(541a) Model-Based Investigation of Upstream CHO Cell Culture Process for Production of Monoclonal Antibodies with Desired N-Linked Glycosylation

N-linked glycosylation is post-translational protein modification that takes place during synthesis of monoclonal antibodies (mAbs) ¹. N-linked glycan composition or glycan index, including total afucosylation, high mannosylation, fucosylation, and/or galactosylation indexes, are often critical quality attributes (CQAs) of mAb based therapeutic proteins ². Researchers have found controlling the cell culture media components such as uridine, galactose, manganese, and ammonia concentration can tweak the glycosylation composition with the desired CQA levels ^3-5. During bioreactor operations, many process parameters or operating conditions can also affect protein glycosylation such as temperature, pH and dissolved oxygen ^6-8. However, the effect of process parameters on mAb glycosylation can vary significantly between different cell lines. To better understand the protein glycosylation process and further optimize the bioreactor operations, process modeling can be used to support quality by design (QbD) by correlating critical process parameters with critical quality attributes and further defining a design space for process operations.

We have investigated the effect of temperature and pH on protein glycosylation for a model Herceptin biosimilar (or Trastuzumab) production using a CHO cell culture cultivation in an upstream fed-batch bioreactor. Mechanistic kinetic model was developed based on the experimental data obtained under different temperature and pH combinations. The mechanistic model contains two parts, including an unstructured cell culture model and a structured intracellular model. For our unstructured cell culture model, viable cell density, glucose, ammonia, and protein concentrations are captured by empirical equations. In the structured model, the intracellular kinetics of biochemical reactions cascade of the N-linked glycosylation process are simulated. The kinetic model is used to understand the effect of temperature and pH on the bioprocess. Finally, feasibility analysis with surrogate-based adaptive sampling is applied to determine a bioreactor operation design space. In this combined experimental and computational study, we have determined how adjusting the bioreactor operating conditions can achieve critical quality attributes of the targeted product. Ongoing work will implement integration with a control system to achieve real-time process control for mAb glycosylation.

References

1. Akmal, M. A.; Rasool, N.; Khan, Y. D. J. P. o., Prediction of N-linked glycosylation sites using position relative features and statistical moments. 2017, 12 (8), e0181966.
2. Szekrenyes, A.; Szigeti, M.; Dvorakova, V.; Jarvas, G.; Guttman, A., Quantitative comparison of the N-glycosylation of therapeutic glycoproteins using the Glycosimilarity Index. A tutorial. TrAC Trends in Analytical Chemistry 2020, 122, 115728.
3. Gramer, M. J.; Eckblad, J. J.; Donahue, R.; Brown, J.; Shultz, C.; Vickerman, K.; Priem, P.; van den Bremer, E. T.; Gerritsen, J.; van Berkel, P. H., Modulation of antibody galactosylation through feeding of uridine, manganese chloride, and galactose. Biotechnol Bioeng 2011, 108 (7), 1591-602.
4. Kotidis, P.; Jedrzejewski, P.; Sou, S. N.; Sellick, C.; Polizzi, K.; del Val, I. J.; Kontoravdi, C., Model-based optimization of antibody galactosylation in CHO cell culture. 2019, 116 (7), 1612-1626.
5. Ehret, J.; Zimmermann, M.; Eichhorn, T.; Zimmer, A., Impact of cell culture media additives on IgG glycosylation produced in Chinese hamster ovary cells. Biotechnol Bioeng 2019, 116 (4), 816-830.
6. Villiger, T. K.; Scibona, E.; Stettler, M.; Broly, H.; Morbidelli, M.; Soos, M., Controlling the time evolution of mAb N-linked glycosylation - Part II: Model-based predictions. 2016, 32 (5), 1135-1148.
7. Sou, S. N.; Sellick, C.; Lee, K.; Mason, A.; Kyriakopoulos, S.; Polizzi, K. M.; Kontoravdi, C., How does mild hypothermia affect monoclonal antibody glycosylation? Biotechnol Bioeng 2015, 112 (6), 1165-76.
8. del Val, I. J.; Kontoravdi, C.; Nagy, J. M., Towards the implementation of quality by design to the production of therapeutic monoclonal antibodies with desired glycosylation patterns. Biotechnol Prog 2010, 26 (6), 1505-27.