Using process modeling to understand process dynamics and potentially explore the design space of a crystallization process is difficult because of its complex nature with many factors at play, such as initial concentration, supersaturation, seeding strategy, and flow pattern. In this work, a systematic approach is applied to sequentially estimate the growth and nucleation rate of the cooling crystallization of carbamazepine at various conditions in batch operation. Different formulations of the kinetic expressions are tested as a model discrimination exercise to obtain the best fit with the most confidence form. Then, based on the risk, determined by the purpose of the obtained model, verification and validation activities are applied. The model is verified and validated to predict concentration and D50 for a specific seeding strategy for crystallization mechanisms, including both nucleation and growth, are highly dependent on the seed PSD. A brief discussion is also given on the transferring of the batch-developed model to continuous operations in response to the growing interest in continuous crystallization development. It is found that the model can be transferred to continuous operations where the supersaturation and solid concentration are similar to those tested during batch experimentation. Because of the complex and interactive effects of supersaturation and solid conditions on crystallization kinetics, it is reasonable to conclude that in order to infer transferable crystallization kinetics, batch experimental conditions must be wide and similar enough to cover the potential continuous operating space.

• U.S. Food and Drug Administration (FDA)

• Modeling

1. carbamazepine
2. cooling crystallization
3. kinetic modelling
4. modeling
5. population balance model
6. Research Article