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基于生理学的 fedratinib 药代动力学模型的进展:在同时抑制 CYP3A4 和 CYP2C19 的双重抑制剂存在下更新剂量指导。

Advancements in physiologically based pharmacokinetic modeling for fedratinib: updating dose guidance in the presence of a dual inhibitor of CYP3A4 and CYP2C19.

机构信息

Bristol Myers Squibb, Princeton, NJ, USA.

出版信息

Cancer Chemother Pharmacol. 2024 Oct;94(4):549-559. doi: 10.1007/s00280-024-04696-y. Epub 2024 Aug 7.

Abstract

PURPOSE

A physiologically based pharmacokinetic (PBPK) model for fedratinib was updated and revalidated to bridge a gap between the observed drug-drug interaction (DDI) of a single sub-efficacious dose in healthy participants and the potential DDI in patients with cancer at steady state. The study aimed to establish an appropriate dose for fedratinib in patients coadministered with dual CYP3A4 and CYP2C19 inhibitors, providing quantitative evidence to inform dosing guidance.

METHODS

The original minimal PBPK model was developed using Simcyp Simulator v17. The model was updated by substituting a single distribution rate (Q) with 2 separate rates (CL/CL) and transitioning to v20. Model parameter updates were further informed with 3 clinical studies, and 3 more studies served as independent validation data. The validated model was applied to simulate potential DDIs between fedratinib and a known dual inhibitor of CYP3A4 and CYP2C19 (fluconazole).

RESULTS

Coadministration of fedratinib with fluconazole in patients was predicted to increase fedratinib exposure by < 2-fold in all simulated scenarios. For patients with cancer receiving the approved dose of fedratinib 400 mg once daily along with fluconazole 200 mg daily, the model predicted an approximate 50% increase in fedratinib exposure at steady state.

CONCLUSIONS

The updated PBPK model improved description of the observed pharmacokinetics and predicted a low risk of clinically significant DDIs between fedratinib and fluconazole. The quantitative evidence serves as a primary foundation for providing dose guidance in clinical practice for the coadministration of fedratinib with dual CYP3A4 and CYP2C19 inhibitors.

摘要

目的

更新并重新验证了 fedratinib 的基于生理学的药代动力学(PBPK)模型,以弥合在健康参与者中观察到的单一亚有效剂量的药物相互作用(DDI)与稳态下癌症患者的潜在 DDI 之间的差距。该研究旨在为接受双重 CYP3A4 和 CYP2C19 抑制剂联合治疗的患者确定 fedratinib 的适当剂量,提供定量证据以指导给药。

方法

原始最小 PBPK 模型使用 Simcyp Simulator v17 开发。通过用 2 个单独的速率(CL/CL)替代单个分布速率(Q)并过渡到 v20 来更新模型。模型参数更新进一步通过 3 项临床研究提供信息,并通过另外 3 项研究作为独立验证数据。验证后的模型用于模拟 fedratinib 与已知的双重 CYP3A4 和 CYP2C19 抑制剂(氟康唑)之间的潜在 DDI。

结果

在所有模拟情况下,预测患者同时服用 fedratinib 和氟康唑会使 fedratinib 的暴露量增加不到 2 倍。对于接受批准剂量的 fedratinib 400mg 每天一次与氟康唑 200mg 每天一次的癌症患者,模型预测稳态时 fedratinib 的暴露量增加约 50%。

结论

更新的 PBPK 模型改善了对观察到的药代动力学的描述,并预测了 fedratinib 与氟康唑之间发生临床显著 DDI 的风险较低。定量证据为提供临床实践中 fedratinib 与双重 CYP3A4 和 CYP2C19 抑制剂联合给药的剂量指导提供了主要依据。

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