(252e) Optimization of a Distillative Crystallization for An API Intermediate | AIChE

(252e) Optimization of a Distillative Crystallization for An API Intermediate

Authors 

Domagalski, N. - Presenter, Bristol-Myers Squibb Co.
Fenster, M. - Presenter, Bristol-Myers Squibb Company
Doubleday, W. - Presenter, Bristol-Myers Squibb Company


This work discusses the optimization of a crystallization process in which the driving force for solubility change is the gradual modification of the process solvent composition by distillation (distillative crystallization). A process model was constructed which incorporated both the solvent composition profile as a function of distillation operations and mathematical representations of the solubility and nucleation boundaries for the API. The model was then used to establish the crystallization conditions that would optimize particle size growth. Additionally, the model offered insight into plant flexibility through in silico study of both batch and constant volume distillation processes. Modeling and laboratory scale validation experiments identified process parameters (pressure, temperature, solvent composition, and product solubility) for a distillative crystallization process with a robust seeding window. Comparative results from the laboratory are presented as well as results from pilot plant operation at a 30 kg scale.