Simultaneous versus sequential pharmacokinetic-pharmacodynamic population analysis using an iterative two-stage Bayesian technique

Abstract

A method for simultaneous pharmacokinetic-pharmacodynamic (PK-PD) population analysis using an Iterative Two-Stage Bayesian (ITSB) algorithm was developed. The method was evaluated using clinical data and Monte Carlo simulations. Data from a clinical study with rocuronium in nine anesthetized patients and data generated by Monte Carlo simulation using a similar study design were analysed by sequential PK-PD analysis, PD analysis with nonparametric PK data and simultaneous PK-PD analysis. Both PK and PD data sets were 'rich' with respect to the number of measurements per individual. The accuracy and precision of the estimated population parameters were evaluated by comparing their mean error (ME) and root mean squared error (RMSE), respectively. The influence of PD model misspecification on the results was also investigated. The simultaneous PK-PD analysis resulted in slightly more precise population parameter estimates than the sequential PK-PD analysis and the nonparametric PK method. In the presence of PD model misspecification, however, simultaneous analysis resulted in poor PK parameter estimates, while sequential PK-PD analysis performed well. In conclusion, ITSB is a valuable technique for PK-PD population analysis of rich data sets. The sequential PK-PD method is better suited for the analysis of rich data than the simultaneous analysis.