High‐Throughput Technologies in Bioprocess Development

Abstract

Bioprocess development is a relatively new field for the application of high‐throughput technologies (HTT). Similar to historical applications in drug discovery, these new tools are generally being applied to increase throughput and efficiency to either enable improved performance by testing a larger experimental design space or improve speed for development for biological pipelines. In surveying the general application of these technologies in the biotechnology industry, it becomes clear that HTT have targeted a few key steps within upstream and downstream process development workflows (also called HTPD i.e. high‐throughput process development). The primary focus for upstream HTT has been cell line selection and cell culture development, whereas downstream HTT has centered on the chromatography unit operation. The successful implementation of these technologies has come with many lessons learned on technology selection, workflow validation, and study execution. Furthermore towards improving the application of HTT, analytical techniques in combination with experimental design strategies have been developed that enable larger and more complete scientific investigation of experimental conditions. The complete set of tools, techniques, and design strategies have yielded tangible benefits for early adopters, particularly where capacity and timeline restrictions create workflow bottlenecks. Applied properly, high‐throughput technologies can be an important tool in meeting the bioprocess challenges of today and tomorrow.

Optimization of cell culture‐derived influenza A virus particles purification using sulfated cellulose membrane adsorbers

“…Design of Experiments (DoE) is a valuable tool for both in academia and industry. The advantages of its application in the production of biopharmaceuticals are widely covered . Although less intuitive than the ‘changing one separate factor at a time’ approach, the application of a DoE strategy can significantly increase the amount and the (statistical) meaning of the information retrieved when screening or optimizing experimental factors.…”