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Publications
  • Publisher:
    Elsevier
  • Publication Date:
    DEC 2018
  • Reference:
    Regulatory Toxicology and Pharmacology: Volume 102, March 2019, Pages 53-64
  • DOI:
    10.1016/j.yrtph.2018.12.007
  • PMID:
  • Publication Type:
    Paper
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Principles and procedures for handling out-of-domain and indeterminate results as part of ICH M7 recommended (Q)SAR analyses

Amberg A; Andaya RV; Anger LT; Barber CG; Beilke L; Bercu J; Bower D; Brigo A; Cammerer Z; Cross K; Custer LL; Dobo KL; Gerets H; Gervais V; Glowienke S; Gomez S; Van Gompel J; Harvey JS; Hasselgren C; Honma M; Johnson C; Jolly R; Kemper R; Kenyon MO; Kruhlak NL; Leavitt P; Miller S; Muster W; Naven RT; Nicolette J; Parenty A; Powley MW; Quigley DP; Reddy MV; Sasaki JC; Stavitskaya L; Teasdale A; Trejo-Martin A; Weiner S; Welch D; White A; Wichard J; Myatt G; Woolley D;

The International Council for Harmonization (ICH) M7 guideline describes a hazard assessment process for impurities that have the potential to be present in a drug substance or drug product. In the absence of adequate experimental bacterial mutagenicity data, (Q)SAR analysis may be used as a test to predict impurities’ DNA reactive (mutagenic) potential. However, in certain situations, (Q)SAR software is unable to generate a positive or negative prediction either because of conflicting information or because the impurity is outside the applicability domain of the model. Such results present challenges in generating an overall mutagenicity prediction and highlight the importance of performing a thorough expert review. The following paper reviews pharmaceutical and regulatory experiences handling such situations. The paper also presents an analysis of proprietary data to help understand the likelihood of misclassifying a mutagenic impurity as non-mutagenic based on different combinations of (Q)SAR results. This information may be taken into consideration when supporting the (Q)SAR results with an expert review, especially when out-of-domain results are generated during a (Q)SAR evaluation.

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