Innovative metabolic data integration applicable for Therapeutic Protein Development 2.0
May 6-11, 2018
Therapeutic proteins development becomes more challenging due to the complexity of the diverse molecule formats. In-depth characterization of high producer cell lines and bioprocesses is essential to ensure robust and consistent production of recombinant therapeutic proteins in high quantity and quality for clinical applications. Controlling the environmental stress present during the cultivation of cells is a key for the successful production of an intended bio-therapeutic protein.
The captured data is applied in a metabolic network model for the analysis of intracellular metabolic fluxes of Roche’s working horse of therapeutic protein production - the Chinese Hamster Ovary cell. The generated metabolic information has the potential to set a new standard for efficient and innovative process development bridging from research to market. Innovative approach of analyzing the stored data is key towards process development of therapeutic proteins 2.0.
In conclusion, the combination of quantitative metabolite profiling, multivariate data analysis, and mechanistic network model simulations can identify metabolic traits characteristic of high-performance clones and empowers the scientists to develop efficient processes.
New approach in metabolic/process modeling and results will be presented.
Wolfgang Paul, Tobias Grosskopf, Sriram Venkateswaran, and Arthur Mohr, "Innovative metabolic data integration applicable for Therapeutic Protein Development 2.0" in "Cell Culture Engineering XVI", A. Robinson, PhD, Tulane University R. Venkat, PhD, MedImmune E. Schaefer, ScD, J&J Janssen Eds, ECI Symposium Series, (2018). http://dc.engconfintl.org/ccexvi/161