Abstract

This study aimed to demonstrate the added value of integrating prior in vitro data and knowledge-rich physiologically based pharmacokinetic (PBPK) models with pharmacodynamics (PDs) models. Four distinct applications that were developed and tested are presented here. PBPK models were developed for metoprolol using different CYP2D6 genotypes based on in vitro data. Application of the models for prediction of phenotypic differences in the pharmacokinetics (PKs) and PD compared favorably with clinical data, demonstrating that these differences can be predicted prior to the availability of such data from clinical trials. In the second case, PK and PD data for an immediate release formulation of nifedipine together with in vitro dissolution data for a controlled release (CR) formulation were used to predict the PK and PD of the CR. This approach can be useful to pharmaceutical scientists during formulation development. The operational model of agonism was used in the third application to describe the hypnotic effects of triazolam, and this was successfully extrapolated to zolpidem by changing only the drug related parameters from in vitro experiments. This PBPK modeling approach can be useful to developmental scientists who which to compare several drug candidates in the same therapeutic class. Finally, differences in QTc prolongation due to quinidine in Caucasian and Korean females were successfully predicted by the model using free heart concentrations as an input to the PD models. This PBPK linked PD model was used to demonstrate a higher sensitivity to free heart concentrations of quinidine in Caucasian females, thereby providing a mechanistic understanding of a clinical observation. In general, permutations of certain conditions which potentially change PK and hence PD may not be amenable to the conduct of clinical studies but linking PBPK with PD provides an alternative method of investigating the potential impact of PK changes on PD.

Highlights

  • Based pharmacokinetic (PBPK) modeling provides a mechanistic platform for the integration of the concentrationtime profile of the drug with realistic physiological and biological processes in the body

  • Predictions on drug–drug interactions, first in man dosing, optimal clinical study designs, dosage requirements for drugs that are metabolized by polymorphic enzymes and dosage adjustments in disease states are some of the physiologically based pharmacokinetic (PBPK) applications that could potentially be used during the drug development and regulatory submission processes (Chen et al, 2012; Huang and Rowland, 2012; Rostami-Hodjegan, 2012; Sinha et al, 2012; Zhao et al, 2012; Rowland, 2013; Vieira et al, 2014)

  • In comparison with extensive metabolizers (EMs), and ultrarapid metabolizers (UMs), the longer action of metoprolol in poor metabolizers (PMs) is a result of residence of drug in the body, which is caused by the lower clearance of metoprolol in PMs group

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Summary

Introduction

Based pharmacokinetic (PBPK) modeling provides a mechanistic platform for the integration of the concentrationtime profile of the drug with realistic physiological and biological processes in the body. This modeling approach offers an advantage over traditional compartmental modeling approaches since it potentially allows for extrapolation and further investigation into conditions for which pharmacokinetic (PK) studies have not been conducted, thereby informing and accelerating the drug development process. This is especially important when the plasma concentration is not a good surrogate for the concentration at the site of drug action (Rostami-Hodjegan, 2013), as demonstrated in a recent study with rosuvastatin, a cholesterol lowering drug which is a substrate of the OATP1B1 influx transporter

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