Literature DB >> 30562600

Principles and procedures for handling out-of-domain and indeterminate results as part of ICH M7 recommended (Q)SAR analyses.

Alexander Amberg1, Roxanne V Andaya2, Lennart T Anger1, Chris Barber3, Lisa Beilke4, Joel Bercu5, Dave Bower6, Alessandro Brigo7, Zoryanna Cammerer8, Kevin P Cross6, Laura Custer9, Krista Dobo10, Helga Gerets11, Véronique Gervais12, Susanne Glowienke13, Stephen Gomez14, Jacky Van Gompel15, James Harvey16, Catrin Hasselgren2, Masamitsu Honma17, Candice Johnson6, Robert Jolly18, Raymond Kemper19, Michelle Kenyon10, Naomi Kruhlak20, Penny Leavitt9, Scott Miller6, Wolfgang Muster7, Russell Naven21, John Nicolette22, Alexis Parenty13, Mark Powley23, Donald P Quigley6, M Vijayaraj Reddy23, Jennifer C Sasaki2, Lidiya Stavitskaya20, Andrew Teasdale24, Alejandra Trejo-Martin5, Sandy Weiner8, Dennie S Welch22, Angela White16, Joerg Wichard25, David Woolley26, Glenn J Myatt27.   

Abstract

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.
Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Substances:

Year:  2018        PMID: 30562600     DOI: 10.1016/j.yrtph.2018.12.007

Source DB:  PubMed          Journal:  Regul Toxicol Pharmacol        ISSN: 0273-2300            Impact factor:   3.271


  6 in total

1.  Implementation of in silico toxicology protocols within a visual and interactive hazard assessment platform.

Authors:  Glenn J Myatt; Arianna Bassan; Dave Bower; Candice Johnson; Scott Miller; Manuela Pavan; Kevin P Cross
Journal:  Comput Toxicol       Date:  2021-10-28

2.  Use of In Silico Methods for Regulatory Toxicological Assessment of Pharmaceutical Impurities.

Authors:  Simona Kovarich; Claudia Ileana Cappelli
Journal:  Methods Mol Biol       Date:  2022

Review 3.  In silico toxicology: From structure-activity relationships towards deep learning and adverse outcome pathways.

Authors:  Jennifer Hemmerich; Gerhard F Ecker
Journal:  Wiley Interdiscip Rev Comput Mol Sci       Date:  2020-03-31

4.  Transitioning to composite bacterial mutagenicity models in ICH M7 (Q)SAR analyses.

Authors:  Curran Landry; Marlene T Kim; Naomi L Kruhlak; Kevin P Cross; Roustem Saiakhov; Suman Chakravarti; Lidiya Stavitskaya
Journal:  Regul Toxicol Pharmacol       Date:  2019-10-03       Impact factor: 3.271

5.  A cross-industry collaboration to assess if acute oral toxicity (Q)SAR models are fit-for-purpose for GHS classification and labelling.

Authors:  Joel Bercu; Melisa J Masuda-Herrera; Alejandra Trejo-Martin; Catrin Hasselgren; Jean Lord; Jessica Graham; Matthew Schmitz; Lawrence Milchak; Colin Owens; Surya Hari Lal; Richard Marchese Robinson; Sarah Whalley; Phillip Bellion; Anna Vuorinen; Kamila Gromek; William A Hawkins; Iris van de Gevel; Kathleen Vriens; Raymond Kemper; Russell Naven; Pierre Ferrer; Glenn J Myatt
Journal:  Regul Toxicol Pharmacol       Date:  2020-12-17       Impact factor: 3.271

6.  Management of pharmaceutical ICH M7 (Q)SAR predictions - The impact of model updates.

Authors:  Catrin Hasselgren; Joel Bercu; Alex Cayley; Kevin Cross; Susanne Glowienke; Naomi Kruhlak; Wolfgang Muster; John Nicolette; M Vijayaraj Reddy; Roustem Saiakhov; Krista Dobo
Journal:  Regul Toxicol Pharmacol       Date:  2020-10-13       Impact factor: 3.271

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.