Title
Metabolomics process modeling: A systems biology approach to understand variability in commercial biologics cell culture processes
Conference Dates
July 14-18, 2019
Abstract
The biopharmaceutical industry strives to develop and operate efficient, robust, reproducible commercial biologics processes. A major challenge of industrial biologics processes is optimization of cell culture conditions to increase productivity while maintaining consistent product quality. The cell culture operations, which involve the use of live cell hosts, have historically introduced significant variability to the overall process. Technological improvements which include the implementation of advanced cell line engineering, chemically defined media, quality by design (QbD) development approaches, and in-line and at-line monitoring, have significantly reduced process variability. Nonetheless, performance variability remains a challenge for many commercial programs. This variability in turn can impact both product yields and product quality. Even small performance differences can become significant in low-yield processes with large campaign sizes, or processes manufactured at multiple sites. The ability to understand and eliminate sources of variability is greatly enhanced by augmenting the quality and quantity of data available from commercial campaigns. Metabolomics Process Monitoring (MPM) is a data-driven approach to understand sources of manufacturing variability on a cellular level. Here we present a case study of MPM implementation in a legacy commercial biologics program. First, we describe how the MPM workflow was successfully integrated into a commercial manufacturing process. Second, we discuss novel data normalization techniques developed to enable long term trending. Third, we describe the selection of an orthogonal projections to latent structures (OPLS) model to link systems biology and process data. Finally, we share key mechanistic insights obtained from the case study, and provide a vision for how MPM can enhance commercial biologics capabilities going forward.
Recommended Citation
Amanda Lewis, Sophia Liu, Jan Lucas Ott, Eric Garr, Bethanne Warrack, and Michael Reily, "Metabolomics process modeling: A systems biology approach to understand variability in commercial biologics cell culture processes" in "Biochemical and Molecular Engineering XXI", Christina Chan, Michigan State University, USA Mattheos Koffas, RPI, USA Steffen Schaffer, Evonik Industries, Germany Rashmi Kshirsagar, Biogen, USA Eds, ECI Symposium Series, (2019). https://dc.engconfintl.org/biochem_xxi/94