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  • Publisher:
    Lhasa Limited
  • Publication Date:
    Mar 2016
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  • Publication Type:
    Poster
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  • Endpoint:
    Mutagenicity
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Improvements to in silico mutagenicity predictivity of aromatic amines with access to proprietary data

pdf fileCanipa S; Macmillan D; Williams RV; Leavitt P; Mack M; Custer LL;

Aromatic amines, widely used in the synthesis of pharmaceuticals, are often found to have mutagenic activity, but accurate prediction of this mutagenic activity has proven difficult. Mutagenicity is normally attributed to the formation of a reactive nitrenium ion - although this reactivity can be influenced by a number of factors.

Access to proprietary data is important for robust in silico predictive models, as models built predominantly on public data sources tend to lack comprehensive coverage in  proprietary pharmaceutical chemical space. Data sharing has become more common, with initiatives such as the Consortium for the Investigation of Genotoxicity of Aromatic Amines (CIGAA)5 in progress. Currently, around 25% of the mutagenicity alerts in Derek Nexus contain anonymised proprietary data; however, there are still gaps in the chemical space covered. By using wide-ranging sources of proprietary data, it is possible to fill these gaps and improve predictivity. 

Poster presented by Donna Macmillan at the 55th SOT, New Orleans, USA; 14th March 2016

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