Model-Supported\nDesign of Multicolumn Countercurrent\nSolvent Gradient Purification Processes for Rapid Implementation

The development of industrial chromatography is typically\nconstrained\nby timelines and available material. For the design of continuous\nmulticolumn processes like multicolumn countercurrent solvent gradient\npurification (MCSGP), the required material consumption during development\n(≈10 to 20 g) is a major issue. In this work we present a\nmethod based on mechanistic modeling to design MCSGP operation in\na material and time-efficient manner and such as to result in a process\nthat is easy to transfer, and fits within a specific facility. Starting\nfrom a viable model, the workflow consists of three major steps: (i)\nsingle column simulations are carried out to identify batch chromatography\nruns that result in a sufficient quality, and to assess recycle parameters\nexpected to result in a fast convergence to cyclic steady state (CSS),\n(ii) all suitable batch runs are transferred to MCSGP by following\nthe common pragmatic approach and the twin column process is simulated\nuntil cyclic steady state; (iii) facility fit is investigated by scaling\nup and adapting the process to the equipment for commercial production.\nWe report the results of applying this workflow in the context of\nan industrial case study, where an MCSGP process was designed for\nthe purification of a synthetic peptide. The results highlight how\nthis methodology allows to design MCSGP operating conditions that\nmeet a target purity in a robust manner, and for which the CSS is\nreached within a few cycles only.