毒理学的机械解释 代谢学数据 代谢学数据
Aniko Kende1, David E Cowie1, Richard A Currie1
1Syngenta Jealott's Hill International Research Centre, Bracknell RG42 6EY, U.K.
Chemical research in toxicology
|August 6, 2025
概括
解释代谢学数据用于毒理学是很困难的. 本研究引入了一种新的方法,使用不良结果途径 (AOP) 来将代谢变化与不良影响联系起来,改善化学品安全评估.
科学领域:
- 毒理学 毒理学 毒理学
- 代谢学 代谢学 代谢学
- 计算生物学 计算生物学
背景情况:
- 解释用于毒理学评估的代谢学数据是具有挑战性的,因为对代谢途径中断和不良健康结果的理解有限.
- 现有的方法很难将观察到的代谢变化与特定的毒理效应联系起来,这阻碍了准确的危险识别.
研究的目的:
- 开发和验证一种新的方法来预测毒理学代谢学数据的不良影响.
- 利用不良结果途径 (AOP) 框架来改进对代谢干扰及其毒理学相关性的解释.
主要方法:
- 结合基于知识的假设生成与基于数据的假设测试.
- 利用不良结果路径 (AOP) 概念来识别和评估关键事件.
- 应用了对原氨基酸氧化酶 (PPO) 抑制的方法,用于证明和验证.
主要成果:
- 拟议的方法有助于创建与AOP关键事件相关的可信代谢物干扰清单.
- 能够在毒理路径的背景下解释差异丰富的代谢物 (DAMs).
- 证明了该方法在评估使用PPO抑制作为案例研究预测不利影响的确定性方面的实用性.
结论:
- 基于AOP的方法通过将代谢变化与不良结果联系起来,提高了代谢学数据的毒理学解释.
- 该方法为生成有毒学意义的关联事件签名提供了一个框架.
- 该方法支持早期化学开发和监管化学安全评估,以确定危险.
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