Build, Validate and Optimise Your Process Digitally

Digital Design and Scale-Up

Digital Design techniques can be used to rapidly develop and test Advanced Process Control (APC) and monitoring schemes in-silico, using parameterised mechanistic models as Digital Twins. 

The PharmaMV platfom is used to apply process response tests to a mechanistic process model, to generate a statistically rich dataset. This data is used to create a reduced order model, which is incorporated into a Model Predictive Controller (MPC), then simulated and tuned in-silco. The MPC is subsequently commissioned on the physical process, achieving equivalent performance to the in-silico system, demonstrating a reduction in material and energy consumption, as well as minimised experimental effort in comparison to a step-by-step empirical approach on the physical plant.

Perceptive Engineering, in collaboration with CPI, PSE and AZ, have developed an APC solution for a Twin Screw Wet Granulation (TSWG) process using the digital design approach. The solution, developed as part of the ADDoPT project, used the digital twin for process response testing and APC design in-silico. The tuned APC scheme was then applied to the physical TSWG process to control the particle size (D50) to target with the real-time D50 predictions coming from the Digital Twin. This digital design workflow resulted in 60% fewer trials and substantially reduced API consumption.


Case Study: Model Predictive Control of a Twin Screw Wet Granulation Process

Why use Digital Design?

  • Rapidly characterise the process operating space by running automated DoE studies on the digital twin as well as identify the ‘non-viable’ drug candidate formulations early on in the process
  • Develop and test APC and monitoring schemes in-silico and in turn minimise the material consumption and experimental effort
  • Reduce the time to market through more informed scale-up implementation

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