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不同 CYP2C9 基因型人群中氟比洛芬的基于生理学的药代动力学(PBPK)建模。

Physiologically based pharmacokinetic (PBPK) modeling of flurbiprofen in different CYP2C9 genotypes.

机构信息

School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea.

College of Pharmacy, Dankook University, Cheonan, 31116, Republic of Korea.

出版信息

Arch Pharm Res. 2022 Aug;45(8):584-595. doi: 10.1007/s12272-022-01403-4. Epub 2022 Aug 26.

Abstract

The aim of this study was to establish the physiologically based pharmacokinetic (PBPK) model of flurbiprofen related to CYP2C9 genetic polymorphism and describe the pharmacokinetics of flurbiprofen in different CYP2C9 genotypes. PK-Sim® software was used for the model development and validation. A total of 16 clinical pharmacokinetic data for flurbiprofen in different CYP2C9 genotypes, dose regimens, and age groups were used for the PBPK modeling. Turnover number (k) of CYP2C9 values were optimized to capture the observed profiles in different CYP2C9 genotypes. In the simulation, predicted fraction metabolized by CYP2C9, fraction excreted to urine, bioavailability, and volume of distribution were similar to previously reported values. Predicted plasma concentration-time profiles in different CYP2C9 genotypes were visually similar to the observed profiles. Predicted AUC in CYP2C9*1/2, CYP2C91/3, and CYP2C93/3 genotypes were 1.44-, 2.05-, and 3.67-fold higher than the CYP2C91/*1 genotype. The ranges of fold errors for AUC, C, and t were 0.84-1.00, 0.61-1.22, and 0.74-0.94 in development and 0.59-0.98, 0.52-0.97, and 0.61-1.52 in validation, respectively, which were within the acceptance criterion. Thus, the PBPK model was successfully established and described the pharmacokinetics of flurbiprofen in different CYP2C9 genotypes, dose regimens, and age groups. The present model could guide the decision-making of tailored drug administration strategy by predicting the pharmacokinetics of flurbiprofen in various clinical scenarios.

摘要

本研究旨在建立与 CYP2C9 遗传多态性相关的氟比洛芬的生理基于药代动力学(PBPK)模型,并描述不同 CYP2C9 基因型下氟比洛芬的药代动力学。PK-Sim®软件用于模型的开发和验证。使用了 16 项不同 CYP2C9 基因型、剂量方案和年龄组的氟比洛芬临床药代动力学数据进行 PBPK 建模。CYP2C9 值的周转率(k)进行了优化,以捕捉不同 CYP2C9 基因型下的观察到的特征。在模拟中,预测的由 CYP2C9 代谢的分数、排泄到尿液中的分数、生物利用度和分布体积与先前报道的值相似。不同 CYP2C9 基因型下的预测血浆浓度-时间曲线与观察到的曲线在视觉上相似。在 CYP2C9*1/2、CYP2C91/3 和 CYP2C93/3 基因型中,AUC 预测值分别是 CYP2C91/*1 基因型的 1.44、2.05 和 3.67 倍。AUC、C 和 t 的折叠误差范围在开发和验证中分别为 0.84-1.00、0.61-1.22 和 0.74-0.94,0.59-0.98、0.52-0.97 和 0.61-1.52,均在可接受范围内。因此,成功建立了 PBPK 模型,并描述了不同 CYP2C9 基因型、剂量方案和年龄组下氟比洛芬的药代动力学。该模型可以通过预测各种临床情况下氟比洛芬的药代动力学来指导个体化给药策略的决策。

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