Dependence of In Vitro-In Vivo Correlation Analysis Acceptability on Model Selections

Abstract

ABSTRACTThe objectives of this study were to assess the influence of pharmacokinetic and dissolution model selection on the success of in vitro–in vivo correlation (IVIVC) analysis of fast-, medium-, and slow-dissolving metoprolol tartrate immediate-release tablet formulations. Several different compartmental models were fit to the fast formulation plasma data. Three candidate models with the best fits were ranked 1, 2, and 3 and used to predict AUC and Cmax of the medium and slow formulations. Acceptability of each model to predict the medium and slow formulations was determined using ±20% as the limit for acceptable relative prediction error. When the best dissolution models were used, models 1 and 2 each failed to adequately predict Cmax for slow formulation (−26.8% error for model 1 and −20.4% error for model 2). However, the less appropriate model 3 adequately predicted Cmaxfor slow formulation (−15.1% error). The selection of the dissolution model also determined the outcome of IVIVC analysis, again with a less appropriate model resulting in successful prediction. When the Weibull function was used to characterize dissolution, model 2 failed to adequately predict Cmax for slow formulation (−20.4% error); however, model 2 adequately predicted Cmax for slow formulation when dissolution was characterized using the poorer fitting first-order model (−14.4% error). These results indicate that the success or failure of external validation of these metoprolol tartrate tablets was dependent on the pharmacokinetic and the dissolution models employed. Considering the role of subjectivity in identifying pharmacokinetic and dissolution models, these findings suggest a need to develop objective criteria to identify models a priori to IVIVC analysis.