Genetic toxicology in silico protocol
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In: Regulatory Toxicology and Pharmacology, Vol. 107, No. 104403, 104403, 01.10.2019.
Research output: Journal contributions › Journal articles › Research › peer-review
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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 -