Streamlining ICH M7 analyses with an implemented protocol

A major focus of our work over the last few years has been on the development and publication of in silico toxicology protocols, discussed in previous blog posts¹. This has resulted in a paper outlining a framework for such protocols²  as well as two published protocols in the areas of genetic toxicology³ and skin sensitization⁴. These protocols have been implemented in the Leadscope computational toxicology software to support a fast, defendable, consistent, and fully documented assessment.

We are continually working on the development of new protocols as part of a series of cross-industry working groups. For example, in silico protocols for skin and eye irritation/corrosion as well as endocrine activity are being generated. In addition, many papers outlining the state-of-the-art in the prediction of different toxicological endpoints, such as liver toxicity, are being submitted for publication as part of a special issue on in silico toxicology protocols in the Journal of Computational Toxicology. These newer publications will provide a springboard for the development of new in silico methods and future protocols.

The ICH M7 guideline⁵ supports the mutagenicity assessment for pharmaceutical impurities and similar approaches are being adopted in many other areas including animal health and pesticide residuals.

Based on the protocol framework, we have now developed an ICH M7 protocol implementation. This pulls together information from the models (statistical QSAR models, expert alerts, cohort-of-concern profilers) and database searches (bacterial mutagenicity, rodent carcinogenicity, acceptable intake limits) which is integrated as part of a documented decision scheme. Figure 1 shows an example of how the new tool summarizes all available information.

In the same manner as the other protocol implementations, it is possible to inspect the underlying decision scheme behind each assessment, perform an expert review (support by a series of guidelines) that may result in modification (such as refuting a (Q)SAR result), as well as documentation of all the results and expert review. Figure 2 shows the decision scheme and expert review guidelines for an individual chemical.

Please get in touch with me (Glenn Myatt; glenn.myatt@instem.com) if you are interested in discussing this approach to mutagenicity assessment.

References

1. Can the burden on industry and regulators be reduced? https://insilicoinsider.blog/2020/09/10/can-the-burden-on-industry-and-regulators-be-reduced/
2. 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
3. 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 
4. 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 
5.  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