Prediction of Metabolism of Drugs using Artificial Intelligence: How far have we reached?
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
Document Type: Research Article
Publication date: 01 February 2016
- Current Drug Metabolism aims to cover all the latest and outstanding developments in drug metabolism and disposition. The journal serves as an international forum for the publication of timely reviews in drug metabolism. Current Drug Metabolism is an essential journal for academic, clinical, government and pharmaceutical scientists who wish to be kept informed and up-to-date with the latest and most important developments. The journal covers the following areas:
In vitro systems including CYP-450; enzyme induction and inhibition; drug-drug interactions and enzyme kinetics; pharmacokinetics, toxicokinetics, species scaling and extrapolations; P-glycoprotein and transport carriers; target organ toxicity and interindividual variability; drug metabolism and disposition studies; extrahepatic metabolism; phase I and phase II metabolism; recent developments for the identification of drug metabolites and adducts. - Editorial Board
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