(656g) Influence of Powder Mixture Composition on Macroscopic Powder Properties

Influence of Powder Mixture Composition on Macroscopic Powder Properties

S.Fathollahi^1,2, E.Faulhammer¹, J.Khinast^1,2*

1: Research Center of Pharmaceutical Engineering (RCPE) GmbH, 8010 Graz, Austria

2: Graz University of Technology, Institute of Process and Particle Engineering, 8010 Graz, Austria

* Correspondent author: Khinast@tugraz.at

Keywords: Powder mixtures, Macroscopic properties, API, Lactose, FT4 powder rheometer

Abstract

Powder processing steps, such as feeding and blending, are critical in many industries, including the pharmaceutical industry. For example, within a continuous tablet manufacturing environment, powder blending impact quality of drugs. Powder feeding is highly relevant in continuous processes. For the design of such operations the powder properties should be known, including the particle size distribution, flowability, compressibility, electrostatic chargeability and tendency to segregate. Typically, these properties are measured for pure components. Although it is known that mixtures of pure materials do not follow a linear dependence of the macroscopic powder properties on the mixture fraction, few studies exist that quantify these effects. This, however, is important for the design and optimization of powder processing operations, such as the ones utilized in a continuous manufacturing plant.

In summary, the development of solid dosage forms and the associated manufacturing processes requires a good understanding of the relationship between powder composition and the properties of the powder [1, 2, 3]. Thus, in our work binary mixtures of powders at different composition were prepared in a Turbula mixer. Then, macroscopic powder properties were measured, including bulk and tapped density (BD and TD), powder compressibility, permeability and flowability.

In our presentation we show that there is a non-linear dependence of the relevant properties and composition and propose a model for describing these dependencies. This is highly relevant for designing processes, especially in the context of continuous pharmaceutical manufacturing.

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