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

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 pro-cess 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 exper-imental 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 appara-tus configurations, accuracy within 8 %LA (labelled amount of API) and an average root mean square devia-tion 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.(c) 2022 American Pharmacists Association. Published by Elsevier Inc. All rights reserved.