The computational toxicology group here at Instem has had another busy year that has resulted in six publications and book chapters1-6, completion of existing and initiation of new collaborative working groups, as well as significant updates to our computational toxicology solutions.
We have been collaborating on a number of research topics related to the in silico assessment of extractables and leachables (E&L). This work is led by Dr. Candice Johnson at Instem and includes (1) a chemical analysis of a large databases of E&L reported by the ELSIE and PQRI organizations, (2) an evaluation of how sensitization in silico models support E&L assessments, and (3) an analysis of whether in silico approaches could be used as a screen to assess whether a leachable may react with a biomolecule API (such as a protein) resulting in possible safety, efficacy or quality concerns. This work was presented at the E&L Europe conference7 and three manuscripts have been submitted for publication.
This year, we also initiated a new collaborative working group to develop a framework and a protocol to support the recently published addendum to the ICH S1B guideline. This addendum describes six weight of evidence factors that could be used as part of a carcinogenicity assessment to determine whether performing a rat study adds value. Dr. Arianna Bassan, who is coordinating this work, recently presented the project at the American College of Toxicology (ACT) meeting in Colorado.8
Progress is being made on a series of collaborative working groups related to N-nitrosamines, which are being led by Dr. Kevin Cross at Instem. This work has resulted in a new publication around the use of the Ames test2 and a series of deliverables on the Mutamind project, funded by the EMA9. He also chaired a workshop on addressing the global challenge of nitrosamine impurities in pharmaceutical drugs at the 2022 ACT meeting.8 This year we also introduced a new Predict™ service10 supporting carcinogenicity risk assessment of N-nitrosamines.
2022 also saw the completion of a Special Issue of the Journal of Computational Toxicology on the in silico toxicology protocol project, which included eight publications and an editorial authored by Instem.11
Earlier this year, we released a new version of the Leadscope Model Applier that includes some significant developments, including a new read-across tool. This application provides access to over 200,000 chemicals and 600,000 toxicology studies through an easy-to-use interface and is aligned with regulatory expectations. A new SaaS (Software as a Service) option for the Leadscope technology was also released. In addition, we introduced a series of new and updated expert alerts and QSAR models to assess a complete battery of acute toxicity endpoints12, updates to the bioactivation models to support the assessment of drug-drug interactions, version 9 of the expert alert for bacterial mutagenicity, as well as new endocrine activity QSAR models. Furthermore, through Instem’s Research Collaboration Agreement with the US FDA, we have updated the abuse liability assessments with a new QSAR model predicting blood-brain barrier penetration,1 as well as updated the cardiotoxicity models13.
We would like to thank all our collaborators, customers, partners, and colleagues for all their help and support over the last year and look forward to continuing our work together to further the acceptance and use of in silico approaches and support the 3Rs.
We all at Instem wish you a Happy Holidays!
Please get in touch with me (Glenn Myatt; email@example.com) if you are interested in discussing in silico approaches or any of the collaborative working groups.
- Faramarzi, S. et al., (2022) Development of QSAR models to predict blood-brain barrier permeability, Front. Pharmacol. https://doi.org/10.3389/fphar.2022.1040838
- Trejo-Martin, A. et al., (2022) Use of the Bacterial Reverse Mutation Assay to Predict Carcinogenicity of N-Nitrosamines, Regulatory Toxicology and Pharmacology, 105247. https://doi.org/10.1016/j.yrtph.2022.105247
- Zwickl, C. et al., (2022) Principles and Procedures for Assessment of Acute Toxicity Incorporating In Silico Methods, Computational Toxicology, 100237. https://doi.org/10.1016/j.comtox.2022.100237
- Crofton, K. et al (2022) Current status and future directions for a neurotoxicity hazard assessment framework that integrates in silico approaches, Computational Toxicology, 22, 100223. https://doi.org/10.1016/j.comtox.2022.100223