Minto C, Schnider T
Royal North Shore Hospital, University of Sydney, Australia.
Br J Clin Pharmacol. 1998 Oct;46(4):321-33. doi: 10.1046/j.1365-2125.1998.00792.x.
Population pharmacokinetics or pharmacodynamics is the study of the variability in drug concentration or pharmacological effect between individuals when standard dosage regimens are administered. We provide an overview of pharmacokinetic models, pharmacodynamic models, population models and residual error models. We outline how population modelling approaches seek to explain interpatient variability with covariate analysis, and, in some approaches, to characterize the unexplained interindividual variability. The interpretation of the results of population modelling approaches is facilitated by shifting the emphasis from the perspective of the modeller to the perspective of the clinician. Both the explained and unexplained interpatient variability should be presented in terms of their impact on the dose-response relationship. Clinically relevant questions relating to the explained and unexplained variability in the population can be posed to the model, and confidence intervals can be obtained for the fraction of the population that is estimated to fall within a specific therapeutic range given a certain dosing regimen. Such forecasting can be used to develop optimal initial dosing guidelines. The development of population models (with random effects) permits the application of Bayes's formula to obtain improved estimates of an individual's pharmacokinetic and pharmacodynamic parameters in the light of observed responses. An important challenge to clinical pharmacology is to identify the drugs that might benefit from such adaptive-control-with-feedback dosing strategies. Drugs used for life threatening diseases with a proven pharmacokinetic-pharmacodynamic relationship, a small therapeutic range, large interindividual variability, small interoccasion variability and severe adverse effects are likely to be good candidates. Rapidly evolving changes in health care economics and consumer expectations make it unlikely that traditional drug development approaches will succeed in the future. A shift away from the narrow focus on rejecting the null hypothesis towards a broader focus on seeking to understand the factors that influence the dose-response relationship--together with the development of the next generation of software based on population models--should permit a more efficient and rational drug development programme.
群体药代动力学或药效学是研究在给予标准给药方案时个体间药物浓度或药理效应的变异性。我们概述了药代动力学模型、药效学模型、群体模型和残差模型。我们概述了群体建模方法如何通过协变量分析来解释患者间的变异性，并且在某些方法中，如何表征个体间无法解释的变异性。将重点从建模者的角度转移到临床医生的角度，有助于对群体建模方法的结果进行解释。患者间可解释和无法解释的变异性都应根据它们对剂量反应关系的影响来呈现。可以向模型提出与群体中可解释和无法解释的变异性相关的临床相关问题，并且可以获得在给定某种给药方案下估计落在特定治疗范围内的群体比例的置信区间。这种预测可用于制定最佳初始给药指南。群体模型（具有随机效应）的发展允许应用贝叶斯公式，以便根据观察到的反应获得个体药代动力学和药效学参数的改进估计。临床药理学面临的一个重要挑战是确定哪些药物可能受益于这种反馈给药的自适应控制策略。用于治疗危及生命疾病的药物，若具有已证实的药代动力学 - 药效学关系、治疗范围窄、个体间变异性大、个体间变异性小以及严重不良反应，则很可能是合适的候选药物。医疗保健经济学和消费者期望的快速演变使得传统药物开发方法在未来不太可能成功。从狭隘地关注拒绝原假设转向更广泛地关注理解影响剂量反应关系的因素，以及基于群体模型开发下一代软件，应该能够实现更高效、合理的药物开发计划。
