Over 6 years ago, the ICH M7 pharmaceutical impurities guideline1 was in its implementation phase, and we were approached to consider writing a cross-industry publication to outline a protocol for performing a (Q)SAR assessment aligned with the guideline. A collaborative working group was established and work began to create this publication. The paper was published in 2016 and outlined considerations for incorporating experimental data on the impurities, rules and principles for performing a (Q)SAR analysis including expert review considerations, recommendations on formats to document the results along with case studies.2

In 2019, it was followed up with a paper outlining how to support indeterminate and out-of-domain (Q)SAR results that included case studies and expert review approaches.3 The paper also outlined an analysis that documented the risk of missing a mutagenic impurity based on the differing results from the two (Q)SAR methodologies.

Both papers are open access and have been widely used and cited, with 77 combined citations including the ICH M7 Q&A4. The principles and procedures have also been incorporated into software applications. For example, the Leadscope model applier includes an ICH M7 protocol implementation that streamlines the application of ICH M7 aligned analyses based on these publications, including tools to guide an expert review.5,6 Instem also uses these publications to support its Predict™ computational toxicology services.7

The development of these papers also helped a series of follow-on activities, including the development of an in silico toxicology protocol framework8 as well as other applications that incorporate similar principles, such as the hazard assessment of extractables and leachables.

If you would like to discuss any of these papers or projects, please get in touch (Glenn Myatt; glenn.myatt@instem.com).

References

  1. ICH, 2017. ICH guideline M7 (R1). Assessment and control of DNA reactive (mutagenic) impurities in pharmaceuticals to limit potential carcinogenic risk (No. EMA/CHMP/ICH/83812/2013), ICH Harmonised Guideline. European Medicines Agency. https://database.ich.org/sites/default/files/M7_R1_Guideline.pdf
  2. Amberg, A., et al., 2016. Principles and procedures for implementation of ICH M7 recommended (Q)SAR analyses. Regul. Toxicol. Pharmacol. 77, 13–24. https://doi.org/10.1016/j.yrtph.2016.02.004
  3. A. Amberg et al., 2019 Principles and procedures for handling out-of-domain and indeterminate results as part of ICH M7 recommended (Q)SAR analyses, Regul. Toxicol. Pharmacol. 102, 53–64. https://doi.org/10.1016/j.yrtph.2018.12.007.
  4. ICH M7 Guideline: Assessment and control of DNA reactive (mutagenic) impurities in pharmaceticals to limit potential carcinogenic risk. Questions and Answers. https://www.ich.org/page/multidisciplinary-guidelines#7-3
  5. https://www.instem.com/solutions/insilico/computational-toxicology.php
  6. Myatt, G.J., Bassan, A., Bower, D., Johnson, C., Miller, S., Pavan, M., Cross, K.P., 2022. Implementation of in silico toxicology protocols within a visual and interactive hazard assessment platform. Comput. Toxicol. 21, 100201. https://doi.org/10.1016/j.comtox.2021.100201
  7. https://www.instem.com/solutions/insilico/predict.php
  8. Myatt, G.J., et al., 2018. In silico toxicology protocols. Regul. Toxicol. Pharmacol. 96, 1–17. https://doi.org/10.1016/j.yrtph.2018.04.014

Published by Glenn Myatt

Glenn J. Myatt is the co-founder of Leadscope and currently Vice President, Informatics of Instem with over 25 years’ experience in computational chemistry/toxicology. He holds a Bachelor of Science degree in Computing, a Master of Science degree in Artificial Intelligence and a Ph.D. in Chemoinformatics. He has published 34 papers, 10 book chapters and three books.