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.
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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.
Perspectives
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.
Dr Sean Ekins
Collaborations in Chemistry
Read the Original
This page is a summary of: Opportunities and challenges using artificial intelligence in ADME/Tox, Nature Materials, April 2019, Springer Science + Business Media,
DOI: 10.1038/s41563-019-0332-5.
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