用NONMEM法建立西酞普兰群体药代动力学模型

Population pharmacokinetics of citalopram by NONMEM

目的建立中国人西酞普兰(抗抑郁药)的群体药代动力学(PPK)模型,为临床个体化给药提供参考。方法用群体药代动力学方法,对西酞普兰生物等效性研究中23例受试者的血药浓度和临床资料进行分析,用NON-MEM软件求算西酞普兰的PPK参数值,建立西酞普兰的PPK模型,并进行模型验证。结果经NONMEM法处理,所有因素中,年龄、体重以及CYP2C19基因型对中央隔室清除率有显著性的影响;体重对分布容积有显著性的影响。年龄和体重的增加对清除率影响分别为-0.39L·h-1.a-1和0.18L.h-1·kg-1。结论用NONMEM软件拟合获得的西酞普兰群体药代动力学最终模型,经验证稳定可靠。

Objective To set up a population pharmacokinetic （PPK） model of citalopram in Chinese, and promote reasonable use of antidepressant drugs in clinical practice. Methods Analyze the plasma concentration and clinical data of the 23 volunteers in bioequivalent study with PPK. Using NONMEM software, PPK parameter values were calculated, and a basic model and a final model were built. Assess the accuracy and prediction of the basic model and the final model. Results Age, body weight and the genetype of CYPC19 effect the clearance of center camera remarkably. Body weight effect the distribution volume markedly. Clearance decreased 0.39 L·h^-1·a^-1 for every year of age and increased 0.18 L·h^-1 per kilogram body weight. Conclusion The PPK final model of citalopram in Chinese is successfully established using the NONMEM software.