建立一个基于生理学的阿尔德海德氧化酶和双阿尔德海德氧化酶-CYP基质的药理动力学框架
Nihan Izat1, Jayaprakasam Bolleddula2, Pasquale Carione3
1Centre for Applied Pharmacokinetic Research, The University of Manchester, Manchester, UK.
CPT: pharmacometrics & systems pharmacology
|October 24, 2024
概括
基于生理学上的药理动力学 (PBPK) 建模改善了阿尔德海德氧化酶 (AO) 和细胞染色体P450s (CYPs) 通过药物清除的预测. 该框架有助于评估双AO-CYP基质的临床药物相互作用风险.
科学领域:
- 药理学 药理学是指药理学的学科.
- 药物新陈代谢 药物新陈代谢
- 药理动力学 药理动力学
背景情况:
- 氧化酶 (AO) 对于清除许多药物至关重要,通常与细胞染色体P450s (CYPs) 一起.
- 需要对AO介导药物清除进行定量框架.
- 基于生理学上的药理动力学 (PBPK) 建模可能会解决双AO-CYP基质的这一差距.
研究的目的:
- 评估PBPK建模对预测AO和双AO-CYP基质的药理动学的有用性.
- 开发和验证PBPK建模框架,用于评估临床药物相互作用 (DDI) 风险.
主要方法:
- 使用体外数据开发了六种药物 (capmatinib,idelalisib,lenvatinib,zaleplon,ziprasidone,zoniporide) 的PBPK模型.
- 模型包含经验缩放因子 (ESF),并通过临床药理动力学,质量平衡和DDI数据进行了改进/验证.
- 由AO (fm_AO) 代谢的部分由于有限的AO抑制剂数据被间接验证.
主要成果:
- 使用ESF的PBPK模型改善了清除预测 (GMFE ≤1.4倍) 与单独基于生理学的缩放 (高达五倍) 相比.
- 质量平衡数据对于准确的fm_AO预测至关重要,防止卡普马提尼布的四倍低预测.
- 对CYP3A4调节的预测药物相互作用比率 (AUCR) 在观察值的1.5倍之内.
结论:
- 一个基于PBPK的新型框架有效地预测了AO介导的药理动力学.
- 这种方法可以对双AO-CYP基质的临床DDI风险进行定量评估.
- PBPK框架支持在药物开发中采用总体证据方法.
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