Demonstration of continuous gradient elution functionality with automated liquid handling systems for high-throughput purification process development

Various high-throughput systems and strategies are employed by the biopharmaceutical industry for early to late-stage process development for biologics manufacturing. The associated increases to experiment productivity and reduction in material consumption makes high throughput tools integral for bioprocess development. While these high-throughput systems have been successfully leveraged to generate high quality data representative of manufacturing scale processes, their data interpretation often requires complex data transformation and time-intensive system characterization. With respect to high throughput purification development, RoboColumns by Repligen operated on Tecan automated liquid handling systems offer superior performance scalability, but lack an optimized liquid delivery system that is representative of preparative chromatography. Particularly, stock Tecan liquid handling systems lack the capability to provide high-capacity continuous liquid flow and ideal linear gradient chromatography conditions. These limitations impact protein chromatography performance and hinder the application of high-throughput gradient elution experiments. In this work, we describe a Tecan Freedom EVO high-throughput purification tool that provides more continuous liquid delivery enabling continuous gradient elution capability for RoboColumn experiments as demonstrated by generation of highly linear conductivity gradients. Results demonstrate that the tool can provide RoboColumn performance and product quality data that is in agreement with larger, bench scale chromatography formats for two model purification methods. The described gradient purification method also provides more consistent performance between RoboColumns and larger column formats compared to step elution methods using the same optimized Tecan system. Lastly, new insights into the impact of discontinuous flow on RoboColumn elution performance are introduced, which may help further improve application of these data towards bioprocess development. (c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )