(714g) Experimentally Validated Computational Models to Predict Powder Flow at Different Humidity Conditions

The flow properties of powder are governed by its intrinsic materials properties (cohesion, surface energies, elastic moduli, coefficient of friction and yield stress) and particle properties (size distribution, morphology, porosity and roughness). Environmental variables that affect the powder flow properties include relative humidity, temperature, and electrostatic charging. This large number of variables and their mutual interactions, along with unknown material properties, make it difficult to predict the flow properties for a new entity (API) or excipient or their mixture without very detailed experimental investigation (based on Design of Experiments-DOE) requiring significant amount of time and resources.

Properties such as flow, compaction, disintegration, dissolution, hardness and chemical stability are all influenced by moisture. The effect of moisture has been introduced in a Discrete Elementary Method based model by incorporating Granular Bond numbers. The experimental appproach involves the flow discharge study of two different hopper angles at 20%, 40% and 60% RH of different grades of Lactose and Avicel. The DEM models for those hopper models, are validated by predicting the accurate granular bond numbers for different RH conditions and comparing the flow properties against the two hopper angles. After systemica compareison of the hopper flow experiments of different individual powders, further study will involve their binary mixtures , to determine the appropriate DEM parameters (bond number, friction coefficients etc).

The preliminary results suggest improved flow properties with the decrease of relative humidity.