Final model assessment
The superiority/inferiority of the final model was validated using the non-parametric bootstrap method and VPC. The bootstrap method involved repeated random sampling with replacement and modeling of the generated data sets to obtain the PK parameters for each data set. The stability of the model was evaluated by calculating the medians and 95% CIs of the PK parameters and comparing them to the estimated values of the final model. VPC involved the generation of virtual sample data sets through simulation, construction of the 95% prediction intervals for observed and predicted values, and estimation of the 5%, 25%, 50%, 75%, and 95% quantiles of the observed and predicted values. The predictive accuracy of the model was evaluated by comparing the overlap between the observed and predicted values.