Digitalisation of the vaccine development and production process at GSK
The pharmaceutical company GSK collaborates with Siemens and ATOS, two of the world’s leading expert companies in digital transformation and technology, to digitalise its vaccine development and production process. This innovative concept named digital twin, which combines the real and digital worlds in a closed loop. A key benefit will be much shorter development times for vaccines.
A Digital Twin is a virtual replica of a process, product, or service. When applied to producing vaccines, it combines the virtual and real realms of development and manufacturing in a closed loop to collect real-time insights from the onset. When the Digital Twin is connected to the real process, the physical sensors send data to the twin and the simulated insights are fed back to the control system to keep the process at the optimum. Think of it as a real-world experiment informing a computer-simulated (in silico) experiment, and vice versa, in a closed-loop so that both can become as efficient as possible.
After successful completion of a proof-of-concept project with Siemens and Atos focusing on the production of particles of a vaccine adjuvant, Digital Twins are now becoming a reality at GSK.
It allows the company to simulate, monitor closely, anticipate failures, and optimise quality and self-learning. The performance data obtained from real run is fed back into the development process and helps optimise products and processes at an early stage. Ultimately this means GSK can speed up the vaccine manufacturing process and get vaccines to people faster.
In addition to production, GSK is also exploring the potential of a Digital Twin to transform the process of vaccine R&D further upstream. Early in a vaccine project, the combination of high-throughput experimentation and the twin models would quickly produce data needed to confirm theories. Further down the line, a Digital Twin has the potential to drastically reduce real experimentation, meaning fewer materials and less energy is consumed. It also allows to reduce batch waste, helping R&D to increase sustainability.
