Rajesh Dave, New Jersey Center for Engineered Particulates,
New Jersey Institute of Technology
Newark, NJ, USA

Particle surface engineering is a cost-effective, promising route to achieve enhancements in the flowability, bulk density and other properties of a variety of cohesive active pharmaceutical ingredients (APIs). This presentation will discuss predictive enhancements after dry coating based particle surface engineering and discuss models and guidelines for the selection of flow aid type and amount, as well as predicting powder bulk properties from their particle-scale properties such as the particle size and distribution, materials density, surface energy, and surface roughness. The use of dry coating in developing direct compression ready blends will be also presented. through dry coating of either API or excipients. Towards those goals, industrially relevant and scalable dry coating devices are used and compared against a material sparing benchmarking device. Mechanistic particle contact models are employed for examining the causes of cohesion reduction and subsequent property enhancements. The bulk property based 2-D processability maps are introduced and used to assess the extent of enhancements in flow and packing as well as the possibility of avoiding wet and/or dry granulation, as well as for moving towards direct compression at high drug loadings. Results are presented to demonstrat that dry coating for particle surface engineering is a powerful technique. Along with our predictive, model-based approach, it can help mitigate problems posed by fine powders, with positive outcomes in flow, and bulk density improvements. Such enhancements enable high drug loaded fine and cohesive API blends through particle engineering. Overall, the bulk property based 2-D processability maps along with dry coating based property enhancements can help make manufacturing decisions regarding the formulation strategy for solid pharmaceutical dosages, presenting a promising platform for commercial applications and cost reduction.

Key Words:     Cohesive powders, dry coating, flowability, bulk density, predictive models