对PARP抑制剂Niraparib的生理学基础的药动力学建模
Gareth J Lewis1, Roxanne C Jewell2, Anu Shilpa Krishnatry3
1GlaxoSmithKline, DMPK, Preclinical Sciences, Stevenage, UK.
CPT: pharmacometrics & systems pharmacology
|January 14, 2026
概括
一个新的基于生理学的尼拉帕里布的药理动力学模型表明,它被碳氧乙酶1代谢. 该模型预测了在各种虚拟人群中对niraparib的药物相互作用风险最小.
科学领域:
- 药理动力学 药理动力学
- 药物新陈代谢 药物新陈代谢
- 在瘤学瘤学.
背景情况:
- 尼拉巴里布是一种用于癌症治疗的PARP抑制剂.
- 了解其药理动力学特征和潜在的药物相互作用 (DDI) 对于安全有效的使用至关重要.
- 基于生理学的药理动力学 (PBPK) 建模为预测不同人群和场景中的药物行为提供了一个强大的工具.
研究的目的:
- 开发和验证尼拉巴里布及其主要代谢物 (M1) 的PBPK模型.
- 评估niraparib的代谢途径并确定其主要代谢酶.
- 在各种虚拟人群中预测niraparib的药理动力学行为和DDI潜力,包括肝功能障碍和特定种族的人群.
主要方法:
- 在体外实验中使用肝脏S9,显微体和肝细胞来识别niraparib的代谢途径.
- 开发一个结合虚拟癌症种群和临床化学数据的PBPK模型.
- 在临床研究和虚拟人群 (肝功能障碍,中国,日本) 中模拟niraparib和M1暴露.
- 评估niraparib与主要药物代谢酶和转运体的相互作用潜力.
主要成果:
- 尼拉巴主要通过碳素化酶1 (CES1) 代谢成一种酸代谢物 (M1).
- 在多项临床研究中,PBPK模型准确地预测了Niraparib和M1暴露在2倍之内.
- 尼拉帕里布在高剂量时显示DDI负担最小,没有CYP抑制或基质活性,并具有弱CYP1A2诱导.
- 对MATE-1/-2K基质,如甲胺,预测有中度的抑制风险.
结论:
- 已经开发了对niraparib及其代谢物M1进行验证的PBPK模型.
- 与其他一些PARP抑制剂相比,Niraparib表现出有利的DDI概况.
- 该模型可以预测不同虚拟人群中的尼拉帕里布暴露,并告知潜在的DDI风险,特别是CYP1A2和MATE-1/-2K基质.
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