Development of a network of carcinogenicity adverse outcome pathways and its employment as an evidence framework for safety assessment

IF 4.5 2区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL
Alex N Cayley, Robert S Foster, Emma Hill, Steven Kane, Grace Kocks, Alun Myden, Daniel Newman, Susanne A Stalford, Jonathan D Vessey, Reza Zarei, Antonio Anax F De Oliveira
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引用次数: 4

Abstract

The traditional paradigm for safety assessment of chemicals for their carcinogenic potential to humans relies heavily on a battery of well-established genotoxicity tests, usually followed up by long-term, high-dose rodent studies. There are a variety of problems with this approach, not least that the rodent may not always be the best model to predict toxicity in humans. Consequently, new approach methodologies (NAMs) are being developed to replace or enhance predictions coming from the existing assays. However, a combination of the data arising from NAMs is likely to be required to improve upon the current paradigm, and consequently a framework is needed to combine evidence in a meaningful way. Adverse outcome pathways (AOPs) represent an ideal construct on which to organize this evidence. In this work, a data structure outlined previously was used to capture AOPs and evidence relating to carcinogenicity. Knowledge held within the predictive system Derek Nexus was extracted, built upon, and arranged into a coherent network containing 37 AOPs. 60 assays and 351 in silico alerts were then associated with KEs in this network, and it was brought to life by associating data and contextualizing evidence and predictions for over 13,400 compounds. Initial investigations into using the network to view knowledge and reason between evidence in different ways were made. Organizing knowledge and evidence in this way provides a flexible framework on which to carry out more consistent and meaningful carcinogenicity safety assessments in many different contexts.

致癌性不良后果途径网络的建立及其作为安全性评估的证据框架
对化学品对人类的致癌潜力进行安全评估的传统模式在很大程度上依赖于一系列已确立的遗传毒性试验,随后通常进行长期、高剂量的啮齿动物研究。这种方法存在各种各样的问题,尤其是啮齿动物可能并不总是预测人类毒性的最佳模型。因此,正在开发新的方法方法(NAMs),以取代或加强来自现有分析的预测。然而,很可能需要结合NAMs产生的数据来改进目前的范例,因此需要一个框架来以有意义的方式结合证据。不良结果通路(AOPs)代表了组织这一证据的理想结构。在这项工作中,先前概述的数据结构用于捕获AOPs和与致癌性有关的证据。Derek Nexus的预测系统中包含的知识被提取、构建并排列成一个包含37个aop的连贯网络。然后,将60项分析和351个计算机警报与该网络中的KEs关联起来,并通过将数据与超过13400种化合物的证据和预测关联起来,将其变为现实。对使用网络以不同方式看待证据之间的知识和推理进行了初步调查。以这种方式组织知识和证据提供了一个灵活的框架,可据此在许多不同情况下开展更一致和更有意义的致癌性安全评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Altex-Alternatives To Animal Experimentation
Altex-Alternatives To Animal Experimentation MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
7.70
自引率
8.90%
发文量
89
审稿时长
2 months
期刊介绍: ALTEX publishes original articles, short communications, reviews, as well as news and comments and meeting reports. Manuscripts submitted to ALTEX are evaluated by two expert reviewers. The evaluation takes into account the scientific merit of a manuscript and its contribution to animal welfare and the 3R principle.
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