The application of in silico toxicology is constantly increasing as we better understand how such methods can support different applications (such as the assessment of genotoxic impurity, extractables and leachables, chemicals requiring classification and labelling, and so on). Position papers are critical to support this expansion. We have reported in some recent blog posts progress in the development of such publications that outline protocols for using such methods1,2,3, expansion of our knowledge around structure-activity relationships4 as well as publications assessing whether in silico methods are fit-for-purpose5,6.

In the development of such publications, we have learned that it is essential to thoroughly understand the context into which such methods are being applied. In addition, some common themes include the importance of high-quality toxicology databases, using multiple in silico methodologies and access to transparent information to perform an expert review. We are currently working hard on the development of new and updated models to support these, and newer applications based on these best practices.

Since the prediction of mutagenicity, sensitization, irritation/corrosion may be used to support extractables and leachables as well as for classification and labelling, we are finalizing new and updated statistical-based and expert rule-based transparent models to cover these endpoints. Prediction of endocrine activity is another area of focus for us as this supports many important applications.

We are also working on models to support some new applications for in silico approaches. These include new bioactivation alerts to support the FDA guidance for industry on in vitro drug interaction studies7 and a new database and expert alerts to support the assessment of abuse liability.

Please contact me (Glenn Myatt; glenn.myatt@instem.com) if you would like to discuss any of these models or collaborative initiatives.

References

  1. Predicting organ toxicity
  2. Endocrine activity in silico protocol
  3. In silico toxicology consortia: impact and future direction
  4. Instem’s Computational Toxicology and Genetic Toxicology Groups at GTA 2021
  5. New acute toxicity (Q)SAR manuscript
  6. Are (Q)SAR models fit-for-purpose for classification and labelling?
  7. Cross-industry development of structural alerts to support the FDA Guidance on in vitro drug interaction studies

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.