Assessment of the Kochak-Benet Equation for Hepatic Clearance for the Parallel-Tube Model: Relevance of Classic Clearance Concepts in PK and PBPK

This report reviews concepts related to operation of the classic parallel-tube model (PTM) for hepatic disposition and examines two recent proposals of a newly derived equation to describe hepatic clearance (CL_H). It is demonstrated that the proposed equation is identical to a re-arrangement of an earlier relationship from Pang and Rowland and provides a means of calculation of intrinsic clearance (CL_int,PTM) rather than CL_H as posed. We further demonstrate how classic hepatic clearance models with an assumed CL_int, while subject to numerous limitations, remain highly useful and necessary in both traditional pharmacokinetics (PK) and physiologically based pharmacokinetic (PBPK) modeling.

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

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.

Simulations of Cytochrome P450 3A4-Mediated Drug-Drug Interactions by Simple Two-Compartment Model-Assisted Static Method

In order to predict cytochrome P450 3A4 (CYP3A4)-mediated drug-drug interactions (DDIs), a simple 2-compartment model-assisted, overall inhibition activity (A_i,overall) method was derived based on 2 concepts. One concept was that the increase in blood victim level and fold increase in the area under the blood victim level curve produced by DDI are determined entirely by A_i,overall, the hepatic availability of the victim and fraction of urinary excreted unchanged victim, where A_i,overall is determined by the perpetrator-specific CYP isoform inhibition activities (A_i,CYPs, DDI predictor-1) and victim-specific fractional CYP isoform contributions (f_m,CYPs, predictor-2). The other concept was that a DDI can be bridged to other DDIs, so that any possible DDI produced by a given victim or a given perpetrator can be predicted by using these predictors. The A_i,CYP3A4s of 12 common CYP3A4 inhibitors were able to be determined and shown to be useful for the prediction of CYP3A4-mediated DDIs wherein victims were metabolized by multiple CYP isoforms. Additionally, it was demonstrated that f_m,CYP values with high confidence can be estimated by bridging DDIs produced by the same victim and different perpetrators. This bridging approach will accelerate prediction of DDIs produced by new chemical entities from the existing DDI database.