群体药动学将经典药动学原理与统计学模型相结合，可以有效利用稀疏数据进行药动学分析。采样点选择对药动学参数计算及结果影响很大，为了更高效、有针对性地挖掘数据信息，保证药动学参数的无偏估计，方便临床与非临床试验的开展，需考虑稀疏点采样优化。稀疏点采样方法包括随机采样法、有限采样法、最大后验贝叶斯法、Fisher信息矩阵法、信息化区间法等，广泛应用于单、多响应药物群体药动学研究。近年来，群体药动学在中药领域发展迅速，但很少有采样优化的研究。通过比较各稀疏点采样优化方法的优缺点、适用条件，介绍单、多响应群体药动学采样优化在中药中的应用，为中药的群体药动学采样优化提供参考。

Combining classical pharmacokinetic principles with statistical models, population pharmacokinetics (popPK) can effectively utilize sparse data for pharmacokinetic analysis. An optimally designed population pharmacokinetic study will balance the efficiency of a popPK study and the precision with which the parameters are estimated to ensure the unbiased estimation of pharmacokinetic parameters and facilitate the development of clinical and non-clinical trials. Sparse sampling methods have been developed for designing population pharmacokinetic experiments including random sampling method, limited sampling strategy, maximum a posteriori Bayesian method, Fisher information matrix method, and informative block randomized design, which have been widely applied in the uni-response and multi-response popPK sampling optimization. In recent years, population pharmacokinetics has been developed rapidly in Chinese materia medica (CMM), but few studies have been conducted to optimize sampling. By comparing the advantages and disadvantages of each sparse point sampling optimization method and the applicable conditions, this work provides a comparative review of optimal design methodologies and gives its application examples, which provides a reference for pharmacokinetic sampling optimization of CMM.

国家中药标准化项目：复方丹参滴丸标准化建设（ZYBZH-C-TJ-55）；天津市科技计划项目：中药定量药理与精准药学平台建设（16PTSYJC00270）