Metabolism-based drug-drug interactions (DDIs) are due mainly to changes in drug metabolizing enzyme (DME) activities, particularly activities of cytochromes P450 (CYPs). Most DDIs result from a co-administered drug acting as a DME inhibitor and causing increased systemic exposure of a second (victim) drug. In vitro predictive approaches are being increasingly applied as tools to predict clinical DDI risk associated with new chemical entities (NCEs). To date, mechanism-based inhibition (MBI) has been reported to be one of the major causes of clinical DDIs resulting from CYP3A4 inhibition. Due to the primary role of CYP3A4 in drug disposition and clinically related DDIs, there is a great need for tools to effectively predict the clinical DDI potential from in vitro mechanism-based CYP3A4 inhibition data. This presentation will give an overview of clinical MBI-based DDIs and describe principles underlying the various kinetic models, uncertainties and sources of bias and error in the in vitro and in vivo determinations (e.g. enzyme-available inhibitor concentration, plasma/microsomal protein binding, and concurrent inhibition and induction), experimental strategies and specific in vitro approaches for predicting the potential of clinical DDIs. The application of these strategies in the early stages of drug development can be cautiously adapted to support decision-making in drug development, to facilitate extrapolating the clinical implications of in vitro data, and to promote informed planning of clinical DDI studies.