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

颗粒产品用于制药、农用化学品、染料和颜料、食品、洗涤剂和配方添加剂等行业。众所周知，颗粒形态对产品的最终用途性质（例如药物的溶出速率和生物利用度）和可加工性（例如流动性）极其重要。在极端情况下，导致公司失去生产药品的许可证。然而，反应器中颗粒群的形状分布的配制和制造中的优化和控制长期以来被认为太具有挑战性而难以实现。因此，先前的努力集中在优化和控制颗粒尺寸分布，其中颗粒的尺寸被定义为具有相同体积的颗粒的球体的直径。这显然忽略了粒子形状的重要信息。由王雪教授领导的小组一直在研究测量技术（使用过程中成像），建模以及优化和控制颗粒群的形状分布。该研究取得了两项重大突破性进展-多尺度图像分析技术和形态种群平衡过程模型的发展，不仅使该研究处于世界领先地位，而且为商业化创造了难得的机会。一个开发项目即将与葛兰素史克签署，重点是分析药物颗粒的SEM图像，目的是了解和最大限度地减少批次间的差异。其他工业合作者（阿斯利康，先正达，国家核实验室和辉瑞）也表达了对这种商业化产品的兴趣。在EPSRC的后续拨款提案中，我们希望将通过EPSRC资助的研究开发的技术和工具商业化。在12个月结束时，我们的目标是开发一个原型工具，该工具具有现有系统无法竞争的独特功能，并且可以向潜在客户（包括最终用户客户，即颗粒产品制造商;仪器供应商;研究机构）销售，用于为客户提供数据分析服务，并吸引新的投资，以实现全面商业化和分拆公司的增长。

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.