(218a) Modeling and Experimental Investigation of Polymorphic Imatinib Mesylate Crystallization in Batch and Continuous Configurations
AIChE Annual Meeting
2024
2024 AIChE Annual Meeting
Pharmaceutical Discovery, Development and Manufacturing Forum
Advances in Control Strategy using Modeling Tools and Approaches
Monday, October 28, 2024 - 3:30pm to 3:48pm
In our work, the effect of process variables such as temperature, solvent, seeding and batch time/residence time on the final polymorphic form produced is studied. As the metastable form has high solubility in methanol compared to the stable form, recrystallizing the stable form from the saturated solution of the metastable form proved beneficial in-terms of creating high supersaturations with respect to stable form and also provide high yields and volume productivity. Batch crystallization experiments revealed that high seeded experiments, seeded with metastable form and performing cooling crystallization with shorter batch times favored the crystallization of metastable form and slower cooling rates with longer holding times favored crystallization of stable form. The possibility of producing various forms selectively by varying residence times and seeding is explored in continuous configuration with a cascade of mixed suspension and mixed product removal crystallizers (MSMPRâs). However, as the main objective is to establish a continuous crystallization model for imatinib mesylate, we combine the knowledge of process analytical technology tools (PAT) (inline infrared spectroscopy, Raman spectroscopy, imaging) and offline characterization (PXRD, particle size distribution) with population balance modeling to investigate the crystallization of stable form from saturated solution of metastable form in a continuous manner at steady state. The solvent mediated polymorphic transformation of α-form form to stable β-form is more suitable for crystallization as β-form crystals are cubic shaped and have better flowability and compaction characteristics compared to needle shaped crystals of α-form. The outcomes illustrated effective model establishment for both batch and mixed-suspension-mixed-product-removal (MSMPR) crystallization configurations. This experimentally validated model, serves as a digital twin of the process which is used to optimize the MSMPR process to produce larger crystals with narrower distributions.
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