Application of in silico approaches to predicting drug-drug interactions

In an environment driven to find the next blockbuster drug, failure years i nto a project should not be an option. Recent studies have shown that poor absorption, distribution, metabolism, and excretion (ADME), and the related properties of toxicity and pharmacokinetics are responsible for a large pr oportion of failures. One way to understand and potentially predict molecul es likely to be successful in humans as drugs from an ADME point of view is to use simulations. Such simulations may include simple rule-based approac hes, structure-activity relationships, three-dimensional quantitative struc ture-activity relationships (3D-QSAR), and pharmacophores, All of these rep resent useful tools in understanding metabolism by the cytochromes P450, pr edicting drag-drug interactions (DDIs), and other pharmacokinetic parameter s. The present paper briefly reviews the application of some computational tools applied to predicting DDIs and will provide the reader with an idea o f their utility. (C) 2001 Elsevier Science Inc. All rights reserved.