| Literature DB >> 29678766 |
Glenn J Myatt1, Ernst Ahlberg2, Yumi Akahori3, David Allen4, Alexander Amberg5, Lennart T Anger5, Aynur Aptula6, Scott Auerbach7, Lisa Beilke8, Phillip Bellion9, Romualdo Benigni10, Joel Bercu11, Ewan D Booth12, Dave Bower13, Alessandro Brigo14, Natalie Burden15, Zoryana Cammerer16, Mark T D Cronin17, Kevin P Cross13, Laura Custer18, Magdalena Dettwiler19, Krista Dobo20, Kevin A Ford21, Marie C Fortin22, Samantha E Gad-McDonald23, Nichola Gellatly15, Véronique Gervais24, Kyle P Glover25, Susanne Glowienke26, Jacky Van Gompel27, Steve Gutsell6, Barry Hardy28, James S Harvey29, Jedd Hillegass18, Masamitsu Honma30, Jui-Hua Hsieh31, Chia-Wen Hsu32, Kathy Hughes33, Candice Johnson13, Robert Jolly34, David Jones35, Ray Kemper36, Michelle O Kenyon20, Marlene T Kim32, Naomi L Kruhlak32, Sunil A Kulkarni33, Klaus Kümmerer37, Penny Leavitt18, Bernhard Majer38, Scott Masten7, Scott Miller13, Janet Moser39, Moiz Mumtaz40, Wolfgang Muster14, Louise Neilson41, Tudor I Oprea42, Grace Patlewicz43, Alexandre Paulino44, Elena Lo Piparo45, Mark Powley32, Donald P Quigley13, M Vijayaraj Reddy46, Andrea-Nicole Richarz47, Patricia Ruiz40, Benoit Schilter45, Rositsa Serafimova48, Wendy Simpson6, Lidiya Stavitskaya32, Reinhard Stidl38, Diana Suarez-Rodriguez6, David T Szabo49, Andrew Teasdale50, Alejandra Trejo-Martin11, Jean-Pierre Valentin51, Anna Vuorinen9, Brian A Wall52, Pete Watts53, Angela T White29, Joerg Wichard54, Kristine L Witt7, Adam Woolley55, David Woolley55, Craig Zwickl56, Catrin Hasselgren13.
Abstract
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.Entities:
Keywords: Computational toxicology; Expert alert; Expert review; In silico; In silico toxicology; Predictive toxicology; QSAR
Mesh:
Year: 2018 PMID: 29678766 PMCID: PMC6026539 DOI: 10.1016/j.yrtph.2018.04.014
Source DB: PubMed Journal: Regul Toxicol Pharmacol ISSN: 0273-2300 Impact factor: 3.271