We are pleased to announce the publication of a new paper “Principles and Procedures for Assessment of Acute Toxicity Incorporating In Silico Methods”.1 This paper presents the results from a significant cross-industry collaboration to support the application of in silico methods for (1) product research and development, (2) product approval and registration as well as (3) the transport, storage and handling of chemicals.

The paper also complements the recent paper assessing whether (Q)SAR models are fit-for-purpose for classification and labelling.2

The new paper describes:

  • a framework for hazard assessment of acute toxicity using different sources of information including in silico methods alongside in vitro or in vivo experiments
  • the endpoints from in vitro studies commonly used for predicting acute toxicity
  • key pathways and key triggering mechanisms underlying acute toxicity
  • the state-of-the-art in prediction of acute toxicity
  • an expert review using weight-of-evidence considerations
  • diverse and practical use cases using in silico approaches

We wish to thank and congratulate all collaborators on this important project supporting the 3Rs.

Please get in touch if you would like to discuss this paper or get involved with other collaborative working groups (Glenn Myatt; glenn.myatt@instem.com).

Reference

  1. Zwickl, C. et al., Principles and Procedures for Assessment of Acute Toxicity Incorporating In Silico Methods, Computational Toxicology, 100237. https://doi.org/10.1016/j.comtox.2022.100237
  2. Bercu, J. et al., A cross-industry collaboration to assess if acute oral toxicity (Q)SAR models are fit-for-purpose for GHS classification and labelling, Regulatory Toxicology and Pharmacology, 120, 2021, 104843. https://doi.org/10.1016/j.yrtph.2020.104843

Published by Glenn Myatt

Glenn J. Myatt is the co-founder of Leadscope and currently Senior Vice President, In Silico & Translational Science Solutions at Instem with over 30 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 37 papers, 11 book chapters and three books.