鼠PermQ:一种基于透性和 perfusion 的生理学基础的药物动力学模型,用于更好地预测大鼠药物度-时间概况
Yifan Gong1, Ken Korzekwa1, Swati Nagar1
1Department of Pharmaceutical Sciences, Temple University School of Pharmacy, Philadelphia, Pennsylvania.
概括
一个新的基于生理学的药理动力学模型,老鼠PermQ,改善了老鼠的药物度-时间预测. 这个模型准确地预测了药物行为,有助于理解分发和消除机制.
科学领域:
- 药理动力学和药物新陈代谢
- 计算生物学和生物信息学
- 毒理学和药理学 毒理学和药理学
背景情况:
- 基于生理学的药理动力学 (PBPK) 模型对于预测药物度-时间 (C-t) 概况至关重要.
- 现有的模型可能无法完全捕捉特定物种中复杂的药物分发和运输机制.
- 准确预测药物行为对于有效的药物开发和安全性评估至关重要.
研究的目的:
- 开发和验证一种新的透性和 perfusion-limited PBPK 模型用于大鼠,命名为大鼠 PermQ.
- 与现有模型相比,提高大鼠中药物C-t概况的预测准确度.
- 用该模型来模拟与药物吸收和分发机制相关的假设.
主要方法:
- 开发了老鼠的PermQ模型,其中包括可逆的毛细血管-间歇液体分布,细胞内分离,以及酸性和基本性药物的特定运输机制.
- 收集了用于模型参数化的体外和体外实验数据.
- 与罗杰斯和罗兰德 (RR) 和基于膜的 perfusion-limited 模型对比大鼠 PermQ 的 C-t 概况预测,用于七种不同的药物.
主要成果:
- 鼠的PermQ在酸性,中性和基性药物中表现出可比或优异的C-t概况与RR和 perfusion-limited模型的预测.
- 包括活性吸收运输和蛋白质结合校正改善了酸性药物的预测.
- 一个浅的分布区显著提高了基本药物的预测.
结论:
- 鼠类PermQ提供了一个强大的框架来预测鼠类药物药理动力学,表现与现有的PBPK模型一样好或更好.
- 该模型促进了对药物吸收和分布的假设测试,强调了精确的体外参数的重要性,如血蛋白结合.
- 鼠的PermQ可以帮助阐明对大鼠和潜在的人类药物分配和消除现象的不太了解.
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