Last year, we discussed the development of a new solution to support the assessment of abuse liability.1 This included a large database of over 4,000 chemicals from numerous sources including the US Drug Enforcement Agency (DEA) scheduled drugs and structural alerts to profile potential abuse liability.

This assessment has now been extended to include a new QSAR model to predict drug permeability across the blood-brain barrier. This model includes a training set of 921 chemicals with rodent data and was developed by the US FDA (under a Research Collaboration Agreement).

A research article titled “Development of QSAR models to predict blood-brain barrier permeability” has just been published describing how this model was developed and validated.2

Please get in touch if you are interested in discussing this approach to assessing abuse liability (Glenn Myatt; glenn.myatt@instem.com).

References

  1. https://insilicoinsider.blog/2021/08/26/using-in-silico-approaches-to-assess-abuse-liability/
  2. https://www.frontiersin.org/articles/10.3389/fphar.2022.1040838/full

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.