Digitalisation and automation of high-value biomanufacturing

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.