Assessing predictability of packing porosity and bulk density enhancements after dry coating of pharmaceutical powders

Ability to predict the porosity, and its reduction after nano-silica dry coating, based on the Bond number and cohesion force estimated via multi-asperity contact model was examined for twenty different pharmaceutical powders. A new model for first order estimates of bulk density improvements after dry coating was found to be reasonably predictive despite variations in size (10–225 μm), particle size distribution, aspect ratios (1–3.5), material density, and dispersive surface energy.

Highlights

• A new empirical model predicts increase in bulk density (10–90%) after dry coating.

• Bond number model well-predicted porosity of a variety of pharmaceutical powders.

• MCC were outliers, due to high relative SSA from non-sphericity and macro-roughness.

• MCC behavior mimicked prior DEM results for cohesive, high aspect ratio particles.

• Using entire PSD vs d₅₀ alone or asperity adjustments did not improve prediction.

For the porosity prediction model based on Bond numbers, Microcrystalline Cellulose (MCC) excipients were outliers, regardless of size (20–200 μm). Analysis of their shape, surface morphology and specific surface areas (SSA), indicated that compared to other powders, MCCs had the highest SSA compared to equivalent spheres and high macro-roughness, while having high aspect ratios. This unique characteristic made them effectively more cohesive leading to their poor packing independent of their size, which is in line with previous simulations. More on assessing predictability of packing porosity and bulk density enhancements after dry coating of pharmaceutical powders