Predicting bulk density of pharmaceutical powder formulations - industrially applicable approach

Bulk density ( ρ b ) serves as a fundamental powder parameter across various industries. In the pharmaceutical industry, its implications on powder behaviour are well known through various processing stages and unit operations. Since the measurement of ρ b is an ordinary analysis during formulation development, the ability to predict ρ b could streamline this stage, saving both time and material resources. The objective of this study was to establish an easy-to-use and industrially relevant predictive model for the ρ b of binary mixtures, leveraging data derived from pure materials. Two distinct methodologies grounded in the principles of flow behaviour in packed beds and the computation of the equivalent hydraulic diameter were developed. The first approach conceptualises the particles of one material as a matrix, the voids within it are being filled by the particles of the second material. The second method entails a theoretical calculation of the particle size distribution of the mixture, using particle size fractions obtained from sieve analysis of the individual materials. The fractions of the calculated distribution are subsequently combined, incorporating the smaller size fractions sequentially into the larger fraction voids. Finally, the developed method could be considered industry relevant. Its application in the pharmaceutical industry might be easily implemented and widely used during the development stage. Moreover, it can reduce time and financial costs of the designed formulation. While it is yet to be tested, the size selective method is not principally limited to binary mixtures and it can be extended to multi-component mixture without altering the fundamental principle. • Predictive models for bulk density of mixtures from components properties. • Bulk density and particle size distribution used as inputs. • Models based on sequential filling of voids structure. • Comparable predictive power to published models – industrially relevant.