Stepping up the pace in vaccine development and production

Global healthcare company GSK is collaborating with digitalization expert Siemens and digital transformation leader ATOS to digitalize its vaccine development and production process. A key benefit will be much shorter development times for vaccines, allowing them to reach people faster and with the optimum quality. The digital twin plays a big role.

Right now, vaccine development typically progresses in many small silos, each digitalized to some extent in its own environment, but with few connections between them. This is where there is potential for optimization. Being able to consider the process as a whole and digitalizing the entire value chain would represent a significant improvement.

Digital twin: the real and digital worlds in a closed loop

For this, Siemens offers an innovative portfolio of Digital Enterprise solutions – it covers product design, which is here developing the vaccine and making the active ingredient, otherwise referred to as primary processing, and manufacturing the pharmaceutical itself, or secondary processing. Siemens collaborated with GSK and ATOS to develop an innovative concept named digital twin, which combines the real and digital worlds in a closed loop.

Digital twins allow data collection to understand exactly what is happening in real time during production. With that information, they can optimize operations

Focus on adjuvant technologies at GSK

As the first application to test the digital twin, GSK, Siemens and ATOS have developed a proof-of-concept digital twin specifically for the development and manufacturing of adjuvant technologies. Adjuvants are vaccine additives that boost the immune response. This can play an essential role to help protect people with weaker immune systems, such as older adults and immune-depressed people. Adjuvants also help reduce the volume of antigen required for each dose of vaccine, allowing the supply of more vaccine doses when demand is high.

Strong software for a challenging task

For the simulation, the “black box” of adjuvants’ particles had first to be decoded. Using mechanical models and artificial intelligence (AI), the partners developed a hybrid model to simulate and monitor the process. As such, the digital twin links the process parameters to the quality of the adjuvant. The sensors and process analytical technology (PAT) provide information that feed the twin to predict the quality of the product. Any deviation from the optimal quality is anticipated and the twin acts on the process parameters to rectify and meet the target requirements.

Various software solutions come to play here:

  • PAT is provided by Simatic SIPAT, which ensures unrestricted data transparency starting with product development and feeds the correlated data back into the process.
  • The Totally Integrated Automation Portal (TIA Portal) integrates hardware, software, and services, facilitating complete access to the entire digitalized automation system and forming the basis for the engineering process used in implementation.
  • Simulation software was used in process modeling and visualization. The process is also supported by Machine Learning.

Simulation: computational flow dynamics (CFD)

The time factor, however, posed a particular challenge for adjuvant simulation. Because the adjuvants’ particle simulation is highly computation-intensive, the computation process can take several hours. That’s a problem for real-time interaction between the digital twin and the real world.

For the simulation, the project partners had to decipher the “black box” of adjuvants’ particles

The project partners therefore extracted the process illustrated here and simulated it using computational flow dynamics (CFD). This enabled them to generate and save simulation files for all kinds of cases in advance. In combination with data from statistical trial planning (DoE) and machine learning, this gives them the ability to predict the adjuvants’ particles that will be created with each change in critical parameters. As a result, the model is real-time-capable.

Digitalization: a faster pace for new vaccine development and manufacturing

With digital twins, it is now possible to collect data to understand exactly what is happening in real time during vaccine production, enabling optimization of operations. It allows not only monitoring of complex processes, but also predicts how changes would affect them.

In short, turning to digitalization helps speed things up at GSK. In the next step, GSK wants to work with Siemens to support its vision of establishing and introducing new digital twins for the entire vaccine development process for new vaccines. Thus, the digital twins of product, production and performance will be linked together.

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