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In silico toxicology protocols

2018; Elsevier BV; Volume: 96; Linguagem: Inglês

10.1016/j.yrtph.2018.04.014

1096-0295

Glenn J. Myatt, Ernst Ahlberg, Yumi Akahori, David Allen, Alexander Amberg, Lennart T. Anger, Aynur O. Aptula, Scott S. Auerbach, Lisa Beilke, Phillip Bellion, Romualdo Benigni, Joel P. Bercu, Ewan D. Booth, Dave Bower, Alessandro Brigo, Natalie Burden, Zoryana Cammerer, Mark T.D. Cronin, Kevin P. Cross, Laura Custer, Magdalena Dettwiler, Krista L. Dobo, Kevin A. Ford, Marie Fortin, Samantha Gad-McDonald, Nichola Gellatly, Véronique Gervais, Kyle P. Glover, Susanne Glowienke, Jacky Van Gompel, Steve Gutsell, Barry Hardy, James Harvey, Jedd Hillegass, Masamitsu Honma, Jui-Hua Hsieh, Chia-Wen Hsu, Kathy Hughes, Candice Johnson, Robert A. Jolly, Davey L. Jones, Ray Kemper, Michelle Kenyon, Marlene T. Kim, Naomi L. Kruhlak, Sunil Kulkarni, Klaus Kümmerer, Penny Leavitt, Bernhard Majer, Scott A. Masten, Scott A. Miller, Janet Moser, Moiz Mumtaz, Wolfgang Muster, Louise Neilson, Tudor I. Oprea, Grace Patlewicz, Alexandre Tadeu Paulino, Elena Lo Piparo, Mark W. Powley, Donald P. Quigley, M. Vijayaraj Reddy, Andrea-Nicole Richarz, Patricia Ruiz, Benoı̂t Schilter, Rositsa Serafimova, Wendy Simpson, Lidiya Stavitskaya, Reinhard Stidl, Diana Suarez-Rodriguez, David T. Szabo, Andrew Teasdale, Alejandra Trejo‐Martin, Jean‐Pierre Valentin, Anna Vuorinen, B. Wall, Pete Watts, Angela White, Joerg Wichard, Kristine L. Witt, Adam Woolley, David Woolley, Craig Zwickl, Catrin Hasselgren,

Computational Drug Discovery Methods

The present publication surveys several applications of in silico (i.e., computational) toxicology approaches across different industries and institutions. It highlights the need to develop standardized protocols when conducting toxicity-related predictions. This contribution articulates the information needed for protocols to support in silico predictions for major toxicological endpoints of concern (e.g., genetic toxicity, carcinogenicity, acute toxicity, reproductive toxicity, developmental toxicity) across several industries and regulatory bodies. Such novel in silico toxicology (IST) protocols, when fully developed and implemented, will ensure in silico toxicological assessments are performed and evaluated in a consistent, reproducible, and well-documented manner across industries and regulatory bodies to support wider uptake and acceptance of the approaches. The development of IST protocols is an initiative developed through a collaboration among an international consortium to reflect the state-of-the-art in in silico toxicology for hazard identification and characterization. A general outline for describing the development of such protocols is included and it is based on in silico predictions and/or available experimental data for a defined series of relevant toxicological effects or mechanisms. The publication presents a novel approach for determining the reliability of in silico predictions alongside experimental data. In addition, we discuss how to determine the level of confidence in the assessment based on the relevance and reliability of the information.