Information about drug metabolism is an essential component of drug development. Modeling the drug
metabolism requires identification of the involved enzymes, rate and extent of metabolism, the sites of metabolism
etc. There has been continuous attempts in the prediction of metabolism of drugs using artificial intelligence in effort
to reduce the attrition rate of drug candidates entering to preclinical and clinical trials. Currently, there are
number of predictive models available for metabolism using Support vector machines, Artificial neural networks,
Bayesian classifiers etc. There is an urgent need to review their progress so far and address the existing challenges
in prediction of metabolism. In this attempt, we are presenting the currently available literature models and some of
the critical issues regarding prediction of drug metabolism.
Keywords: Artificial intelligence, drug designing, drug metabolism, machine learning, pharmacokinetics, prediction.
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