About 6 years ago, the International Conference on Harmonization (ICH) published the M7 guideline “Assessment and Control of DNA reactive (mutagenic) Impurities in Pharmaceuticals to limit Potential Carcinogenic Risk”.[1] This was a landmark moment for computational toxicology, as it was the first time such methods were recognized by the ICH as a regulatory test.

An implementation period followed the guideline’s publication in which pharmaceutical companies used computational assessments of impurities in their submissions to regulatory authorities. During this period, many questions on how such an assessment should be performed and documented were raised by the stakeholders. And after a series of discussions, we decided to form a consortium to address these issues through the development of a protocol outlining how computational toxicology assessments aligned with ICH M7 should be performed. In 2016 this protocol was published “Principles and procedures for implementation of ICH M7 recommended (Q)SAR analyses” [2] and we were encouraged to see how well received the paper was. It is consistently in the most downloaded articles in Regulatory Toxicology and Pharmacology and is often cited in publications and presentations by regulators and industry scientists. A follow-on paper was published in 2019 to address issues related to handling inconclusive results “Principles and procedures for handling out-of-domain and indeterminate results as part of ICH M7 recommended (Q)SAR analyses”. [3]

Based on the success of this work, we began to wonder – could we repeat this experience for other toxicology endpoints?  This would reduce the burden on industry and regulators to justify their use, as well as ensuring in silico assessments are performed in a consistent and reproducible manner to support good in silico practices.

Propelled by an NIH grant and enthusiasm from a wider consortium of over 60 members, we began to develop a framework for such protocols which was published in 2018 “In silico toxicology protocols”. [4] Individual working groups focusing on the development of the endpoints-specific protocols were established and in 2019, the “Genetic toxicology in silico protocol” [5] was published, followed by the “Skin sensitization in silico protocol” [6] in 2020.

Work continues on the development of other protocols and supporting position papers. It is clear that for endpoints, such as skin sensitization, where there are generally accepted Adverse Outcome Pathways (AOPs), Integrated Approaches to Testing and Assessment (IATAs), Defined Approaches (DAs), etc., that the process of putting together an accepted protocol is more straightforward than other areas, such as carcinogenicity. As such, position papers reflecting the current state-of-the-art, as well as gaps in our current knowledge, are important steps towards in silico protocols for complex toxicological endpoints.

This year also marked another important landmark in the evolution of this project with the complete implementation of the published protocols within Leadscope’s products. The solution provides access to computation methodologies and toxicity databases outlined in the protocols which are incorporated within a visual decision framework to support an inspection of the results, along with the ability to perform an expert review and document the entire assessment process.

We are excited with the progress to date and the momentum of this project to support the more widespread application of in silico methods through adoption of good in silico practices.

Please get in touch if you’d like to collaborate on this project.

References

[1] ICH M7, 2017 (R1) (2017) Assessment and control of DNA reactive (mutagenic) impurities in pharmaceuticals to limit potential carcinogenic risk. https://database.ich.org/sites/default/files/M7_R1_Guideline.pdf

[2] Amberg, A., Beilke, L., Bercu, J., et al. (2016) Principles and procedures for implementation of ICH M7 recommended (Q)SAR analyses. Regul. Toxicol. Pharmacol. 77, 13–24. doi:10.1016//j.yrtph.2016.02.004

Open access: https://doi.org/10.1016/j.yrtph.2016.02.004

[3] Amberg, A., Andaya, R.V., Anger, L.T., 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. 10.1016/j.yrtph.2018.12.007

Open access: https://doi.org/10.1016/j.yrtph.2018.12.007

[4] Myatt, G.J., Ahlberg, E., Akahori, Y., et al. (2018) In Silico Toxicology Protocols. Regul. Toxicol. Pharmacol. 98, 1-17. doi:10.1016/j.yrtph.2018.04.014

Open access: https://doi.org/10.1016/j.yrtph.2018.04.014

[5] Hasselgren, C., Ahlberg, E., Akahori, Y., et al. (2019) Genetic toxicology in silico protocol. Regul. Toxicol. Pharmacol.  107, 104403. doi:10.1016/j.yrtph.2019.104403 

Open access: https://doi.org/10.1016/j.yrtph.2019.104403

[6] Johnson, C., Ahlberg, E., Anger, L.T., et al. (2020) Skin sensitization in silico protocol. Regul. Toxicol. Pharmacol.  116, October 2020, 104688. doi: 10.1016/j.yrtph.2020.104688 

Open access: https://doi.org/10.1016/j.yrtph.2020.104688

Published by Glenn Myatt

Glenn J. Myatt is the co-founder and currently head of Leadscope (An Instem company) with over 25 years’ experience in computational chemistry/toxicology. He holds a Bachelor of Science degree in Computing from Oxford Brookes University, a Master of Science degree in Artificial Intelligence from Heriot-Watt University and a Ph.D. in Chemoinformatics from the University of Leeds. He has published 27 papers, 6 book chapters and three books.