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晚期实体瘤患者 Z-ENDOXIFEN 的群体药代动力学。

Population Pharmacokinetics of Z-Endoxifen in Patients With Advanced Solid Tumors.

机构信息

Department of Oncology, Mayo Clinic, Rochester, Minnesota, USA.

CATO SMS, Cary, North Carolina, USA.

出版信息

J Clin Pharmacol. 2022 Sep;62(9):1121-1131. doi: 10.1002/jcph.2053. Epub 2022 Apr 19.

Abstract

The purpose of this study was to develop and validate a population pharmacokinetic model for Z-endoxifen in patients with advanced solid tumors and to identify clinical variables that influence pharmacokinetic parameters. Z-endoxifen-HCl was administered orally once a day on a 28-day cycle (±3 days) over 11 dose levels ranging from 20 to 360 mg. A total of 1256 Z-endoxifen plasma concentration samples from 80 patients were analyzed using nonlinear mixed-effects modeling to develop a population pharmacokinetic model for Z-endoxifen. A 2-compartment model with oral depot and linear elimination adequately described the data. The estimated apparent total clearance, apparent central volume of distribution, and apparent peripheral volume of distribution were 4.89 L/h, 323 L, and 39.7 L, respectively, with weight-effect exponents of 0.75, 1, and 1, respectively. This model was used to explore the effects of clinical and demographic variables on Z-endoxifen pharmacokinetics. Weight, race on clearance, and aspartate aminotransferase on the absorption rate constant were identified as significant covariates in the final model. This novel population pharmacokinetic model provides insight regarding factors that may affect the pharmacokinetics of Z-endoxifen and may assist in the design of future clinical trials.

摘要

本研究旨在开发和验证晚期实体瘤患者 Z-雌莫昔芬的群体药代动力学模型,并确定影响药代动力学参数的临床变量。Z-雌莫昔芬盐酸盐每天口服一次,28 天为一个周期(±3 天),共 11 个剂量水平,范围为 20 至 360mg。对 80 名患者的 1256 个 Z-雌莫昔芬血浆浓度样本进行非线性混合效应模型分析,以建立 Z-雌莫昔芬的群体药代动力学模型。口服储库和线性消除的 2 室模型能够很好地描述数据。估计的表观总清除率、表观中央分布容积和表观外周分布容积分别为 4.89 L/h、323 L 和 39.7 L,体重效应指数分别为 0.75、1 和 1。该模型用于探索临床和人口统计学变量对 Z-雌莫昔芬药代动力学的影响。体重、清除率的种族以及天冬氨酸氨基转移酶对吸收速率常数的影响被确定为最终模型中的重要协变量。该新型群体药代动力学模型提供了有关可能影响 Z-雌莫昔芬药代动力学的因素的见解,并可能有助于未来临床试验的设计。

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