目的 通过分析奥氮平的群体药代动力学研究,探讨影响奥氮平药动学参数的因素,为临床制定个体化给药方案提供依据。方法 在中国知网、万方、维普、迈特思创、PubMed和Embase等中英文数据库,以“奥氮平”“群体药代动力学”“模型”“非线性混合效应模型”及“olanzapine pamoate”“olanzapine”“population pharmacokinetic”“pharmacokinetic model”“nonlinear mixed effect”“NONMEM”为检索策略,检索建库至2023年5月所有关于奥氮平群体药代动力学的研究。结果 共纳入14篇奥氮平的群体药代动力学研究,大多数研究将奥氮平的药代动力学描述为一个单室模型。成人群体药代动力学模型群体典型值吸收速率常数：（0.3~2.85）/h;表观分布清除率：（10.4~25.4）L/h;表观分布容积：（223~2 390）L。儿童青少年模型群体典型值吸收速率常数：（0.142~0.758）/h;表观分布清除率：（13.6~16.8）L/h;表观分布容积：（322~899）L。年龄、体质量、性别、种族、吸烟状况、合并用药是影响奥氮平药动学参数的显著协变量。结论 奥氮平药动学参数估计值存在差异且有不同程度的个体间变异,未来应侧重于对特殊人群的研究。有必要对先前发表的模型进行外部验证,以便更准地的描述模型的适用性。

Objective By analyzing the population pharmacokinetics of olanzapine,the factors affecting the pharmacokinetic parameters of olanzapine were discussed,so as to provide a basis for the clinical formulation of individualized dosing regimens．Methods In Chinese and English databases such as CNKI,Wanfang,Wipro database,FMRS,PubMed and Embase,all studies on population pharmacokinetics of olanzapine from the establishment of the database to May 2023 were searched with “olanzapine pamoate”“olanzapine”,“population pharmacokinetics”,“pharmacokinetic model”,“nonlinear mixed-effect” and “NONMEM” as key words．Results A total of 14 population pharmacokinetic studies of olanzapine were included．Most studies described the pharmacokinetics of olanzapine as a single-chamber model．Adult pharmacokinetic model population typical values absorption rate constant was（0.3-2.85）/h;apparent distribution clearance was（10.4-25.4）L/h;apparent volume of distribution was（223-2390）L．absorption rate constants of the population of children and adolescents was（0.142-0.758）/h,apparent distribution clearance was（13.6-16.8）L/h,apparent volume of distribution was（322-899）L．Age,weight,gender,ethnicity,smoking status and concomitant medication were significant covariates affecting the pharmacokinetic parameters of olanzapine．Conclusions Estimates of pharmacokinetic parameters of olanzapine vary and have varying degrees of inter-individual variation．In the future,research should focus on special populations．Externally validation of previously published models should also be performed to more accurately describe the applicability of the models．