A digital design tool that can transfer material property information between unit operations to predict the product attributes in integrated purification processes has been developed to facilitate end-to-end integrated pharmaceutical manufacturing. This work aims to combine filtration and washing operations frequently using active pharmaceutical ingredient (API) isolation. This is achieved by coupling predicted and experimental data produced during the upstream crystallization process. To reduce impurities in the isolated cake, a mechanistic model-based workflow was used to optimize an integrated filtration and washing process model. The Carman-Kozeny filtration model has been combined with a custom washing model that incorporates diffusion and axial dispersion mechanisms. The developed model and approach were applied to two systems, namely, mefenamic acid and paracetamol, which are representative compounds, and various crystallization and wash solvents and related impurities were used. The custom washing model provides a detailed evolution of species concentration during washing, simulating the washing curve with the three stages of the wash curve: constant rate, intermediate stage, and diffusion stage. A model validation approach was used to estimate cake properties (e.g., specific cake resistance, cake volume, cake composition after washing, and washing curve). A global systems analysis was conducted by using the calibrated model to explore the design space and aid in the setup of the optimization decision variables. Qualitative optimization was performed in order to reduce the concentration of impurities in the final cake after washing. The findings of this work were translated into a final model to simulate the optimal isolation conditions.
© 2024 The Authors. Published by American Chemical Society.