(466d) Parameter Estimation Methods for Salting out Crystallization

Predictive modeling is increasingly utilized to gain better understanding of processes and reduce the number of experiments required for process development, optimization and understanding. In the pharmaceutical arena, modeling is typically utilized in late stage projects to provide additional data for QbD and for design space verification and confirmation. All models require the knowledge of appropriate kinetic parameters which are typically acquired from experiments. PAT tools are well suited to generate a wealth of data that can be used to estimate kinetic parameters to be utilized in predictive models. In this study we present two approaches to extract crystal growth kinetic parameters from PAT tools, namely FTIR/ATR and FBRM, combined with off-line microscopy. The methods are applied to a salting out crystallization that affords elongated, columnar crystals. Two parameter estimation approaches are utilized: a GSK developed algorithm that returns growth parameters in two growth directions and a parameter estimation routine developed by Scale-up systems Ltd. in collaboration with GSK. The two approaches provided similar growth kinetic parameters that were utilized to perform simulations to predict process behavior under different process conditions.