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.