使用基于生理学的药代动力学模型模拟健康受试者和肾功能受损患者的非布司他药代动力学,Biopharmaceutics & Drug Disposition

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使用基于生理学的药代动力学模型模拟健康受试者和肾功能受损患者的非布司他药代动力学
Biopharmaceutics & Drug Disposition ( IF 1.7 ) Pub Date : 2022-06-24 , DOI: 10.1002/bdd.2325
Yichao Xu ₁ , Jinliang Chen ₁ , Zourong Ruan ₁ , Bo Jiang ₁ , Dandan Yang ₁ , Yin Hu ₁ , Honggang Lou ₁

Affiliation

美国风湿病学会痛风管理指南推荐非布司他作为降低痛风患者尿酸盐水平的一线疗法。目前，这种药物的处方主要是根据医生的临床经验。未考虑临床和人口统计学变量对非布索坦的生物利用度和治疗效果的潜在影响。本研究建立了基于生理学的非布司他药代动力学 (PBPK) 模型，从而为痛风患者的个体化给药提供了理论依据。模拟和验证了与健康受试者和肾功能正常的痛风患者相对应的血浆浓度-时间曲线；然后，该模型用于预测该药物在患有不同程度肾功能损害的痛风患者中的药代动力学（PK）数据。误差值（预测值/观察值）用于验证 PBPK 模型预测的模拟 PK 参数，包括血浆浓度-时间曲线下面积、最大血浆浓度和达到最大血浆浓度的时间。考虑到所有错误倍数的变化都小于 2，PBPK 模型是。在患有轻度肾功能不全、中度肾功能不全、重度肾功能不全和终末期肾病 (ESRD) 的受试者中，预测的 AUC 包括血浆浓度-时间曲线下面积、最大血浆浓度和达到最大血浆浓度的时间。考虑到所有错误倍数的变化都小于 2，PBPK 模型是。在患有轻度肾功能不全、中度肾功能不全、重度肾功能不全和终末期肾病 (ESRD) 的受试者中，预测的 AUC 包括血浆浓度-时间曲线下面积、最大血浆浓度和达到最大血浆浓度的时间。考虑到所有错误倍数的变化都小于 2，PBPK 模型是。在患有轻度肾功能不全、中度肾功能不全、重度肾功能不全和终末期肾病 (ESRD) 的受试者中，预测的 AUC与肾功能正常的痛风患者相比，_{0-24h值分别增加了1.62、1.74、2.27和2.65倍。}总体而言，结果表明，本研究构建的 PBPK 模型可以预测不同程度肾功能受损的痛风患者的药代动力学变化。

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Simulation of febuxostat pharmacokinetics in healthy subjects and patients with impaired kidney function using physiologically based pharmacokinetic modeling

Febuxostat is recommended by the American College of Rheumatology Gout Management Guidelines as a first-line therapy for lowering the level of urate in patients with gout. At present, this drug is being prescribed mainly based on the clinical experience of doctors. The potential effects of clinical and demographic variables on the bioavailability and therapeutic effectiveness of febuxostat are not being considered. In this study a physiologically based pharmacokinetic (PBPK) model of febuxostat was developed, thereby providing a theoretical basis for the individualized dosing of this drug in gout patients. The plasma concentration–time profiles corresponding to healthy subjects and gout patients with normal kidney function were simulated and validated; then, the model was used to predict the pharmacokinetic (PK) data of the drug in gout patients suffering from varying degrees of impaired kidney function. The error values (the predicted value/observed value) were used to validate the simulated PK parameters predicted by the PBPK model, including the area under the plasma concentration–time curve, the maximum plasma concentration, and time to maximum plasma concentration. Considering that to all error fold changes were smaller than 2, the PBPK model was. In subjects suffering from mild kidney impairment, moderate kidney impairment, severe kidney impairment, and endstage kidney disease (ESRD), the predicted AUC_0-24h values increased by 1.62, 1.74, 2.27, and 2.65-fold, respectively, compared to gout patients with normal kidney function. Overall, the results showed that the PBPK model constructed in this study predict the pharmacokinetic changes in gout patients suffering from varying degrees of impaired kidney function.

更新日期：2022-06-24

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