General Interest: Using DynoChem to Inform Experimental Design of Batch Crystallization
Wednesday, December 12, 2012 from 9:00 AM to 10:00 AM (EST)
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Rahn McKeown of GSK will describe how a simplified modeling strategy has been devised to minimize the experimental load for evaluating the design space of a crystallization.
The step-wise approach is:
1. Collect solubility data and desupersaturation data
2. Fit to a mass transfer based model
3. Build a model in DynoChem which describes the crystallization process parameters
4. Simulate processing conditions in DynoChem using a full factorial design for all parameters
5. Visualize the response "maximum supersaturation" and reduce the DoE.
This response can then be used as a proxy for the final crystal properties. The number of factorial DoE experiments can then be greatly reduced by using "maximum supersaturation" as a parameter instead of the multitude of processing parameters.
In this talk, Rahn will present model performance against an optimization DoE as a training set, as well as examples of how this approach can be used to reduce experimental load for a scoping study and also a robustness DoE.
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