SHAPE: Morphology Characterisation and Control of Particulate Products: Integrating Multi-scale Image Analysis and Modelling

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Particulate products are made in industries including pharmaceuticals, agro-chemicals, dyes and pigments, food, detergents and formulation additives. It is well known that particle morphology is extremely important to products end-use properties e.g. dissolution rate and bio-availability of pharmaceuticals and processability e.g. flowability. In extreme cases, resulting in a company's loss of the license to make the drug product. However, optimisation and control in formulation and manufacture of the shape distribution of a particle population in a reactor has long been considered to be too challenging to achieve. Therefore, previous efforts have focused on optimising and controlling particle size distribution where the size of a particle is defined as the diameter of a sphere that has the same volume of the particle. This clearly misses important information of particle shape. The group led by Professor Xue Wang has been researching technologies for measurement (using in-process imaging), modeling, and optimisation and control of the shape distribution for a particle population. The research has led to two major breakthrough advance - the development of a multi-scale image analysis technique and a morphological population balance process model, which not only positioned the research in a world leading position, but also created a rare opportunity for commercialisation. A development project is close to be signed with GlaxoSmithKline focusing on analysing the SEM images of pharmaceutical particles with the aim of understanding and minimising batch to batch variation. Other industrial collaborators (AstraZeneca, Syngenta, National Nuclear Laboratory and Pfizer) have also expressed interest in such a commercialised product.In this EPSRC follow-on grant proposal we want to commercialise the technologies and tools developed through the EPSRC funded research. At the end of the 12 moths, we aim to develop a prototype tool that has unique features that no existing system can compete, and can be marketed to potential customers (including end-user customers i.e. particulate product manufacturers; instrument suppliers; research organisations), used to provide data analysis services to customers, and attract new investment for full commercialization and the spin-off company growth.