(375m) Experimentally Validated Computational Models to Predict the Impact of Humidity on the Flow of Pharmaceutical Mixtures
Moisture-induced flow variability in pharmaceutical mixtures lead to multiple impediments during manufacturing of solid dosage formulations as the processing and storage humidity conditions can bear significant impact on the final product quality. Experimentally validated Discrete Element Method (DEM) based computational models has been developed to predict the effects of humidity on pharmaceutical powder flow by altering the cohesive forces based on granular bond numbers in simple geometries. Statistical formalism (Simplex Centroid Design) has been performed to understand the moisture induced cohesion in binary and tertiary mixtures at 20%, 40% and 60% RH. V-blending was applied to prepare the pharmaceutical blends, and mixing characterization was performed using a Raman PhAT probe. Optimum fill volume was established for the mixing conditions to minimize static charging due to blender wall interactions on the pharmaceutical powders. Statistical analysis predicted and quantified the non-linearity of the moisture-induced cohesion between the pharmaceutical powders within the blends, based on their systematic hopper discharge studies (experiments and simulations). A methodical implementation of these quantification tools were hence performed to validate a design space that enables an approach to the appropriate selection of blend concentrations that achieve minimum mixture flow variability across different humidity conditions.