Abstract
Abstract In the recent few years, continuous processing has been considered as a promising process alternative to batch processing in pharmaceutical manufacturing. Via a novel population balance model framework, a multi-dimensional multi-component model for a continuous granulation process was developed, describing time evolutions of distributions with respect to granule size, liquid distribution and granule composition. A parametric study was performed to analyze the effects of various process and design parameters, including granulator size and configuration, liquid spray rate and particle velocity, on evolutions and distributions of key granule properties. Simulation results capture experimentally observed sensitivities and trends thus demonstrating the use of a model-based framework for granulation process design, control and optimization to enable QbD in drug product development.
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