Suppr超能文献

机制验证。

Mechanistic validation.

机构信息

Center for Alternatives to Animal Testing (CAAT), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.

出版信息

ALTEX. 2013;30(2):119-30. doi: 10.14573/altex.2013.2.119.

Abstract

Validation of new approaches in regulatory toxicology is commonly defined as the independent assessment of the reproducibility and relevance (the scientific basis and predictive capacity) of a test for a particular purpose. In large ring trials, the emphasis to date has been mainly on reproducibility and predictive capacity (comparison to the traditional test) with less attention given to the scientific or mechanistic basis. Assessing predictive capacity is difficult for novel approaches (which are based on mechanism), such as pathways of toxicity or the complex networks within the organism (systems toxicology). This is highly relevant for implementing Toxicology for the 21st Century, either by high-throughput testing in the ToxCast/Tox21 project or omics-based testing in the Human Toxome Project. This article explores the mostly neglected assessment of a test's scientific basis, which moves mechanism and causality to the foreground when validating/qualifying tests. Such mechanistic validation faces the problem of establishing causality in complex systems. However, pragmatic adaptations of the Bradford Hill criteria, as well as bioinformatic tools, are emerging. As critical infrastructures of the organism are perturbed by a toxic mechanism we argue that by focusing on the target of toxicity and its vulnerability, in addition to the way it is perturbed, we can anchor the identification of the mechanism and its verification.

摘要

新方法在监管毒理学中的验证通常被定义为对特定目的的测试的可重复性和相关性(科学依据和预测能力)进行独立评估。在大型环试验中,迄今为止的重点主要是可重复性和预测能力(与传统测试相比),而对科学或机制基础的关注较少。对于新方法(基于机制,如毒性途径或生物体内部的复杂网络(系统毒理学)),评估预测能力具有挑战性。这对于实施 21 世纪毒理学非常重要,无论是通过 ToxCast/Tox21 项目中的高通量测试还是人类毒库项目中的基于组学的测试。本文探讨了对测试科学依据的评估,这在验证/确定测试时将机制和因果关系置于突出位置。这种机制验证面临着在复杂系统中建立因果关系的问题。然而,布拉德福德·希尔标准的实用改编以及生物信息学工具正在出现。由于有毒机制扰乱了生物体的关键基础设施,我们认为,除了扰乱的方式外,通过关注毒性的靶标及其脆弱性,我们可以确定机制并验证其验证。

相似文献

1
Mechanistic validation.机制验证。
ALTEX. 2013;30(2):119-30. doi: 10.14573/altex.2013.2.119.
6
2015 Lush Science Prize.2015年鲁什科学奖。
Altern Lab Anim. 2016 Oct;44(5):461-468. doi: 10.1177/026119291604400510.
7

引用本文的文献

4
A framework for establishing scientific confidence in new approach methodologies.建立新方法学科学置信度的框架。
Arch Toxicol. 2022 Nov;96(11):2865-2879. doi: 10.1007/s00204-022-03365-4. Epub 2022 Aug 20.

本文引用的文献

1
Big biology: The 'omes puzzle.大生物学:“组学”难题。
Nature. 2013 Feb 28;494(7438):416-9. doi: 10.1038/494416a.
2
15 years out: reinventing ICCVAM.15年后:重塑ICCVAM。
Environ Health Perspect. 2013 Feb;121(2):a40. doi: 10.1289/ehp.1206292.
3
Observability of complex systems.复杂系统的可观测性。
Proc Natl Acad Sci U S A. 2013 Feb 12;110(7):2460-5. doi: 10.1073/pnas.1215508110. Epub 2013 Jan 28.
7
Predictive models and computational toxicology.预测模型与计算毒理学
Methods Mol Biol. 2013;947:343-74. doi: 10.1007/978-1-62703-131-8_26.
8
Detecting causality in complex ecosystems.检测复杂生态系统中的因果关系。
Science. 2012 Oct 26;338(6106):496-500. doi: 10.1126/science.1227079. Epub 2012 Sep 20.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验