Development and evaluation of a physiologically based pharmacokinetic model to predict carvedilol-paroxetine metabolic drug-drug interaction in healthy adults and its extrapolation to virtual chronic heart failure patients for dose optimization

Purpose: The metabolic drug-drug interactions (mDDIs) are one of the most important challenges faced by the pharmaceutical industry during the drug development stage and are frequently associated with labeling restrictions and withdrawal of drugs. The capacity of physiologically based pharmacokinetic (PBPK) models to absorb and upgrade with the newly available information on drug and population-specific parameters, makes them a preferred choice over the conventional pharmacokinetic models for predicting mDDIs. Method: A PBPK model capable of predicting the stereo-selective disposition of carvedilol after administering paroxetine by incorporating mechanism (time) based inhibition of CYP2D6 and CYP3A4 was developed by using the population-based absorption, distribution, metabolism and elimination (ADME) simulator, Simcyp (R). Results: The model predictions for both carvedilol enantiomers were in close agreement with the observed PK data, as the ratios for observed/predicted PK parameters were within the 2-fold error range. The developed PBPK model was successful in capturing an increase in exposures of R and S-carvedilol, due to the time-based inhibition of CYP2D6 enzyme caused by paroxetine. Conclusion: The developed model can be used for exploring complex clinical scenarios, where multiple drugs are given concurrently, particularly in diseased populations where no clinical trial data is available.

Automated summary

The PBPK model incorporating mechanism-based inhibition predicted the stereo-selective distribution of carvedilol accurately. The model showed close agreement between predicted and observed data, and can be used for exploring complex clinical scenarios.