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

Patel ML; Yeo D; Werner AL; Kranz M; Harvey JS; Giddings A; Naven RT; Wichard J; Walter MW; Muniedas JM; Kenyon MO; Dobo KL; Bringezu F; Whitehead L; Selby M; Reuberson J; Sutter A; Glowienke S; Jolly R; Amberg A; Atienzar F; Gerets H; Swallow S; Fellows M; Spirkl HP; Muster W;


Primary aromatic amines (pAAs) are attractive building blocks in medicinal chemistry programmes yet their potential for mutagenic activity causes real concern owing to the risk of genotoxicity-related drug attrition. In addition, despite the existence of a substantial body of experimental data, the prediction of aromatic amine mutagenicity still poses a significant challenge for in silico tools. Major contributors to this dilemma are the stability and physicochemical properties of a subset of aromatic amines that affords them capricious mutagenic properties in the Ames test. Such inconsistent mutagenic potential is also compounded by the inherent variability with the assay itself and underscores the need for a rigorous approach in executing the experimental protocol. In order to understand the utility of the in silico approach towards the prediction of pAAs mutagenicity and to widen the availability of mutagenicity data, a group of pharmaceutical companies has formed a consortium with the aim of exchanging their in-house data and making them publicly available for the first time. Summary data compiled during the first phase of this effort is disclosed here and its utility in conjunction with in silico prediction is discussed. Conclusions from this analysis highlight the critical role of expert judgement in rationalizing the experimental activity seen in the Ames test with predictions from in silico models. This collaboration demonstrates the value of sharing such data pre-competitively to aid in both the selection of Ames negative building blocks for drug development while simultaneously helping to develop better in silico tools.