Three approaches were compared to predict the actual magnitude of drug interaction (the mean fold-change in the area under the curve (AUC)) of reversible or irreversible (mechanism-based) cytochrome P450 (CYP) inhibitors. These were: (1) the pragmatic use of the '[I]/K(i)' approach; (2) the 'Mechanistic-Static Model' (MSM), which is a more complex extension of the '[I]/K(i)' approach that incorporates f(m,CYP), intestinal availability for CYP3A substrates, and mechanism-based inhibition (MBI); and (3) the 'Mechanistic-Dynamic Model' (MDM) which considers the time-variant change in the concentration of the inhibitor by using physiologically-based pharmacokinetic (PBPK) models (as implemented within the Simcyp(R) Population-Based ADME Simulator). The three approaches ([I]/K(i), MSM, and MDM) predicted a 'correct' drug-drug interaction (DDI) result (interaction: Greater than or equal to twofold; no interaction: Less than twofold) in 74, 87, and 80% of the 100 trials evaluated, respectively. Importantly, for trials with a greater than or equal to twofold change in AUC in the presence of the inhibitor (59 trials), the [I]/K(i), MSM, and MDM approaches predicted the mean AUC change within twofold of actual in 17, 53, and 64% of the trials, respectively. Overall, the MDM approach showed an improvement in the prediction of DDI magnitude compared to the other methods evaluated and was useful in its ability to predict variability in DDI magnitude and pharmacokinetic parameters. Moreover, the MDM model allowed the automated prediction of the inhibition of parallel metabolic pathways and simulations of different dosing regimens.