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Comparative Study
. 1998 Mar;15(3):466-73.
doi: 10.1023/a:1011988601696.

Development and internal validation of an in vitro-in vivo correlation for a hydrophilic metoprolol tartrate extended release tablet formulation

Affiliations
Comparative Study

Development and internal validation of an in vitro-in vivo correlation for a hydrophilic metoprolol tartrate extended release tablet formulation

N D Eddington et al. Pharm Res. 1998 Mar.

Erratum in

  • Pharm Res 1998 Aug;15(8):1320

Abstract

Purpose: To develop and validate internally an in vitro-in vivo correlation (IVIVC) for a hydrophilic matrix extended release metoprolol tablet.

Methods: In vitro dissolution of the metoprolol tablets was examined using the following methods: Apparatus II, pH 1.2 & 6.8 at 50 rpm and Apparatus I, pH 6.8, at 100 and 150 rpm. Seven healthy subjects received three metoprolol formulations (100 mg): slow, moderate, fast releasing and an oral solution (50 mg). Serial blood samples were collected over 48 hours and analyzed by a validated HPLC assay using fluorescence detection. The f2 metric (similarity factor) was used to analyze the dissolution data. Correlation models were developed using pooled fraction dissolved (FRD) and fraction absorbed (FRA) data from various combinations of the formulations. Predicted metoprolol concentrations were obtained by convolution of the in vivo dissolution rates. Prediction errors were estimated for Cmax and AUC to determine the validity of the correlation.

Results: Apparatus I operated at 150 rpm, and pH of 6.8 was found to be the most discriminating dissolution method. There was a significant linear relationship between FRD and FRA when using either two or three of the formulations. An average percent prediction error for Cmax and AUC for all formulations of less than 10% was found for all IVIVC models.

Conclusions: The relatively low prediction errors for Cmax and AUC observed strongly suggest that the metoprolol IVIVC models are valid. The average percent prediction error of less than 10% indicates that the correlation is predictive and allows the associated dissolution data to be used as a surrogate for bioavailability studies.

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