Xenobiotica · 2007 · 120 citations · 125 references
PharmacyPharmacokineticsPharmacologyDrug InteractionsPharmacodynamicsPharmacokinetic ModelingDrug-drug InteractionsMetabolism InteractionsMetabolism ModelingPharmacokinetic Drug InteractionsPharmacokinetic SimulationPhysiologically Based Pharmacokinetic ModelingCytochrome P450 Interaction ModelingCytochrome P450 ModelingDrug-drug Interaction SimulationMechanism-based InhibitionMetabolic Interaction ModelingPharmacokinetic Interaction ModelingPhysiological-based Pharmacokinetic ModelingPrediction
The study compared three methods for predicting the magnitude of CYP inhibitor–driven drug–drug interactions. The methods compared were the simple “[I]/K(i)” approach, the more detailed Mechanistic‑Static Model (MSM) incorporating enzyme fraction and intestinal availability, and the Mechanistic‑Dynamic Model (MDM) using PBPK‑based time‑variant inhibitor concentrations. The MDM outperformed the other methods, correctly predicting ≥2‑fold interactions in 80 % of trials and estimating mean AUC changes within twofold of observed values in 64 % of cases, and also enabled automated prediction of parallel pathway inhibition and dosing simulations.
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.
125
K. Sandy Pang, Malcolm Rowland · Journal of Pharmacokinetics and Biopharmaceutics · 1977 · 798 citations
Thorir D. Bjornsson, John T. Callaghan, Heidi J. Einolf et al. · Drug Metabolism and Disposition · 2003 · 784 citations