Development of the toxicity values database, ToxValDB: A curated resource for experimental and derived human health-relevant toxicity data

IF 3.1 Q2 TOXICOLOGY
Jonathan T. Wall , Risa R. Sayre , Doris Smith , Samuel Winter , Maxwell Groover , Jasmine Hope , Adriana Webb , Katie Paul Friedman , Madison Feshuk , Antony J. Williams , Charles Lowe , Nisha S. Sipes , Jason Lambert , Jennifer H. Olker , Russell S. Thomas , Colleen Elonen , Richard S. Judson , Chelsea A. Weitekamp
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引用次数: 0

Abstract

The Toxicity Values Database, ToxValDB, was developed by the U.S. EPA Center for Computational Toxicology and Exposure as a resource to curate, store, standardize, and make accessible a wide range of human health-relevant toxicity information. The database originated in response to the need for harmonized and computationally accessible toxicology data. The scope and design of the database have evolved over time since its first release in 2016. Herein, the newly redesigned structure and development of ToxValDB v9.6.1 is described. The database is a compilation of three classes of summary-level values for chemical substances: in vivo toxicity study results (e.g., lowest- and no-observed adverse effect level), derived toxicity values (e.g., maximum acceptable oral dose), and media exposure guidelines (e.g., maximum contaminant level for drinking water). The current version of the database (9.6.1) contains 242,149 records covering 41,769 unique chemicals from 36 sources (55 source tables). With all records in a consistent structure normalized to a standardized vocabulary, the chemical and data landscape of ToxValDB v9.6.1 can be evaluated. To illustrate chemical coverage, the available data were mapped to chemical lists of regulatory importance. Further, the distribution of oral administered doses within in vivo toxicity studies was assessed by annotated chemical class. The harmonized in vivo data within ToxValDB have many applications including use in chemical screening and prioritization for human health assessment, modeling predictions, and benchmarking for New Approach Methods (NAMs), as well as to address a diverse range of novel research questions.
开发毒性值数据库ToxValDB:与人类健康有关的实验和衍生毒性数据的精选资源
毒性值数据库(ToxValDB)是由美国环保署计算毒理学和暴露中心开发的,作为一种资源,用于整理、存储、标准化和提供广泛的与人类健康有关的毒性信息。该数据库起源于对协调和计算可访问毒理学数据的需要的响应。自2016年首次发布以来,该数据库的范围和设计随着时间的推移而不断发展。本文描述了ToxValDB v9.6.1新近重新设计的结构和开发。该数据库汇编了三类化学物质的总水平值:体内毒性研究结果(例如,最低和未观察到的不良反应水平)、衍生毒性值(例如,最大可接受口服剂量)和媒介接触指南(例如,饮用水的最大污染物水平)。当前版本的数据库(9.6.1)包含242,149条记录,涵盖来自36个来源(55个源表)的41,769种独特化学品。在将所有记录归一化为标准化词汇表的一致结构中,可以评估ToxValDB v9.6.1的化学和数据环境。为了说明化学品的覆盖范围,可用的数据被映射到具有监管重要性的化学品清单。此外,在体内毒性研究中,口服给药剂量的分布通过注释化学分类进行评估。ToxValDB中统一的体内数据有许多应用,包括用于化学筛选和人类健康评估的优先级,建模预测和新方法(NAMs)的基准测试,以及解决各种各样的新研究问题。
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
Computational Toxicology
Computational Toxicology Computer Science-Computer Science Applications
CiteScore
5.50
自引率
0.00%
发文量
53
审稿时长
56 days
期刊介绍: Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs
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