What is it about?
A review on computational approaches for predicting drug-drug interactions with cytochrome P450s and transporters. We summarize a large body work over the last decade or so. We describe pharmacophore, machine learning, protein-based modeling, hybrid approaches, informatics driven approaches, physiological based pharmacokinetics modeling.
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Why is it important?
We describe common computational approaches, and some of the models that have been built with various machine learning approaches. We also mention the prediction of interactions with Traditional Chinese Medicines. Several tables describe web servers for predicting drug-drug interactions
Perspectives
In over a decade the number of publications describing computational prediction of drug drug interactions has been quite extensive. We suggest there are still gaps where the knowledge is pretty limited and the accessibility of some models is limited.
Dr Sean Ekins
Collaborations in Chemistry
Read the Original
This page is a summary of: In silico methods for predicting drug–drug interactions with cytochrome P-450s, transporters and beyond, Advanced Drug Delivery Reviews, June 2015, Elsevier,
DOI: 10.1016/j.addr.2015.03.006.
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Contributors
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