How To Develop More Robust Crystallization Processes

Crystallization and precipitation are critical processing steps in chemical development. They can serve as purification and separation steps, and have implications on the yield, purity and particle size distribution. Even though crystallization has advanced significantly over the past decade, many chemists have such short deadlines that they must base everyday decisions on past experience rather than understanding the crystals in situ. Due to the complexity of crystallization, a process may be developed simply by crashing solids out of solution and transferring a non-robust process with inconsistencies in the yield, purity and particle size distribution.

Today every crystallization and precipitation step has an opportunity for improved understanding and quality. Chemists use established inline Process Analytical Technology (PAT) techniques to understand what is changing during the process and gain knowledge to ensure the desired size, shape and form is isolated. In the past, understanding crystallization processes was considered time consuming, and reserved for specialized groups, who focused on the most important process steps.

crystallization development white paperNew generations of intuitive process analytical tools provide a rapid understanding of changes (nucleation, growth, oiling out, agglomeration and supersaturation) from within the crystallizer. These tools make it easy to gain high quality information, accelerate understanding, and establish knowledge for crystallization development and transfer.

A new white paper demonstrates the methodology chemists use to identify operating parameters such as temperature, solvent addition rates and seeding to improve crystallization, batch repeatability, and crystal size and shape distribution. 

By accelerating process understanding, more robust crystallization processes are developed with higher yield and higher purity. Examples include a 10% yield improvement, elimination of a costly process impurity, and increased monthly throughput by 20%.