A tandem simulated moving bed (SMB) process for insulin purification has been proposed and validated experimentally. The mixture to be separated consists of insulin, high molecular weight proteins, and zinc chloride. A systematic approach based on the standing wave design, rate model simulations, and experiments was used to develop this multicomponent separation process. The standing wave design was applied to specify the SMB operating conditions of a lab-scale unit with 10 columns. The design was validated with rate model simulations prior to experiments. The experimental results show 99.9% purity and 99% yield, which closely agree with the model predictions and the standing wave design targets. The agreement proves that the standing wave design can ensure high purity and high yield for the tandem SMB process. Compared to a conventional batch SEC process, the tandem SMB has 10% higher yield, 400% higher throughput, and 72% lower eluant consumption. In contrast, a design that ignores the effects of mass transfer and nonideal flow cannot meet the purity requirement and gives less than 96% yield.

A tandem simulated moving bed (SMB) was developed previously for the purification of insulin from two impurities in two sequential steps. In this study, an efficient optimization tool based on the standing wave design is developed to find the optimal tandem SMB for insulin purification. Both system parameters (total number of columns, zone configuration, column diameter, and column length for each ring) and operating parameters (zone flow rates and switching time for each ring) are optimized to achieve the lowest purification cost. In the production range of interest, equipment cost dominates. For this reason, the optimal design has eight or fewer columns in each ring. The optimal design also has a small column length and a large column diameter, as the stationary phase for insulin purification is compressible and has a zone linear velocity limit. Splitting strategies and constraints on the column diameter and column length have significant effects on the optimal design. If there is a limit on the column diameter, optimization of the splitting strategy and column length can result in 24 and 25% savings, respectively, in total purification costs. Finally, if the limit on linear velocity is removed, a lower purification cost can be achieved by using longer columns with smaller diameters. The method developed in this study can be applied to other size-exclusion systems or linear isotherm systems.

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