Save Your Ingredients Using a Digital Twin

Learn how we collaborated with the ADDoPT project to reduce ingredient consumption and experimental effort using a digital twin

By Nicola Jones
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As a pharmaceutical manufacturer, how well do you achieve consistent product with the required particle size distribution (PSD)? How effective are your advanced process control schemes? Such consistency typically requires experiment…after experiment…after experiment, as well as substantial active pharmaceutical ingredient (API) consumption during development.

In this case study, we collaborated with the ADDoPT project to develop a novel approach using a model as a digital twin for in-silico model predictive control (MPC) development. The proposed advanced control scheme required up to 60% fewer trials, resulting in substantially reduced API consumption and experimental effort.

For details on our approach and methods, check out the full use case below.

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