Opportunities and challenges using artificial intelligence in ADME/Tox

  • Barun Bhhatarai, W. Patrick Walters, Cornelis E. C. A. Hop, Guido Lanza, Sean Ekins
  • Nature Materials, April 2019, Springer Science + Business Media
  • DOI: 10.1038/s41563-019-0332-5

Is deep learning having any impact on ADME/Tox?

What is it about?

This article is a commentary that followed an AI conference panel last year. Basically everyone chimes in other issues facing ADME/Tox modeling and what if any impact deep learning has had or could have in future on this topic.

Why is it important?

The panel consisted of scientists from Big Pharma and small biotech and presented very different opinions on the subject matter. We were able to go much deeper than we could at the conference.


Dr Sean Ekins
Collaborations in Chemistry

This article was very iterative in how we approached writing it. Kind of like fast prototyping. We were able to write a first draft pretty quickly. We had significant edits that were added from reviewers comments as well. Although all the panel had different opinions it was definitely clear that we came to similar conclusions on deep learning.

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The following have contributed to this page: Dr Sean Ekins