从原始数据到基于NAM的信息的漫长道路:关于数据层和处理步骤的概述.
Jonathan Blum1, Markus Brüll1, Jan G Hengstler2
1In vitro Toxicology and Biomedicine, University of Konstanz, Konstanz, Germany.
ALTEX
|January 16, 2025
概括
了解新方法方法 (NAM) 中的数据处理是至关重要的. 一致的数据管理和解释确保可重复和可靠的毒理学结果,以获得监管认可.
科学领域:
- 毒理学 毒理学 毒理学
- 计算生物学 计算生物学
- 数据科学数据科学数据科学
背景情况:
- 毒理学测试方法产生原始数据,需要复杂的处理管道.
- 新方法方法 (NAM) 依赖于从原始输出到最终分类的多层数据处理.
- 数据处理中的变化可能会对NAM的结果和监管接受产生重大影响.
研究的目的:
- 提供NAM开发和应用中关键数据级别的概述.
- 为了说明这些级别之间的数据处理和评估步骤.
- 强调数据处理对NAM信任和可重复性的重要性.
主要方法:
- 对毒理学试验方法中的数据处理管道的审查.
- 数据水平的分析从原始产量到击中定义.
- 数据处理步骤及其对结果的影响的说明.
主要成果:
- 数据处理管道是复杂的,涉及多个层.
- 不同处理相同的原始数据可能会导致不同的最终结果.
- 对数据处理意义的认识对于NAM在风险评估中至关重要.
结论:
- 数据管理,处理和解释对于全面的NAM定义至关重要.
- 在报告模板 (例如,ToxTemp) 中包括处理管道是必要的.
- 了解数据处理可以建立信任,确保接受,并促进NAM结果的可重现性.
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