Late last year we reviewed a collaboration to assess whether acute (Q)SAR models are fit-for-purpose1 to support classification and labeling, since the use of an alternative approach would support the 3Rs.

As part of this exercise, a series of primarily proprietary chemicals with acute toxicity data were run through the different acute (Q)SAR methodologies and the results, both experimental and predicted, were shared with us. This information was then combined from all the companies and performance statistics generated.

The project also took into consideration how an expert review of the information would factor into such assessments and what elements might be considered as part of such a review.

Based on the results from this project, a workflow was proposed that incorporates (Q)SAR assessment.

We are pleased that the open access publication describing this work is now online and can be viewed at: https://doi.org/10.1016/j.yrtph.2020.104843

The paper concludes that such a workflow that includes (Q)SAR models as well as an expert review “… provides a scientifically rational, reasonable and conservative approach to hazard identification”.

We are now working hard on the next generation of these models to support classification and labelling.

If you’d like to discuss this work in more detail, please contact me at gmyatt@leadscope.com.

References

  1. https://insilicoinsider.blog/2020/12/03/are-qsar-models-fit-for-purpose-for-classification-and-labelling/

Published by Glenn Myatt

Glenn J. Myatt is the co-founder of Leadscope and currently Vice President, Informatics of Instem with over 25 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 34 papers, 10 book chapters and three books.