DEVELOPMENT AND INTERNAL VALIDATION OF AN IN-VITRO IN-VIVO CORRELATION FOR A HYDROPHILIC METOPROLOL TARTRATE EXTENDED-RELEASE TABLET FORMULATION

Citation
Nd. Eddington et al., DEVELOPMENT AND INTERNAL VALIDATION OF AN IN-VITRO IN-VIVO CORRELATION FOR A HYDROPHILIC METOPROLOL TARTRATE EXTENDED-RELEASE TABLET FORMULATION, Pharmaceutical research, 15(3), 1998, pp. 466-473
Citations number
16
Categorie Soggetti
Pharmacology & Pharmacy
Journal title
ISSN journal
07248741
Volume
15
Issue
3
Year of publication
1998
Pages
466 - 473
Database
ISI
SICI code
0724-8741(1998)15:3<466:DAIVOA>2.0.ZU;2-B
Abstract
Purpose. To develop and validate internally an in vitro-in vivo correl ation (IVIVC) for a hydrophilic matrix extended release metoprolol tab let. Methods. In vitro dissolution of the metoprolol tablets was exami ned 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 re ceived three metoprolol formulations (100 mg): slow, moderate, fast re leasing and an oral solution (50 mg). Serial blood samples were collec ted over 48 hours and analyzed by a validated HPLC assay using fluores cence detection. The fl 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. Predic tion errors were estimated for C-max 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. The re was a significant linear relationship between FRD and FRA when usin g either two or three of the formulations. An average percent predicti on error for C-max and AUC for all formulations of less than 10% was f ound for all IVIVC models. Conclusions. The relatively low prediction errors for C-max 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 a ssociated dissolution data to be used as a surrogate for bioavailabili ty studies.