Convolution- and Deconvolution-Based Approaches for Prediction of Pharmacokinetic Parameters of Diltiazem Extended-Release Products in Flow-Through Cell Dissolution Tester

Abstract

The present study evaluated the effect of different configuration setups of the Flow-Through Cell (USP IV) dissolution tester in developing in vitro–in vivo correlation (IVIVC). A Biopharmaceutics Classification System (BCS) Class I Diltiazem (DTZ), formulated in extended-release (ER) gel-matrix system, was employed for this purpose. The study also assessed the validity and predictability of IVIVC employing both deconvolution- and convolution-based approaches. In vitro release was conducted in USP IV as open- or closed-loop setups, while the pharmacokinetic (PK) data were obtained from a previous fasted-state cross-over study conducted on 8 healthy male volunteers, after oral administration of ER matrix tablets against market product (Tildiem Retard® 90 mg). PK parameters (Cmax, AUC0-t and AUC0-∞) were predicted, and compared with actual data to establish the strength of correlation models. Results showed that DTZ release from ER products was influenced by operating the FTC in different configuration-setups, where ≥ 75% of labeled DTZ was released after 6 h and 12 h using the open- and closed-loop settings, respectively. Correlation between fraction-dissolved versus fraction-absorbed for both ER products displayed linear relation upon employing FTC open-loop setup. Convolution-based approach was more discriminative in predicting DTZ in vivo PK parameters with a minimal prediction error, compared to deconvolution-based approach. A successful trial to predict DTZ PKs from individual in vitro data performed in USP IV dissolution model was established, employing convolution technique. Basic principle of the convolution approach provides a simple and practical method for developing IVIVC, hence could be utilized for other BCS Class I extended-release drug products.Graphical abstract