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• W1704689675 endingPage "55" @default.
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• W1704689675 abstract "Abstract In silico methods have multiple roles to play in drug discovery by reducing costs and increasing screening throughput compared to in vitro and in vivo methods, and by providing information to help guide chemical synthesis in producing compounds having desired properties. In terms of drug metabolism, in silico methods can make predictions regarding the net rate of metabolism of a compound, the identity of enzyme isoforms that are likely to metabolise a compound, the concentration dependency of metabolism and the identity of expected metabolites. In terms of drug–drug interactions, models have been described for the inhibition of metabolism of one compound by another, and for the compound–dependent induction of drug–metabolising enzymes. Analogous models have been described for a number of properties of drug–transporting proteins. Physiologically‐based pharmacokinetic (PBPK) models can predict the in vivo consequences of drug–drug interactions observed in in vitro assays or predicted by in silico models. In this chapter we discuss several areas in which in silico modeling can contribute to the quantitative or qualitative understanding and prediction of drug metabolism and drug–drug interactions. We describe a number of the available in silico approaches to these application areas and discuss, in some detail, a number of specific application areas in which these methods have been used. We describe the use of physiologically based modelling to obtain predictions of the extent of drug–drug interactions expected in vivo . We finish with a discussion of some practical aspects of applying in silico methods in drug discovery." @default.
• W1704689675 created "2016-06-24" @default.
• W1704689675 creator A5021669399 @default.
• W1704689675 creator A5057023170 @default.
• W1704689675 creator A5058221215 @default.
• W1704689675 date "2012-10-15" @default.
• W1704689675 modified "2023-10-12" @default.
• W1704689675 title "In SilicoModels of Drug Metabolism and Drug Interactions" @default.
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