Predicting In Vivo Target Occupancy (TO) Profiles via Physiologically Based Pharmacokinetic–TO Modeling of Warfarin Pharmacokinetics in Blood: Importance of Low Dose Data and Prediction of Stereoselective Target Interactions

Abstract

ordinary differential equation; K p , the tissue-to-blood partitioning coefficients; K d , the equilibrium dissociation constant; k a , the absorption rate constant; k on , the association rate constant; k off , the dissociation rate constant; CYP, cytochrome P450; PS, the permeability surface product; V d , the volume of distribution; CL, clearance; CL int,all , the overall intrinsic clearance; X TotalR , the total amount of the receptor; V max , the maximum rate in the Michaelis-Menten equation; CGNM, the Cluster Gauss-Newton Method; SSR, the sum of squared residuals This article has not been copyedited and formatted. The final version may differ from this version.

A physiologically‐based pharmacokinetic/pharmacodynamic modeling approach for drug–drug‐gene interaction evaluation of S‐warfarin with fluconazole

“…PBPK modeling of warfarin has previously been applied to investigate specific scenarios, such as studying bioequivalence, 57 determining the role of OAT2, 35 predicting in vivo target occupancy, 38 and DDI. 59,66,69 Two studies of PBPK/PD modeling are applied to dose management when warfarin and sorafenib or nirmatrelvir/ ritonavir are administered in combination.…”

“…As early as 1994, Professor Levy proposed the TMDD for warfarin and subsequently simulated blood concentration profiles in rats and humans using the PBPK model 36,58 . Two recently published PBPK models for warfarin consider the effect of TMDD on warfarin, and both improve the model compared to models that do not incorporate TMDD 38,59 . In this study, the model was greatly improved by adding the TMDD process.…”

“…OAT2‐mediated drug transport from the interstitial space to the intracellular in the liver is described using Michaelis–Menten equation too, the K m extracted from literature 35 . VKORC1 protein was added for binding to S‐warfarin, and the dissociation rate constant was obtained from literature 38 . In the modeling, the turnover number ( k cat ) for all enzymes metabolism, maximum rate of reaction for OAT2, and dissociation constant for TMDD were identified in the CYP2C9*1/*1 population.…”

“…35 VKORC1 protein was added for binding to Swarfarin, and the dissociation rate constant was obtained from literature. 38 In the modeling, the turnover number (k cat ) for all enzymes metabolism, maximum rate of reaction for OAT2, and dissociation constant for TMDD were identified in the CYP2C9*1/*1 population. Next, only the k cat values of the CYP2C9 and CYP3A4 enzymes were altered in different genotype populations.…”

Cluster Gauss‐Newton method for a quick approximation of profile likelihood: With application to physiologically‐based pharmacokinetic models

“…In this way, the user can discuss and draw a conclusion about the simulation study while considering multiple possible simulation results that originate from the fact that some parameters are not identifiable. For example, recently, Lee et al 14 have shown that the despite that not all model parameters can…”