Prediction of drug–drug interactions between roflumilast and CYP3A4/1A2 perpetrators using a physiologically-based pharmacokinetic (PBPK) approach

Guangwei Jia, Congcong Ren, Hongyan Wang, Caixia Fan
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Abstract

This study aimed to develop a physiologically-based pharmacokinetic (PBPK) model to predict changes in the pharmacokinetics (PK) and pharmacodynamics (PD, PDE4 inhibition) of roflumilast (ROF) and ROF N-oxide when co-administered with eight CYP3A4/1A2 perpetrators. The population PBPK model of ROF and ROF N-oxide has been successfully developed and validated based on the four clinical PK studies and five clinical drug-drug interactions (DDIs) studies. In PK simulations, every ratio of prediction to observation for PK parameters fell within the range 0.7 to 1.5. In DDI simulations, except for tow peak concentration ratios (Cmax) of ROF with rifampicin (prediction: 0.63 vs. observation: 0.19) and with cimetidine (prediction: 1.07 vs. observation: 1.85), the remaining predicted ratios closely matched the observed ratios. Additionally, the PBPK model suggested that co-administration with the three perpetrators (cimetidine, enoxacin, and fluconazole) may use with caution, with CYP3A4 strong inhibitor (ketoconazole and itraconazole) or with dual CYP3A41A2 inhibitor (fluvoxamine) may reduce to half-dosage or use with caution, while co-administration with CYP3A4 strong or moderate inducer (rifampicin, efavirenz) should avoid. Overall, the present PBPK model can provide recommendations for adjusting dosing regimens in the presence of DDIs.
采用基于生理学的药代动力学(PBPK)方法预测罗氟司特与 CYP3A4/1A2 致效体之间的药物相互作用
本研究旨在开发一种基于生理学的药代动力学(PBPK)模型,以预测罗氟司特(ROF)和ROF N-氧化物与8种CYP3A4/1A2致效剂合用时的药代动力学(PK)和药效学(PD,PDE4抑制)变化。基于四项临床 PK 研究和五项临床药物相互作用(DDIs)研究,成功开发并验证了 ROF 和 ROF N-氧化物的群体 PBPK 模型。在 PK 模拟中,PK 参数的预测值与观察值的比值均在 0.7 至 1.5 之间。在 DDI 模拟中,除了 ROF 与利福平(预测值:0.63,观察值:0.19)和西咪替丁(预测值:1.07,观察值:1.85)的拖峰浓度比(Cmax)外,其余的预测比值与观察比值非常接近。此外,PBPK 模型表明,与三种致病因子(西咪替丁、依诺沙星和氟康唑)合用时应慎用,与 CYP3A4 强抑制剂(酮康唑和伊曲康唑)或与 CYP3A41A2 双抑制剂(氟伏沙明)合用时应减至半量或慎用,而与 CYP3A4 强或中度诱导剂(利福平、依非韦伦)合用时应避免。总之,本 PBPK 模型可为出现 DDI 时调整给药方案提供建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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