Abstract

There has been a growing interest in fibers and fiber-based adsorbents as alternative adsorbents for preparative chromatography. While the benefits of fiber-based adsorbents in terms of productivity have been highlighted in several recent studies, microscale tools that enable a fast characterization of these novel adsorbents, and an easy integration into process development workflows, are still lacking.In the present study an automated high-throughput screening (HTS) for fiber-based adsorbents was established on a robotic liquid handling station in 96 well filter plates. Two techniques – punching and weighing – were identified as techniques that enabled accurate and reproducible portioning of short-cut fiber-based adsorbents. The impact of several screening parameters such as phase ratio, shaking frequency, and incubation time were investigated and optimized for different types of fiber-based adsorbents. The data from the developed HTS correlated with data from packed fiber columns, and binding capacities from both scales matched closely. Subsequently, the developed HTS was utilized to optimize the hydrogel architecture of anion exchange (AEX) fiber-based adsorbent prototypes. A novel AEX fiber-based adsorbent was developed that compared favorably with existing resin and membrane adsorbents in terms of productivity and DNA binding capacity. In addition, the developed HTS was also successfully employed in order to identify step elution conditions for the purification of a monoclonal antibody from product- and process-related impurities with a cation exchange (CEX) fiber-based adsorbent. Trends from the HTS were found to be in good agreement with trends from lab scale column runs.The tool developed in this paper will enable a faster and more complete characterization of fiber-based adsorbents, easier tailoring of such adsorbents towards specific process applications, and an easier integration of such materials into processes. In comparison to previous lab scale experiments, material requirements are reduced by a factor of 3–40 and time requirements are reduced by a factor of 2–5.

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