The first research focuses on implementing PAT tools in the crystallization process to enhance sustainability by reaching the desired particle size and eliminating agglomeration concerns. The experimental data helps in successfully executing the scale up batch up to pilot scale.
The second case study mainly focused on improving the distillation operation within the crystallization process, a combination of simulation models and laboratory experiments was employed. This approach facilitated the development of an effective scale-up process, optimizing both distillation time and solvent usage. The results demonstrated the importance of integrating simulation models with experimental data for process optimization.
The third case study shows importance of mixing parameter in maintaining the diastereomeric ratio of an API to avoid temperature or concentration gradients that could favor isolation of one diastereomer over the other in the crystallization process. The dimensionless numbers were estimated using simulation software at lab scale, assisted in defining the mixing parameter required for a successful scale up batch.
These case studies collectively illustrate the potential for sustainable advancements in pharmaceutical crystallization processes through the integration of PAT tools and simulation models.