Multi-objective optimization of simulated moving bed and Varicol processes for enantio-separation of racemic pindolol

Rigorous multi-objective optimization of simulated moving bed (SMB) and Varicol processes for enantio-separation of racemic pindolol, a nonselective beta blocker in terms of cardio-selectivity, was carried out in this study using an experimentally verified mathematical model and isotherm parameters. Several two-objective optimization problems were solved simultaneously maximizing product purity and recovery for both SMB and Varicol processes. The shift in Pareto optimal solutions was investigated to study the effect of feed concentration, eluent flow rate as well as column geometry and column configuration. A state-of-the-art optimization technique, non-dominated sorting genetic algorithm with jumping genes (NSGA-II-JG) was used to obtain the Pareto optimal solutions. Significant performance improvement was achieved when rigorous optimization was performed. Subsequently, the optimized solutions were verified experimentally. The results show that operating conditions for SMB and Varicol processes should be selected as a compromise between separation performance and robustness.