A pharma-wide approach to address the genotoxicity prediction of primary aromatic amines

Patel, Mukesh; Kranz, Michael; Munoz-Muriedas, Jordi; Harvey, James S.; Giddings, Amanda; Swallow, Steve; Fellows, Mick D.; Naven, Russell T.; Werner, Anne-Laure; Yeo, David J.; Bringezu, Frank; Wichard, Joerg; Sutter, Andreas; Glowienke, Susanne; Whitehead, Lewis; Selby, Matt; Reuberson, James; Atienzar, Franck; Gerets, Helga; Kenyon, Michelle; Dobo, Krista L.; Walter, Magnus W.; Jolly, Robert A.; Amberg, Alexander; Spirkl, Hans-Peter; Muster, Wolfgang; Gompel, Jacques Van

doi:10.1016/j.comtox.2018.06.002

Cited by 24 publications

(32 citation statements)

References 21 publications

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“…The prediction accuracies of commercial QSAR tools for primary aromatic amines are 59 to 64% for 599 test compounds and can be improved to about 63 to 79% by adding new data sets and revising the rules [ 4 ]. For another 268 test compounds, the reported accuracy ranged from 57 to 73% [ 5 ].…”

Section: Resultsmentioning

confidence: 99%

“…The prediction accuracy of QSAR tools is improved by increasing the number of training sets and modifying algorithms [ 2 , 3 ]. However, the mutagenicity of several structures, such as aromatic amines, is still difficult to predict when using QSAR tools [ 4 , 5 ].…”

Section: Introductionmentioning

confidence: 99%

“…Because aromatic amines are widely used as intermediates in pharmaceutical synthesis and can remain as impurities, their mutagenicity is a serious safety issue [ 4 , 5 ]. In addition, aromatic amines can be formed as metabolites, especially for drugs with amide bonds that may easily break down by enzymatic hydrolysis [ 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, several efforts have been made to improve the prediction accuracy of QSAR tools. One method is to share nonpublic data held by pharmaceutical companies, as existing QSAR tools have been built based on public knowledge [ 4 , 5 ]. Another method is to perform expert reviews.…”

Section: Introductionmentioning

confidence: 99%

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A local QSAR model based on the stability of nitrenium ions to support the ICH M7 expert review on the mutagenicity of primary aromatic amines

Furukawa¹,

Ono²,

Yamada³

et al. 2022

Genes and Environ

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Background Aromatic amines, often used as intermediates for pharmaceutical synthesis, may be mutagenic and therefore pose a challenge as metabolites or impurities in drug development. However, predicting the mutagenicity of aromatic amines using commercially available, quantitative structure–activity relationship (QSAR) tools is difficult and often requires expert review. In this study, we developed a shareable QSAR tool based on nitrenium ion stability. Results The evaluation using in-house aromatic amine intermediates revealed that our model has prediction accuracy of aromatic amine mutagenicity comparable to that of commercial QSAR tools. The effect of changing the number and position of substituents on the mutagenicity of aromatic amines was successfully explained by the change in the nitrenium ion stability. Furthermore, case studies showed that our QSAR tool can support the expert review with quantitative indicators. Conclusions This local QSAR tool will be useful as a quantitative support tool to explain the substituent effects on the mutagenicity of primary aromatic amines. By further refinement through method sharing and standardization, our tool can support the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) M7 expert review with quantitative indicators.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A local QSAR model based on the stability of nitrenium ions to support the ICH M7 expert review on the mutagenicity of primary aromatic amines

Furukawa¹,

Ono²,

Yamada³

et al. 2022

Genes and Environ

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“…The comments accompanying the Derek Nexus prediction suggest compound 1 narrowly misses an exclusion and also highlights the borderline mutagenic activity of multiply substituted aromatic amines and amides, making them a significant challenge to in silico tools [ 21 ]. Derek Nexus described that activity is expected to result from metabolic activation, initially to the amine.…”

Section: Introductionmentioning

confidence: 99%

The importance of expert review to clarify ambiguous situations for (Q)SAR predictions under ICH M7

et al. 2020

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The use of in silico predictions for the assessment of bacterial mutagenicity under the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) M7 guideline is recommended when two complementary (quantitative) structure-activity relationship (Q)SAR models are used. Using two systems may increase the sensitivity and accuracy of predictions but also increases the need to review predictions, particularly in situations where results disagree. During the 4th ICH M7/QSAR Workshop held during the Joint Meeting of the 6th Asian Congress on Environmental Mutagens (ACEM) and the 48th Annual Meeting of the Japanese Environmental Mutagen Society (JEMS) 2019, speakers demonstrated their approaches to expert review using 20 compounds provided ahead of the workshop that were expected to yield ambiguous (Q)SAR results. Dr. Chris Barber presented a selection of the reviews carried out using Derek Nexus and Sarah Nexus provided by Lhasa Limited. On review of these compounds, common situations were recognised and are discussed in this paper along with standardised arguments that may be used for such scenarios in future.

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Evolution of Quantitative Structure–Activity Relationships ((Q)SAR) for Mutagenicity

2021

Mutagenic Impurities

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A pharma-wide approach to address the genotoxicity prediction of primary aromatic amines

Cited by 24 publications

References 21 publications

A local QSAR model based on the stability of nitrenium ions to support the ICH M7 expert review on the mutagenicity of primary aromatic amines

A local QSAR model based on the stability of nitrenium ions to support the ICH M7 expert review on the mutagenicity of primary aromatic amines

The importance of expert review to clarify ambiguous situations for (Q)SAR predictions under ICH M7

Evolution of Quantitative Structure–Activity Relationships ((Q)SAR) for Mutagenicity

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