Abstract
Abstract Model-based optimization of cocrystallization processes involves the simultaneous identification of the optimal coformer and solvent types and the process operating conditions, which should suppress the formation of undesirable solid-state forms. New methods are needed for such optimization tasks. This work presents a computational framework for the optimal selection of coformers, solvents, and operating conditions for a cocrystallization process of a drug with low aqueous solubility. The method considers a cocrystal product that meets a specified target for solubility enhancement, which enhances product functionality. The proposed framework is demonstrated for the model drug carbamazepine. An optimization problem is formulated and solved with the proposed strategy, which illustrates its effectiveness for the optimization of cocrystallization processes with constraints on the pharmaceutical product performance.
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