(343f) Estimation of Powder Blend Particle Size Distribution and Flow Properties From Single Components

Purpose: A model was developed for estimating the particle size distribution and flow performance of a blend using particle size data from each of its components. Methods: Eight blends were prepared containing 0 to 100% surrogate API (fine grade HPMCAS) with the balance of 2 parts microcrystalline cellulose and 1 part lactose. The particle size distribution (laser diffraction) and flow performance (shear cell) of each sample were measured. The experimental results were compared with a blend particle size distribution and flow model. Assuming a log normal distribution for each the components, the 10th, 50th, and 90th percentile of the particle size distribution of each component were valued as adequate descriptors of their particle size distributions. Using these three particle size descriptors, the percent of weight of each component in the total mixture, and the true density of each component, the particle size distribution of the blend was estimated. The estimated particle size distribution of the blend was then used to estimate its relative flow performance. Results: The model was successful in describing both the shape and trends of the particle size distribution of each blend. Both the experiment and model showed that as the proportion of the API was increased, the fines mode increased while the coarse mode decreased. Similarly, the model effectively estimated the trends in mean particle diameter and breadth of distribution. A previously published empirical model developed to estimate relative flow performance of a blend from its particle size distribution correlated very well with the trend, and matched the experimental flow data very well after a baseline adjustment. Conclusions: This model presents a tool for estimating the powder flow performance and particle size distribution of previously uncharacterized blends when only the particle size distribution data of each component is available. It is clearly recognized that this approach is not a substitute for sophisticated particle size or powder flow evaluations, but does offer a suitable material sparing approach to guiding the prototype design of APIs and solid dosage formulations by reducing material consumption and testing resources.