药品
内生
药理学
药物代谢
CYP3A型
药代动力学
医学
内科学
新陈代谢
细胞色素P450
作者
Hiroaki Takubo,Toshio Taniguchi,Yukihiro Nomura
标识
DOI:10.1016/j.dmd.2025.100109
摘要
CYP3A-mediated drug-drug interactions are a source of safety concerns for new molecular entities. In this study, the focus was on endogenous biomarkers, the urinary or plasma 6β-hydroxycortisol/cortisol (6β-OHF/F) ratio and the 6β-hydroxylation clearance of cortisol (CLm[6β]), for the quantitative prediction of CYP3A-mediated drug-drug interactions. The fold change of these biomarkers and the ratio of the area under the plasma concentration-time curve (AUCR) in the presence and absence of a coadministered perpetrator were obtained from the literature. A scaling factor was set in a mechanistic static pharmacokinetic model equation. The scaling factor was then calculated from the fold change of the endogenous biomarker and used for prediction. By applying the approach using the urinary 6β-OHF/F ratio to 29 perpetrators with no to strong induction or inhibition potential or both, the success rate of AUCR prediction within 2-fold of the observed AUCR was 73.1%. Among these, the success rate for inducers was 61%, but for inhibitors and others, it was approximately 80%, showing good prediction performance. Based on the same concept, approaches using the plasma 6β-OHF/F ratio and CLm(6β) were exploratory applied to 1 and 5 perpetrators, respectively, with success rates of 100% and 90.3%, respectively. However, it should be noted that the number of perpetrators for CLm(6β) was 5. Approaches using the urinary 6β-OHF/F ratio and CLm(6β) may be useful tools to quantitatively predict the CYP3A inhibition potential and the CYP3A induction and inhibition potential, respectively, in the early clinical stages of drug development. SIGNIFICANCE STATEMENT: Some studies have reported poor correlation between urinary 6β-hydroxycortisol/cortisol ratio and CYP3A activity. In this study using 29 perpetrators, our approach using this biomarker showed good prediction of CYP3A inhibition-mediated drug-drug interactions.
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