Three-Dimensional Representations of Powder Mixedness Using a Positron Emission Tracking Technique
Brian Armstrong1, Jonathan P. K. Seville1, Xianfeng Fan2, Andy Ingram1, David J. Parker2, Trevor G. Page3, and Vejay Jekmohan4. (1) Department of Chemical Engineering, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom, (2) School of Physics and Astronomy, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom, (3) Niro Pharma Systems, GEA Process Engineering Ltd, PO Box 15, Eastleigh, SO53 4ZD, United Kingdom, (4) Buck Systems Ltd, GEA Process Engineering Ltd, 257 Wharfdale Road, Tyseley, Birmingham, B11 2DP, United Kingdom
The mixing of powders is a long established practice and is undertaken in most industrial applications where powders are handled. The quality of the mixture has a significant impact on the end product; for example the efficacy of pharmaceuticals or the strength of a sintered metal component. The measurement of the quality of a mixture is not without debate, and many ways of determining ‘mixedness' have been proposed. Tomographic techniques have been used extensively to follow process behaviour in dynamic solid/liquid and solid/gas systems, but the evaluation of batch solid/solid blending systems has been under represented. This paper presents the results of a positron emission tomographic (PET) study of the blending of a range of binary mixtures in a laboratory scale 15litre mini IBC blender. This non-invasive technique allows the radioactive marking of a small quantity of microcrystalline cellulose that can then be tracked during a blending experiment with a larger volume of another pharmaceutical excipient. The resultant data provide a full 3D map of the concentration of the minor component during the mixing process and significantly more sample points than conventional thief sampling methods. Moreover, PET allows the “scale of scrutiny” of the mixing investigation to be varied. To the authors' knowledge, this is the first time PET has been used in this way. The study will also evaluate the potential of linking the mixing behaviour to the powder properties of the range of binary systems being studied. The results allow the development of a greater understanding of mixedness in batch blenders and will permit further relational studies to on-line blend characterisation sensors, such as near infrared spectroscopy (NIR), which are becoming more prevalent under the Process Analytical Technology (PAT) Initiative promoted by the US Food and Drug Administration (FDA).