Predictive Drug Release Modeling Across Dissolution Apparatuses I and II using Computational Fluid Dynamics

Abstract

A modeling process is developed and validated with which active pharmaceutical ingredient (API) release is predicted across the United States Pharmacopeia (USP) dissolution apparatuses I and II based on limited experimental dissolution data (at minimum two dissolution profiles at different apparatus settings). The process accounts for formulation-specific drug release behavior and hydrodynamics in the apparatuses over the range of typical agitation rates and medium volumes. This modeling process involves measurement of experimental mass transfer coefficients via a conventional mass balance and the relationship of said mass transfer coefficients to hydrodynamics and apparatus setting via computational fluid dynamics (CFD). A novel 1-D model is hence established, which provided calibration data for a particular formulation, can model mass transfer coefficients and their corresponding drug release at apparatus configurations of interest. Based on validation against experimental data produced from five erosion-based formulations over a range of apparatus configurations, accuracy within 8 %LA (labelled amount of API) and an average root mean square deviation of 3 %LA is achieved. With this predictive capability, minimizing the number of dissolution experiments and the amount of chemical materials needed during method development appears feasible.