A Novel Integrated Workflow for Isolation Solvent Selection Using Prediction and Modeling

A predictive tool was developed to aid process design and rationally select optimal solvents for isolation of active pharmaceutical ingredients. The objective minimize the experimental work required a purification by (i) starting from selected crystallization solvent based on maximizing yield minimizing consumption (with constraint maintaining suspension density which allows crystal suspension); (ii) identified step 1, list potential (selected series constraints) is ranked, thermodynamic consideration predicted purity using mass balance model; (iii) most promising combinations verified experimentally, conditions are adjusted maximize impurity removal yield, taking into account transport kinetic considerations. Here, we present selection workflow logical ranking supported solubility predictions, coupled with digital tools transfer material property information between operations predict strategy. This approach addresses isolation, preserving particle attributes generated during crystallization, risks product precipitation dissolution washing, solvents, favorable drying.