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中国临床药理学与治疗学 ›› 2022, Vol. 27 ›› Issue (9): 984-990.doi: 10.12092/j.issn.1009-2501.2022.09.004

• 定量药理学 • 上一篇    下一篇

基于模型的Meta分析建立中国老年人群美罗培南群体药动学模型

叶红波1,宋洋洋1,薛领2,芮建中3   

  1. 1安吉县中医医院西药房,湖州 313100,浙江;2苏州大学附属第一医院临床药理室,苏州 215006,江苏;3解放军东部战区总医院药理科,南京 210002,江苏

  • 收稿日期:2022-06-27 修回日期:2022-08-29 出版日期:2022-09-27 发布日期:2022-10-14
  • 通讯作者: 芮建中,男,博士,主任药师,研究方向:定量药理学。 E-mail: ruijz@tom.com
  • 作者简介:叶红波,男,硕士,副主任药师,研究方向:群体药动学。 E-mail: yhb5442387@163.com
  • 基金资助:
    湖州市科学技术局项目(2020GY82)

Meropenem population pharmacokinetic model for the Chinese elderly established by model-based META analysis

YE Hongbo1, SONG Yangyang1, XUE Ling2, RUI Jianzhong3   

  1. Department of Pharmacy, Anji Traditional Chinese Medicine Hospital, Huzhou 313100, Zhejiang, China
  • Received:2022-06-27 Revised:2022-08-29 Online:2022-09-27 Published:2022-10-14

摘要: 目的:采用基于模型的Meta分析,建立美罗培南在中国老年人群的群体药动学模型。方法:通过文献检索,提取药物剂量、采样时间点、浓度、样本量、年龄、性别、体质量和肌酐清除率等数据。用NONMEM建立群体模型,采用逐步递归法筛选协变量。自举法和可视化检验(VPC)分别验证模型的稳定性和预测能力。结果:美罗培南的药动学采用二房室描述。经过协变量筛选,最终模型纳入肌酐清除率对CL,体质量对V1的影响。自举法验证和VPC检验都显示模型的良好稳定性和预测能力。结论:通过基于模型的Meta分析的方法,建立一个更加具有代表性的美罗培南的中国老年人群体药动学模型。

关键词: 美罗培南, MBMA, 中国老年人, NONMEM

Abstract: AIM: To build a meropenem population pharmacokinetic model for Chinese elderly through model-based meta-analysis. METHODS: Informations including dosing regimen, sampling times, concentrations, sample size, age, gender, body weight (BW) and creatinine clearance were extracted after the literature were retrieved. The model was built by NONMEM. Stepwise covariate modeling strategy was used for covariates analysis.RESULTS: A two-compartment model was applied to describe meropenem pharmacokinetics. After stepwise covariate modeling, covariates that remained significant in the final model were creatinine clearance (CLcr) on CL and the BW on V1. The stability and predictive performance were confirmed by bootstrapping and visual predictive check. CONCLUSION: A more representative population pharmacokinetics model of meropenem in Chinese elderly patients is built through model-base meta-analysis method.

Key words: meropenem, model-based meta-analysis, the Chinese eldlerly, NONMEM

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