对高血蛋白结合化合物的药物相互作用的预测
David Tess1, Makayla Harrison2,3, Jian Lin2
1Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Cambridge, Massachusetts, USA.
The AAPS journal
|December 11, 2024
概括
对高度结合的化合物进行准确的药物相互作用 (DDI) 预测,现在可以使用等离子体 (fu,p) 中的实验性未结合分数值. 这种方法尽量减少假阳性,并确保可靠地识别临床DDI风险.
科学领域:
- 药理动力学和药物新陈代谢
- 药物安全与药物相互作用
背景情况:
- 准确预测药物相互作用 (DDI) 对临床研究设计和风险评估至关重要.
- 监管机构历来在对高度结合的化合物的DDI预测中使用了血未结合分数 (fu,p) 的1%下限,导致频繁的错误阳性.
- 国际协调理事会 (ICH) M12指南现在允许在高度结合的化合物中预测DDI的实验fu,p值.
研究的目的:
- 用实验fu,p值来评估对高度结合的化合物DDI预测的准确性.
- 评估基本和机械静态模型在预测fu,p<1%和观察到的临床DDI>20%的化合物临床DDI风险方面的性能.
主要方法:
- 对一组药物的评估,实验确定fu,p1%和已知的临床DDI>20%.
- 使用实验fu,p值进行DDI风险评估的基本和机械静态模型的应用.
- 模型预测与已建立的临床DDI数据的比较.
主要成果:
- 机械静态模型使用实验fu,p值准确地标记了所有被评估的DDI风险化合物,没有假负值.
- 基本静态模型确定了所有化合物的DDI风险,只有一个例外 (阿尔莫雷克桑特的CYP2D6抑制).
- 实验性fu,p测量提高了对高度结合化合物的DDI预测的准确性.
结论:
- 对血蛋白结合的实验测量 (fu,p) 能够准确预测高度结合化合物的DDI潜力.
- 使用实际的fu,p值提高了DDI风险评估的可靠性,与最近的监管准则保持一致.
- 这种方法通过减少错误的DDI预测,支持改进临床试验设计和药物安全性评估.
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