Model-Based Optimization of Cooling Crystallization of Active Pharmaceutical Ingredients Undergoing Thermal Degradation

Many active pharmaceutical ingredients (APIs) undergo degradation at high temperature. Optimum cooling profiles from first principle models usually do not consider this degradation mechanism. Generally, for maximization of the rate of crystal growth, a slow cooling profile is preferred. This however keeps the API solution at elevated temperatures for a longer time, which promotes thermal degradation. For thermally unstable APIs, fast cooling is preferred to minimize the amount of degradation, leading to excess nucleation and small crystals. In this work, model-based optimization of crystallization processes of thermally unstable APIs are considered. The typical crystallization model is combined with the kinetic model of thermal degradation, and the optimum cooling profiles, which take thermal degradation into account, are computed. An in silico multiobjective optimization study is carried out to find the optimum temperature profile under the competing objectives between maximizing crystal growth and minimizing degradation of the API. Experimental studies have also been carried out to validate our in silico optimization studies.