上海交通大学学报(医学版) ›› 2024, Vol. 44 ›› Issue (11): 1414-1421.doi: 10.3969/j.issn.1674-8115.2024.11.008

• 论著 · 临床研究 • 上一篇    

基于生理药物代谢动力学模型预测氯氮平联合用药的药物相互作用

牟凡1(), 黄志伟2, 程渝1, 赵雪3, 李华芳2, 禹顺英1()   

  1. 1.上海交通大学医学院附属精神卫生中心遗传室,上海 200030
    2.上海交通大学医学院附属精神卫生中心药物临床试验机构,上海 200030
    3.上海交通大学医学院附属精神卫生中心临床研究中心,上海 200030
  • 收稿日期:2024-05-22 接受日期:2024-06-24 出版日期:2024-11-28 发布日期:2024-11-28
  • 通讯作者: 禹顺英 E-mail:moufan2021@163.com;yushunying@smhc.org.cn
  • 作者简介:牟 凡(1996—),女,硕士生;电子信箱:moufan2021@163.com
  • 基金资助:
    上海市精神卫生中心临床研究中心(CRC2021ZD02);上海交通大学“交大之星”计划医工交叉研究基金(YG2023LC14)

Prediction of drug-drug interactions in clozapine combination therapy based on physiologically based pharmacokinetic model

MOU Fan1(), HUANG Zhiwei2, CHENG Yu1, ZHAO Xue3, LI Huafang2, YU Shunying1()   

  1. 1.Genetic Biochemistry Laboratory, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
    2.Drug Clinical Trial Institution, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
    3.Clinical Research Center, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
  • Received:2024-05-22 Accepted:2024-06-24 Online:2024-11-28 Published:2024-11-28
  • Contact: YU Shunying E-mail:moufan2021@163.com;yushunying@smhc.org.cn
  • Supported by:
    Clinical Research Center at Shanghai Mental Health Center(CRC2021ZD02);Medical Engineering Cross Research Fund(YG2023LC14)

摘要:

目的·以氯氮平-氟伏沙明合用为例,通过构建针对中国群体的生理药物代谢动力学(physiologically based pharmacokinetic,PBPK)模型,预测氯氮平联合用药的药物相互作用(drug-drug interaction,DDI)并对氯氮平进行剂量优化。方法·通过文献及药理学相关数据库获取氯氮平及氟伏沙明的基本理化性质参数,药物吸收、分布、代谢及排泄(absorption,distribution, metabolism and excretion,ADME)相关参数及中国群体的生理解剖相关参数,利用PK-Sim?软件构建2种药物的PBPK模型。以平均百分比误差(mean percentage error,MPE)和平均绝对百分比误差(mean absolute percentage error,MAPE),或者预测药时曲线下面积(area under the curve,AUC)或峰浓度(peak concentration,Cmax)与实测AUC或Cmax的比值为判断指标,并通过真实世界血药浓度数据进行模型验证。在此基础上结合氟伏沙明对氯氮平的抑制作用参数构建氯氮平-氟伏沙明联合用药的PBPK模型,预测氯氮平的药物代谢动力学变化。以药时曲线下面积比值(area under the curve ratio,AUCR)或峰浓度比值(peak concentration ratio,CmaxR)的90%置信区间为评价指标判断是否存在临床显著的DDI(无效应边界为80%~125%)。根据PBPK模型量化氯氮平-氟伏沙明联合用药后氯氮平的药物代谢动力学变化,并制定氯氮平的剂量优化方案。结果·构建的氯氮平、氟伏沙明模型验证的MPE绝对值≤10%且MAPE<25%,说明预测的药时曲线是准确的。氯氮平-氟伏沙明合用的PBPK模型的AUC预测值与实测值的比值在1.25以内,可准确地预测药物代谢动力学参数。氯氮平-氟伏沙明联用模型的预测结果提示,氯氮平-氟伏沙明联合用药的AUCR和CmaxR的90%置信区间均不完全位于无效应边界内,说明两药合用会发生临床显著性的DDI。此外,PBPK模型的剂量优化结果提示:受试者联合服用氯氮平及氟伏沙明时,氯氮平的剂量减少至原本剂量的50%,可使氯氮平的暴露水平与单药治疗时保持一致。结论·研究建立的PBPK模型可以较好模拟联合用药对氯氮平药物代谢动力学的影响,对于预测药物可能的相互作用及剂量优化方案有参考意义。如果治疗过程中需要合用氯氮平和氟伏沙明,须警惕临床显著的DDI,并应优化氯氮平的剂量。

关键词: 氯氮平, 联合用药, 药物相互作用, 生理药物代谢动力学模型

Abstract:

Objective ·To develop physiologically based pharmacokinetic (PBPK) models specifically designed for the Chinese population by utilizing the combination of clozapine and fluvoxamine as a case, and predict the drug-drug interaction (DDI) associated with the combination medication of clozapine, ultimately optimizing the dosage of clozapine. Methods ·By obtaining the physicochemical parameters, absorption, distribution, metabolism, excretion (ADME)-related parameters, and physiologically relevant parameters of the Chinese population through literature and pharmacology-related databases, PBPK models for the clozapine and fluvoxamine were constructed by using PK-Sim? software. The models′ accuracy was evaluated by comparing predicted values of the area under the curve (AUC) and peak concentration (Cmax) to observed data, using the mean percentage error (MPE) and mean absolute percentage error (MAPE) as evaluation indicators. The models were validated against real-world plasma drug concentration data. Additionally, combining the inhibitory effect of fluvoxamine on clozapine, models for the combination therapy of clozapine and fluvoxamine were developed to predict the pharmacokinetic changes of clozapine. The presence of clinically significant DDI was determined by using the 90% confidence interval of the AUC ratio (AUCR) or Cmax ratio (CmaxR) as evaluation metrics, with a non-effect boundary set at 80%?125%. The pharmacokinetic changes of clozapine upon co-administration with fluvoxamine based on PBPK models were quantified, and a dosage optimization for clozapine was developed. Results ·The constructed model of clozapine and fluvoxamine was considered accurate if the absolute value of the MPE was ≤10% and the MAPE was <25% during validation, indicating that the predicted concentration-time curves were accurate. The PBPK model for the co-administration of clozapine and fluvoxamine was able to accurately predict pharmacokinetic parameters if the ratio of predicted AUC to observed AUC was within 1.25. The prediction of PBPK model for the co-administration showed that the 90% confidence intervals for AUCR and CmaxR of the combination therapy of clozapine and fluvoxamine were not entirely within the ineffective effect boundary, indicating a clinically significant DDI when these two drugs were used concomitantly. Moreover, the dose optimization according to the PBPK models indicated that when subjects were co-administered with clozapine and fluvoxamine, reducing the dose of clozapine to 50% of the original dose could maintain the exposure levels of clozapine consistent with monotherapy. Conclusion ·The established PBPK model can effectively simulate the impact of combination therapy on pharmacokinetic changes of clozapine, providing valuable insights for predicting potential DDI and optimizing dosage regimens. If clozapine needs to be co-administered with fluvoxamine during the treatment, clinicians should remain vigilant for clinically significant DDI and contemplate optimizing the dosage of clozapine accordingly.

Key words: clozapine, combination medication, drug-drug interaction, physiologically based pharmacokinetic model

中图分类号: