The Adverse Outcome Pathway: A Conceptual Framework to Support Toxicity Testing in the Twenty-First Century

不良结局途径 计算机科学 背景(考古学) 钥匙(锁) 文档 结果(博弈论) 事件(粒子物理) 风险分析(工程) 数据科学 生化工程 计算生物学 工程类 生物 医学 计算机安全 古生物学 物理 数学 数理经济学 量子力学 程序设计语言
作者
Edward Perkins,Natàlia García‐Reyero,Stephen W. Edwards,Clemens Wittwehr,Daniel L. Villeneuve,Daniel F. Lyons,Gerald T. Ankley
出处
期刊:Methods in pharmacology and toxicology 卷期号:: 1-26 被引量:15
标识
DOI:10.1007/978-1-4939-2778-4_1
摘要

The need to rapidly characterize the risk of large numbers of chemicals has moved the traditional toxicological paradigm from animal testing to a pathway-based approach using in vitro assay systems and modeling where possible. Adverse Outcome Pathways (AOPs) provide a conceptual framework that can be used to link in vitro assay results to whole animal effects in a pathway context. AOPs are defined and examples are provided to demonstrate key characteristics of AOPs. To support development and application of AOPs, a knowledge base has been developed containing a Wiki site designed to permit documentation of AOPs in a crowd-sourced manner. Both empirical and computational methods are demonstrated to play a significant role in AOP development. The combination of computational approaches, including different modeling efforts, together with apical end points within the pathway-based framework will allow for a better understanding of the linkage of events from a molecular initiating event to a potential adverse outcome, therefore defining key events, AOPs, and even networks of AOPS. While these approaches are indeed very promising, the ability to understand and define key events and key event relationships will remain one of the more complex and challenging efforts within AOP development. In order to make AOPs useful for risk assessment these challenges need to be understood and overcome. An interdisciplinary approach including apical and molecular measurements, computational, and modeling efforts is currently being one of the most promising approaches to ensure AOPs become the useful framework they were designed to be.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
斑比发布了新的文献求助10
2秒前
JUN发布了新的文献求助10
2秒前
3秒前
bkagyin应助澄桦采纳,获得10
3秒前
天真似狮发布了新的文献求助10
5秒前
6秒前
7秒前
科研通AI6应助厚朴采纳,获得10
7秒前
lzp完成签到 ,获得积分10
8秒前
8秒前
已知中的未知完成签到 ,获得积分10
8秒前
8秒前
chenbin1105完成签到,获得积分10
9秒前
量子星尘发布了新的文献求助10
9秒前
CipherSage应助大胆的魔镜采纳,获得10
9秒前
10秒前
CipherSage应助sxh采纳,获得10
10秒前
完美世界应助明芬采纳,获得10
10秒前
renxin完成签到,获得积分10
10秒前
11秒前
11秒前
11秒前
万能图书馆应助fjnm采纳,获得10
11秒前
高手发布了新的文献求助10
12秒前
小江不饿完成签到,获得积分10
12秒前
顺利的似狮完成签到,获得积分10
13秒前
李健应助renxin采纳,获得10
14秒前
52hzzz关注了科研通微信公众号
14秒前
fanfan发布了新的文献求助10
15秒前
15秒前
17秒前
17秒前
宁羽发布了新的文献求助10
18秒前
大块发布了新的文献求助10
19秒前
王之争霸完成签到,获得积分10
19秒前
19秒前
领导范儿应助高手采纳,获得10
20秒前
积极幻雪完成签到 ,获得积分10
21秒前
万能图书馆应助han采纳,获得10
21秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
2025-2031全球及中国金刚石触媒粉行业研究及十五五规划分析报告 6000
Real World Research, 5th Edition 680
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 660
Superabsorbent Polymers 600
Handbook of Migration, International Relations and Security in Asia 555
Between high and low : a chronology of the early Hellenistic period 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5675369
求助须知:如何正确求助?哪些是违规求助? 4945575
关于积分的说明 15152710
捐赠科研通 4834585
什么是DOI,文献DOI怎么找? 2589541
邀请新用户注册赠送积分活动 1543247
关于科研通互助平台的介绍 1501131