Temporal Galactose‐Manganese Feeding in Fed‐Batch and Perfusion Bioreactors Modulates UDP‐Galactose Pools for Enhanced mAb Glycosylation Homogeneity

Monoclonal antibodies (mAbs) represent a majority of biotherapeutics in the market today. These glycoproteins undergo posttranslational modifications, such as N-linked glycosylation, that influence the structural & functional characteristics of the antibody. Glycosylation is a heterogenous posttranslational modification that may influence therapeutic glycoprotein stability and clinical efficacy, which is why it is often considered a critical quality attribute (CQA) of the mAb product. While much is known about the glycosylation pathways of Chinese Hamster Ovary (CHO) cells and how cell culture chemical modifiers may influence the N-glycosylation profile of the final product, this knowledge is often based on the final cumulative glycan profile at the end of the batch process. Building a temporal understanding of N-glycosylation and how mAb glycoform composition responds to real-time changes in the biomanufacturing process will help build integrated process models that may allow for glycosylation control to produce a more homogenous product. Here, we look at the effect of specific nutrient feed media additives (e.g., galactose, manganese) and feeding times on the N-glycosylation pathway to modulate N-glycosylation of a Herceptin biosimilar mAb (i.e., Trastuzumab). We deploy the N-GLYcanyzer process analytical technology (PAT) to monitor glycoforms in near real-time for bench-scale bioprocesses operated in both fed-batch and perfusion modes to build an understanding of how temporal changes in mAb N-glycosylation are dependent on specific media additives. We find that Trastuzumab terminal galactosylation is sensitive to media feeding times and intracellular nucleotide sugar pools. Temporal analysis reveals an increased desirable production of single and double galactose-occupied glycoforms over time under glucose-starved fed-batch cultures. Comparable galactosylation profiles were also observed between fed-batch (nutrient-limited) and perfusion (non-nutrient-limited) bioprocess conditions. In summary, our results demonstrate the utility of real-time monitoring of mAb glycoforms and feeding critical cell culture nutrients under fed-batch and perfusion bioprocessing conditions to produce higher-quality biologics.

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Publication Details

Journal
Biotechnology and Bioengineering
Published
2025-04-18
DOI
https://doi.org/10.1002/bit.28999
Citations
3
Primary Topic
Viral Infectious Diseases and Gene Expression in Insects
Type
article
Field-Weighted Citation Impact
2.42

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article

Temporal Galactose‐Manganese Feeding in Fed‐Batch and Perfusion Bioreactors Modulates UDP‐Galactose Pools for Enhanced mAb Glycosylation Homogeneity

Shishir P. S. Chundawat, David N. Powers, Erica J. Fratz‐Berilla, Aron Gyorgypal et al.
3 citations
Biotechnology and Bioengineering
Viral Infectious Diseases and Gene Expression in Insects
2.42
article

Temporal Galactose‐Manganese Feeding in Fed‐Batch and Perfusion Bioreactors Modulates UDP‐Galactose Pools for Enhanced mAb Glycosylation Homogeneity

Shishir P. S. Chundawat, David N. Powers, Erica J. Fratz‐Berilla, Aron Gyorgypal, Casey Kohnhorst
article en
3 citations

Abstract

Monoclonal antibodies (mAbs) represent a majority of biotherapeutics in the market today. These glycoproteins undergo posttranslational modifications, such as N-linked glycosylation, that influence the structural & functional characteristics of the antibody. Glycosylation is a heterogenous posttranslational modification that may influence therapeutic glycoprotein stability and clinical efficacy, which is why it is often considered a critical quality attribute (CQA) of the mAb product. While much is known about the glycosylation pathways of Chinese Hamster Ovary (CHO) cells and how cell culture chemical modifiers may influence the N-glycosylation profile of the final product, this knowledge is often based on the final cumulative glycan profile at the end of the batch process. Building a temporal understanding of N-glycosylation and how mAb glycoform composition responds to real-time changes in the biomanufacturing process will help build integrated process models that may allow for glycosylation control to produce a more homogenous product. Here, we look at the effect of specific nutrient feed media additives (e.g., galactose, manganese) and feeding times on the N-glycosylation pathway to modulate N-glycosylation of a Herceptin biosimilar mAb (i.e., Trastuzumab). We deploy the N-GLYcanyzer process analytical technology (PAT) to monitor glycoforms in near real-time for bench-scale bioprocesses operated in both fed-batch and perfusion modes to build an understanding of how temporal changes in mAb N-glycosylation are dependent on specific media additives. We find that Trastuzumab terminal galactosylation is sensitive to media feeding times and intracellular nucleotide sugar pools. Temporal analysis reveals an increased desirable production of single and double galactose-occupied glycoforms over time under glucose-starved fed-batch cultures. Comparable galactosylation profiles were also observed between fed-batch (nutrient-limited) and perfusion (non-nutrient-limited) bioprocess conditions. In summary, our results demonstrate the utility of real-time monitoring of mAb glycoforms and feeding critical cell culture nutrients under fed-batch and perfusion bioprocessing conditions to produce higher-quality biologics.

Biotechnology and BioengineeringVol. 122(7)
Rutgers, The State University of New Jersey (US), United States Food and Drug Administration (US), Center for Drug Evaluation and Research (US), Harvard University (US), Massachusetts General Hospital (US), Quality Research (US)
U.S. Department of Energy, U.S. Department of Commerce, Oak Ridge Associated Universities, U.S. Food and Drug Administration, National Institute of Standards and Technology, Oak Ridge Institute for Science and Education, National Institute for Innovation in Manufacturing Biopharmaceuticals
Openalex Percentile: Top 12%
Viral Infectious Diseases and Gene Expression in Insects
2.42
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