Multiscale Model Parallelization and Run-to-Run Control of Batch Protein Crystallization

In this work, we initially develop a parallelized multiscale, multidomain modeling scheme that directly reduces computation time requirements without compromising the accuracy of established chemical models for a batch protein crystallization process. Then, a double exponentially weighted moving average (dEWMA)-based model predictive controller (MPC) is applied to a multiscale model of a batch crystallization process used to produce hen-egg-while (HEW) lysozyme crystals to compensate for batch-to-batch drift in process parameters. The average crystal shape distribution of crystals produced from the closedloop simulation of the batch crystallizer under the dEWMA-based MPC is much closer to a desired set-point value compared to that of MPC based on the nominal process model.