A hybrid system of mixture models for the prediction of particle size and shape, density, and flowability of pharmaceutical powder blends.

This paper presents a system of hybrid models that combine both mechanistic and data-driven approaches to predict physical powder blend properties from their raw component properties. Mechanistic, probabilistic models were developed to predict the particle size and shape, represented by aspect ratio, distributions of pharmaceutical blends using those of the raw components. Additionally, the accuracy of existing mixture rules for predicting the blend's true density and bulk density was assessed.