Using a drag and drop interface process engineers can model crystallisation in batch and continuous production of active pharmaceutical ingredients (API) and excipients. Predictions made by the model can be used to make more educated process optimisation and scale up decisions.
“New model-based techniques now make scale-up from laboratory bench to industrial size much easier and more reliable”, said Sean Bermingham, vice president of strategic business development at PSE's solids modelling business.
Processes that have already been scaled up can be optimised based on modelling data. “Proper quantification makes it possible to achieve higher throughput and better and consistent quality, often with large energy savings”, Bermingham said.
Case studies
PSE has trialled the system with pharmaceutical clients and written up the results as case studies. Friesland Campina cut batch time for production of pharma grade lactose by 44% after changing its cooling crystallisation process, PSE said, and others have used the platform for APIs.
Working with a pharma company and Mettler-Toledo AutoChem PSE scaled-up production of an API from 1 litre laboratory scale to 1.6m³ vessels. The effects of scale up were predicted and the process optimised using PSE’s platform, allowing the pharma company to quickly transition to 1.6m³ vessels.
“The hybrid modelling approach allowed scale-up to the new size based with design decisions based on detailed understanding of the growth in various zones of the crystalliser”, PSE said.