物浓度的时间过程。后者被称为药代动力学(PK),描述了给药剂量与血浆中药物浓度之间的关系。因此,PK 的改变需要进行剂量调整,以优化重症监护中的药物治疗。因此,需要了解基本 PK 原则,以改善所治疗人群的剂量指南。在这里,我们定义了关键的 PK 参数,并特别应用于危重症患者。然后,我们概述了用于 PK 分析的方法,无论是在研究中还是在临床环境中。传统上,非房室和标准两阶段方法已在具有相似人口统计学和病理生理学特征的小患者组中使用。然而,这些方法需要密集采样,并且不能明确描述个体间变异性,或与测量或采样相关的误差。群体药代动力学(POPPK)建模在这方面具有优势,并且可以使用稀疏和丰富的数据集为个体间变异性(BSV)提供准确的估计。此外,POPPK 可以探索患者参数协变量关系,以解释 PK 中的一些 BSV。这些信息对于在临床上协助个体化给药很有用。虽然上述方法适用于研究,但在临床环境中过于耗时,并且已经采用贝叶斯方法来优化给药。这些方法,以及 POPPK 和适当的研究设计,被推荐用于改善重症监护中的给药。

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