中文摘要：

基于生理的药代动力学（PBPK）模型是当前药物研究领域的重要方法,已被广泛应用于药物发现和开发的各个阶段。在药物发现阶段,利用PBPK模型对药物药代动力学性质进行预测,完成对候选药物的筛选;在临床前阶段,通过结合体外数据和生理放大系数,利用PBPK模型预测候选药物在动物和人的整体药代动力学行为,并结合体外代谢实验,可提前预测药物药物相互作用;在临床阶段,PBPK模型有助于预测不同参照人群（不同年龄、不同疾病状态、不同种族）的差异,尤其是对儿童给药剂量及采样时间的预测。目前,PBPK模型的输入参数多为群体均值,难以达到服务个体的目的。在个体化需求前提下,要求模型的输入参数更能反映个体特征,且导入更加符合实际生理条件的时间参数。本文综述了PBPK模型的原理和特征,及其在药物发现阶段、临床前开发阶段、临床开发阶段、药物相互作用和个体化用药的应用,并简要介绍了常用的PBPK软件的特点。

英文摘要：

Currently, a physiologically based pharmacokinetic （PBPK） model plays a key role in pharmaceutical research, which has been widely used at each stage of drug discovery and develop- ment. In the process of drug discovery, the selection of drug candidates is finished using the PBPK model to predict the pharmacokinetic properties of the drugs. In the process of preclinical development, through a combination of in vitro and physiological data amplification coefficient, the PBPK model can be used to predict not only the overall pharmacokinetic behavior of drug candidates in humans and animals and in vitro metabolism experiments, but also drug-drug interactions （DDI）. In the course of clinical development, the PBPK model can help predict the difference between reference populations （age, different disease state, and polymorphism）, especially the dosage and sampling time of the children. At present, the input parameters of PBPK model are mostly the mean values of the population, making it difficult to serve individuals. It is hoped that the input parameters of the model can reflect more of the individual characters according to the individual requirement, and that the time parameters of the input accord more with the actual physiological condition. In this article, we briefly introduced the characteristics of common PBPK software, and reviewd the principle and feature of the PBPK model, as well as its application to drug discovery, preclinical development and clinical development, DDI, and individualized medication.