In silico methods combined with expert knowledge rule out mutagenic potential of pharmaceutical impurities: An industry survey

Dobo, Krista L.; Greene, Nigel; Fred, Charlotta; Glowienke, Susanne; Harvey, James S.; Hasselgren, Catrin; Jolly, Robert A.; Kenyon, Michelle; Munzner, Jennifer B.; Muster, Wolfgang; Neft, Robin E.; Reddy, M. Vijayaraj; White, Angela; Weiner, Sandy

doi:10.1016/j.yrtph.2012.01.007

Cited by 83 publications

(44 citation statements)

References 19 publications

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“…Eight companies were surveyed for their success rate in prediction of mutagenicity with in silico tools [63]. The Negative Predictive Value (NPV) of the in silico approaches was 94%.…”

Section: Reliability Of (Q)sar Applications For Mutagenicity Predictionmentioning

confidence: 99%

“…The survey clearly illustrated the importance of expert interpretation of in silico predictions. In addition, the survey also suggested that the use of multiple computational models is not a significant factor in the success of the in silico approaches with respect to NPV [63]. A new tool that can help in the (in silico) interpretation of mutagenicity of a chemical is the ToxRead software [64].…”

Section: Reliability Of (Q)sar Applications For Mutagenicity Predictionmentioning

confidence: 99%

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Testing the Mutagenicity Potential of Chemicals

Verheyen¹

2017

J Genet Genome Res

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All information for the proper development, functioning and reproduction of organisms is coded in the sequence of matched base-pairs of DNA. DNA mutations can result in harmful effects and play a role in genetic disorders and cancer. As mutations can arise through exposure to chemical substances, testing needs to be done on substances that humans and animals can be exposed to. This review focuses on the different testing strategies for risk assessment of chemicals for genotoxicity and carcinogenicity. This review is not meant to cover all testing methodologies, but rather to give an overview of the main methodologies that are used in a regulatory context. In silico and in vitro tools are playing an increasingly important role, in order to reduce in vivo animal testing. Especially in silico tools like (Q)SARs are promising as they are non-testing methods and thereby also reduce the costs and time that are needed to perform in vitro assays. (Q)SARs are not sufficiently reliable to be used as stand-alone tools, and should be associated with expert judgment or used in combination with other Weight of Evidence such as in vitro and in vivo data and data derived from other similar molecules (read-across). For some product (sub) categories, testing (in vitro/in vivo) will be unavoidable; however the future may bring reliable approaches for ensuring human safety.

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“…Eight companies were surveyed for their success rate in prediction of mutagenicity with in silico tools [63]. The Negative Predictive Value (NPV) of the in silico approaches was 94%.…”

Section: Reliability Of (Q)sar Applications For Mutagenicity Predictionmentioning

confidence: 99%

Section: Reliability Of (Q)sar Applications For Mutagenicity Predictionmentioning

confidence: 99%

Testing the Mutagenicity Potential of Chemicals

Verheyen¹

2017

J Genet Genome Res

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show abstract

“…nih.gov), ExPub (http://www.expub.com), Potency Database (http://potency.berkeley.edu), Vitic (Lhasa Ltd., http://www.lhasalimited.org) gibi veri tabanlarında bulunmaktadır. 5,7,26 Safsızlıkların genotoksisiteleri ve karsinojeniteleri, yapı-aktivite ilişkisi analizi [structure-activity relationship (SAR)] ve nicel yapı-aktivite ilişkisi [quantitative-SAR (QSAR)] modelleri kullanılarak "in silico" denilen yöntemlerden elde edilen yapısal alarmlar ile değerlendirilebilir. 21 …”

Section: Safsizliklarin Genotoksi̇si̇teleri̇ni̇n Beli̇rlenmesi̇nde Kullanilunclassified

Genotoxic Impurities in Drugs for Human: Review

Palabıyık¹,

Baydar²,

Şahin³

2016

Turkiye Klinikleri J Pharm Sci

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“…Their use in the pharmaceutical field is more related to the R&D of new drugs avoiding potential adverse effects. Furthermore, regulatory criteria have been defined for the use of in silico predictions in drug safety for the genotoxicity evaluation of drug impurities where the presence or absence of specific structural alerts triggers the subsequent management of potential risk posed by the presence of this impurity [39,40]. In this context, new models have been recently proposed to estimate genotoxic or carcinogenic potency in order to estimate safety [40,41] Very good results have been obtained in the evaluation of genotoxic impurities in the industrial sector when in silico data were coupled with expert evaluation [40] achieving a negative predictive value of 99%.…”

Section: Regulatory Context For In Silico Modelsmentioning

confidence: 99%