TY - JOUR

T1 - Genetic toxicology in silico protocol

AU - Hasselgren, Catrin

AU - Ahlberg, Ernst

AU - Akahori, Yumi

AU - Amberg, Alexander

AU - Anger, Lennart T.

AU - Atienzar, Franck

AU - Auerbach, Scott

AU - Beilke, Lisa

AU - Bellion, Phillip

AU - Benigni, Romualdo

AU - Bercu, Joel

AU - Booth, Ewan D.

AU - Bower, Dave

AU - Brigo, Alessandro

AU - Cammerer, Zoryana

AU - Cronin, Mark T.D.

AU - Crooks, Ian

AU - Cross, Kevin P.

AU - Custer, Laura

AU - Dobo, Krista

AU - Doktorova, Tatyana

AU - Faulkner, David

AU - Ford, Kevin A.

AU - Fortin, Marie C.

AU - Frericks, Markus

AU - Gad-McDonald, Samantha E.

AU - Gellatly, Nichola

AU - Gerets, Helga

AU - Gervais, Véronique

AU - Glowienke, Susanne

AU - Van Gompel, Jacky

AU - Harvey, James S.

AU - Hillegass, Jedd

AU - Honma, Masamitsu

AU - Hsieh, Jui Hua

AU - Hsu, Chia Wen

AU - Barton-Maclaren, Tara S.

AU - Johnson, Candice

AU - Jolly, Robert

AU - Jones, David

AU - Kemper, Ray

AU - Kenyon, Michelle O.

AU - Kruhlak, Naomi L.

AU - Kulkarni, Sunil A.

AU - Kümmerer, Klaus

AU - Leavitt, Penny

AU - Masten, Scott

AU - Miller, Scott

AU - Moudgal, Chandrika

AU - Muster, Wolfgang

AU - Paulino, Alexandre

AU - Lo Piparo, Elena

AU - Powley, Mark

AU - Quigley, Donald P.

AU - Reddy, M. Vijayaray

AU - Richarz, Andrea Nicole

AU - Schilter, Benoit

AU - Snyder, Ronald D.

AU - Stavitskaya, Lidiya

AU - Stidl, Reinhard

AU - Szabo, David T.

AU - Teasdale, Andrew

AU - Tice, Raymond R.

AU - Trejo-Martin, Alejandra

AU - Vuorinen, Anna

AU - Wall, Brian A.

AU - Watts, Pete

AU - White, Angela T.

AU - Wichard, Joerg

AU - Witt, Kristine L.

AU - Woolley, Adam

AU - Woolley, David

AU - Zwickl, Craig

AU - Myatt, Glenn J.

N1 - Publisher Copyright: © 2019 The Authors

PY - 2019/10/1

Y1 - 2019/10/1

N2 - In silico toxicology (IST) approaches to rapidly assess chemical hazard, and usage of such methods is increasing in all applications but especially for regulatory submissions, such as for assessing chemicals under REACH as well as the ICH M7 guideline for drug impurities. There are a number of obstacles to performing an IST assessment, including uncertainty in how such an assessment and associated expert review should be performed or what is fit for purpose, as well as a lack of confidence that the results will be accepted by colleagues, collaborators and regulatory authorities. To address this, a project to develop a series of IST protocols for different hazard endpoints has been initiated and this paper describes the genetic toxicity in silico (GIST) protocol. The protocol outlines a hazard assessment framework including key effects/mechanisms and their relationships to endpoints such as gene mutation and clastogenicity. IST models and data are reviewed that support the assessment of these effects/mechanisms along with defined approaches for combining the information and evaluating the confidence in the assessment. This protocol has been developed through a consortium of toxicologists, computational scientists, and regulatory scientists across several industries to support the implementation and acceptance of in silico approaches.

AB - In silico toxicology (IST) approaches to rapidly assess chemical hazard, and usage of such methods is increasing in all applications but especially for regulatory submissions, such as for assessing chemicals under REACH as well as the ICH M7 guideline for drug impurities. There are a number of obstacles to performing an IST assessment, including uncertainty in how such an assessment and associated expert review should be performed or what is fit for purpose, as well as a lack of confidence that the results will be accepted by colleagues, collaborators and regulatory authorities. To address this, a project to develop a series of IST protocols for different hazard endpoints has been initiated and this paper describes the genetic toxicity in silico (GIST) protocol. The protocol outlines a hazard assessment framework including key effects/mechanisms and their relationships to endpoints such as gene mutation and clastogenicity. IST models and data are reviewed that support the assessment of these effects/mechanisms along with defined approaches for combining the information and evaluating the confidence in the assessment. This protocol has been developed through a consortium of toxicologists, computational scientists, and regulatory scientists across several industries to support the implementation and acceptance of in silico approaches.

KW - (Q)SAR

KW - Computational toxicology protocols

KW - Expert alerts

KW - Expert review

KW - Genetic toxicology

KW - In silico

KW - In silico toxicology

KW - Chemistry

UR - http://www.scopus.com/inward/record.url?scp=85063724475&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/688c11a9-86ad-3cc4-aad3-0ee5a4342d4e/

U2 - 10.1016/j.yrtph.2019.104403

DO - 10.1016/j.yrtph.2019.104403

M3 - Journal articles

C2 - 31195068

AN - SCOPUS:85063724475

VL - 107

JO - Regulatory Toxicology and Pharmacology

JF - Regulatory Toxicology and Pharmacology

SN - 0273-2300

IS - 104403

M1 - 104403

ER -