Digitalisation and automation of high-value biomanufacturing

二十多年来，蛋白质已被用于治疗各种危及生命的疾病，如癌症和自身免疫性疾病。然而，单克隆抗体等蛋白质类药物的获取受到严重限制，因为治疗费用高达每名患者每年35 000美元。这部分是由于药物和工艺开发的高成本以及制造工艺本身的高运营成本。负责开发和交付这些药物的生物加工行业在自动化和数字化方面落后于汽车、航空和化学品制造等其他行业。人们普遍认为，将操作与监测过程性能的技术相结合，可以在效率和成本降低方面带来阶跃式变化。拟议工作的目的是开发一个数字孪生模型，这是一个基于计算机的制造过程模拟，以及一个界面，很像和应用程序，用于将其与过程中的测量集成。开发将首先集中在单克隆抗体的成熟制造工艺上，以微调模型及其与传感技术的集成。然后，我们将继续调整我们的工作，以适应新型蛋白质产品的新制造工艺，这也带来了挑战。我们将与工业界密切合作，以确保我们的技术是实用和方便用户的，因此，更有可能以负责任的方式使用。我们设想，我们的方法将是使工业加快工艺开发和自动化制造的第一步。

Proteins have been used for the treatment of a variety of life-threatening diseases like cancers and autoimmune disorders for over two decades. Access protein-based drugs, such as monoclonal antibodies, is, however, severely restricted as treatment cost is as high as $35,000 per patient per year. This is due, in part, to the high cost of drug and process development and the high operating cost of the manufacturing process itself. The bioprocessing industry, which is responsible for developing and delivering these drugs, is lagging behind other industries such as automotive, aviation and chemicals manufacture in terms of automation and digitalisation. It is widely thought that the integration of operations with technologies that monitor process performance can introduce a step-change in efficiency and cost-reduction. The purpose of the proposed work is to develop a digital twin, which is a computer-based analogue of the manufacturing process, and an interface, much like and app, for integrating it with measurements from the process. The development will first focus on the mature manufacturing process of monoclonal antibodies to finetune the models and their integration with sensing technologies. We will then proceed to adapt our work to a new manufacturing process of novel protein products, which presents its own challenges. We will work closely with industry to ensure that our technology is practical and user-friendly and, therefore, more likely to be used in a responsible way. We envisage that our approach will be a first step towards enabling industry to expedite process development and automate manufacturing.