The problem with limiting the definition of design space to only looking at quality is that two operating points that give the same quality can differ a lot in yield and productivity. The wider design space that shows where it is possible to run the process should be supplemented with an optimal design space that shows where to the process run optimally. The challenge is that to maintain a high process performance and yield, a batch with higher amounts of impurity should be run differently than a batch with lower amounts. This work presents a method for creating a design space that takes both quality and performance into account, by optimizing the process for different batch scenarios, the interaction between input variables and process parameters can be determined and used to run the process with a constant high performance and with a very low variation of product quality.

Creating an optimal design space for chromatographic purifications: A model-based approach

245th National Meeting (2013)

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