Controlling the time evolution of mAb N‐linked glycosylation ‐ Part II: Model‐based predictions

Abstract

N-linked glycosylation is known to be a crucial factor for the therapeutic efficacy and safety of monoclonal antibodies (mAbs) and many other glycoproteins. The nontemplate process of glycosylation is influenced by external factors which have to be tightly controlled during the manufacturing process. In order to describe and predict mAb N-linked glycosylation patterns in a CHO-S cell fed-batch process, an existing dynamic mathematical model has been refined and coupled to an unstructured metabolic model. High-throughput cell culture experiments carried out in miniaturized bioreactors in combination with intracellular measurements of nucleotide sugars were used to tune the parameter configuration of the coupled models as a function of extracellular pH, manganese and galactose addition. The proposed modeling framework is able to predict the time evolution of N-linked glycosylation patterns during a fed-batch process as a function of time as well as the manipulated variables. A constant and varying mAb N-linked glycosylation pattern throughout the culture were chosen to demonstrate the predictive capability of the modeling framework, which is able to quantify the interconnected influence of media components and cell culture conditions. Such a model-based evaluation of feeding regimes using high-throughput tools and mathematical models gives rise to a more rational way to control and design cell culture processes with defined glycosylation patterns. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1135-1148, 2016.

Influence of protein/glycan interaction on site‐specific glycan heterogeneity

“…Fluxes were considered time invariant (16). In addition, a pseudo steady state was assumed for structures within the Golgi, given that the protein residence time in the Golgi (20-40 min) is much shorter than any observed change in protein glycosylation, which is on the order of days (40,42). The balance of the fluxes between the different glycan structures within the glycosylation network can therefore be written as Eq.…”

Quality by control: Towards model predictive control of mammalian cell culture bioprocesses

“…Given the ultimate QbD objective of controlling the CQAs, such as the glycan profile or the charge variants of monoclonal antibodies, it is evident that the models must describe the formation of these attributes. In case of the glycan profile, progress has been made in the modeling of the Golgi apparatus and the underlying reaction network . However, in case of the charge variants only data‐driven models have been applied to date .…”

“…The sensitivity of e.g. the glycan formation to the changes in the extracellular environment, such as temperature, ammonia, manganese and nucleotide sugars , but also that of the charge variants clearly highlight the potential for advanced process control to maintain the CQAs within the limits by suitable adaptation of the media, feeding and other process parameters. To this end, hybrid modeling seems to be a suitable modeling methodology as fundamentally known relationships can be combined with data‐driven techniques that represent the unknown parts.…”

Kinetic Modeling of Mammalian Cell Culture Bioprocessing: The Quest to Advance Biomanufacturing

“…Without considering the antibody assembly mechanisms, Jedrzejewski et al coupled the biosynthetic pathways of nucleotide and nucleotide sugars with an unstructured Monod ‐type model and a pre‐existing Golgi model to simulate the glycan structures of a monoclonal antibody produced in a fed‐batch culture of hybridoma cells . The Golgi model was also coupled with unstructured Monod ‐type equations representing the simplified nucleotide sugar synthesis pathways to examine the impact of supplements on mAb N‐glycosylation patterns . Recently, a similar model has been used to investigate the effect of Golgi cisternae volume on mAb specific productivity with variations in N‐glycosylation …”