Intelligent Columns for Synthesis and Separation

工业层析成像系统有限公司（ITS）是一家设计和制造精密仪器的公司，提供对过程操作的深入了解。我们的产品在全球市场销售，具有工业4.0的未来潜力。在这个项目中，我们的目标是将我们的人工智能（AI）知识与我们最先进的电阻抗断层扫描技术（EIT）相结合，以应对制药市场的工业挑战，我们的创新承诺在降低制造成本的同时，大大提高产品质量和效率。该项目针对全球通用的“填充柱”工艺，在该工艺中，试剂反应形成最终或中间制品填充柱是一种广泛用于化学品分离、蛋白质合成和蛋白质纯化的技术，这些是药物和疫苗开发的基本关键过程。色谱柱过程中会产生大量的化学废物，这是提高效率和降低成本的主要候选者。ITS建议使用创新的电阻抗断层成像（EIT）技术，结合我们的人工智能知识，实时准确监控色谱柱过程。EIT是一种非侵入性技术，它可以扫描并重建一个过程到实时图像中，这使得用户可以在没有任何反应干扰的情况下“看到他们的过程”。在这个项目中，人工智能将与EIT技术相结合，以“使其更智能”。在项目结束时，我们将拥有一个"智能色谱柱系统"，该系统可以正确诊断色谱柱条件，同时提供实时工艺信息，而无需终端用户的任何额外输入。这将在设计有效的柱工艺方面给最终用户和制造商带来相当大的好处，通过提高生产率，同时延长柱材料的生命周期，从而降低制药行业的制造成本。

Industrial Tomography Systems Ltd (ITS) is a designer and manufacturer of sophisticated instrumentation providing major insight into process operations. Our products are sold in global markets with future potential for Industry-4.0\. In this project, we aim to combine our Artificial Intelligent (AI) knowledge, with our state-of-the-art electrical impedance tomography technology (EIT), to tackle the industrial challenges in the pharmaceutical market, where our innovation promises major enhancements in product quality and efficiency with reduced manufacturing cost.This project targets the globally common 'packed column' process in which reagents react to form a final or intermediate product. The packed column is a widely used technique for chemicals separation, protein synthesis and protein purification, which are fundamentally key processes for drug and vaccine developments. Significant chemical waste is produced during the column process and it is a prime candidate for efficiency and cost reduction improvements.ITS is proposing to use an innovative electrical impedance tomography (EIT) technique, in combination with our AI knowledge, to accurately monitor the column process in real-time. EIT is a non-intrusive technique that scans and reconstruct a process into real-time images, which allow users to 'see inside their processes' without any reaction disturbance. In this project, AI will be combined with EIT technology to 'make it smarter'. At the end of the project, we will have a 'Smart Column System' that can correctly diagnose the column conditions, and at the same time provide real-time process information, without any extra input from the end-users. This will give the end-user and manufacturer considerable benefit in designing an efficient column process, by increasing productivity, and at the same time, extending the life-cycle of the column material, thus reducing manufacturing costs in the pharmaceutical industries.