What is it about?
Making computational models accessible, especially ADME/Tox models, is an area I have been focused on for about 6 years. We now have the means to put models in the hands of scientists. Using a few small datasets from collaborations and some larger published transporter datasets we demonstrate Bayesian models can be build and implemented in mobile apps.
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Why is it important?
Getting scientists to share or even use computational models is a challenge. We achieve this using open source fingerprints and algorithms and a free mobile app (MMDS). We show how models can be built and implemented. We believe its the first time such an effort has been attempted. Its immediately useful to scientists in resource constrained areas - perhaps they only have an iPhone or iPad.
Perspectives
This is but the latest attempt by us to show how approaches that were previously limited to the desktop, namely machine learning and ADME/Tox prediction, can now be done on mobile devices.
Dr Sean Ekins
Collaborations in Chemistry
Read the Original
This page is a summary of: Making Transporter Models for Drug–Drug Interaction Prediction Mobile, Drug Metabolism and Disposition, July 2015, American Society for Pharmacology & Experimental Therapeutics (ASPET),
DOI: 10.1124/dmd.115.064956.
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