Multi-objective dynamic optimization of ampicillin batch crystallization: Sensitivity analysis of attainable performance vs. product quality constraint

Ampicillin is a broad-spectrum antibiotic and World Health Organization Essential Medicine whose crystallization is an important unit operation in its production. A published model for the solubility of ampicillin as a function of pH as well as growth and nucleation kinetics allows for dynamic simulation and optimization of its batch crystallization. While experimental approaches to investigating different dynamic pH profiles have been considered in the literature, dynamic mathematical optimization of pH modulations to meet specific production objectives for ampicillin batch crystallization has yet to be implemented; therein lies the novelty of this study. In this study, dynamic simulation and optimization of the batch crystallization of ampicillin are performed to establish optimal pH manipulations for different production objectives. Simulation of already published batch seeded ampicillin crystallization experiments is performed prior to definition and solution of a dynamic optimization problem for maximization of mean crystal sizes and minimization of size distribution width. The effects of seed loading, time domain discretization, and mean crystal size and size distribution width objective function weights are considered and discussed. Pareto fronts showing trade-offs between different objectives and constraints are then investigated.