对生物统计管道进行比较研究,用于对in vitro查试验的基准度建模
Kelly E Carstens1, Arif Dönmez2,3, Jui-Hua Hsieh4
1Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, 27711, USA.
Computational toxicology (Amsterdam, Netherlands)
|July 17, 2025
概括
新方法方法 (NAM) 减少了对化学品安全的动物试验. 通过比较四个发育神经毒性 (DNT) NAM数据的分析管道,结果显示出很好的一致性,提高了对结果的信心.
科学领域:
- 毒理学 毒理学 毒理学
- 计算化学是一种计算化学.
- 发育生物学是发展生物学.
背景情况:
- 新方法方法 (NAM) 对于减少化学安全评估中的动物试验至关重要.
- 对于可重复的基准度 (BMC) 估计和不确定性量化,需要进行标准化分析.
- 发育神经毒性 (DNT) 测定需要强大的数据分析管道.
研究的目的:
- 为了比较DNT NAM数据的四个已建立的BMC分析管道的性能.
- 评估不同管道的生物活性结果的一致性和相关性.
- 确定影响不一致的因素,并为可靠的化学安全评估提供管道选择的信息.
主要方法:
- 通过使用四个BMC分析管道评估了321个化学样本:ToxCast (tcpl),CRStats,DNT DIVER (Curvep和Hill).
- 评估的整体活动击中呼叫一致性和BMC估计的相关性.
- 分析了BMC置信区间,双相模型的影响以及选择性生物活性分类.
主要成果:
- 实现了77.2%的整体活动命中呼叫一致性和高度相关的BMC估计 (r = 0.92).
- 不一致主要归因于数据噪声和边界活动水平.
- 管道选择影响BMC下限估计;双相模型对DNT数据很重要;CRstats对选择性活动严格.
结论:
- 已建立的BMC分析管道显示,对DNT NAM数据的总体一致性很好,这增加了对结果的信心.
- 了解管道的优势和不确定性对于准确的生物学解释和监管决策至关重要.
- 标准化分析方法对于在化学安全评估中可靠实施NAM至关重要.
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