Simulation of Metabolic Drug-Drug Interactions Perpetrated by Fluvoxamine Using Hybridized Two-Compartment Hepatic Drug-Pool-Based Tube Modeling and Estimation of In Vivo Inhibition Constants

Abstract

Co-administration of fluvoxamine (FLV) (perpetrator) and ramelteon (victim, high-clearance CYP1A2 substrate) reportedly showed a 130-fold increase in the area under blood-ramelteon-levels curve (AUCR), which is unpredictable by any method assuming the traditional well-stirred hepatic extraction (Eh ) model. Thus, in order to predict this drug interaction (DDI), a mathematical method that allows simulation of dynamic changes in blood victim levels in response to metabolic inhibition by a perpetrator, without the use of any specialized tools, was derived using hybridized two-compartment hepatic drug-pool-based tube modeling. Using this method, the ramelteon-victimized DDI could be simulated in comparison with other victim DDIs, assuming a consistent FLV dosing regimen. Despite large differences in AUCRs, CYP1A2 or CYP2C19 substrate-victimized DDIs resulted in equivalent inhibition constants (Ki , around 3 nM) and net enzymatic inhibitory activities calculated by eliminating hepatic availability increases for victims. Thus, the unusually large ramelteon DDI could be attributed to the Eh of ramelteon itself. This DDI risk could also be accurately predicted from Ki s estimated in the other CYP1A2 or CYP2C19-substrate interactions. Meanwhile, dynamic changes in blood perpetrator levels were demonstrated to have a small effect on DDI, thus suggesting the usefulness of a tube-based static method for DDI prediction.

Keywords: CYP1A2; CYP2C19; compartment model; drug interactions; fluvoxamine; hepatic clearance; parallel tube model; pharmacokinetics; prediction; simulation.