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Real time on-line amino acid analysis to explore amino acid trends and link to glycosylation outcomes of a model monoclonal antibody |
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| Authors: | Nicole Azer Nicholas Trunfio Erica J Fratz-Berilla Jin Sung Hong Jackie Cullinan Talia Faison Cyrus D Agarabi David N Powers |
| Institution: | 1. U.S. Food and Drug Administration, Center for Drug Evaluation and Research, Office of Product Quality, Office of Biotechnology Products, Division of Biotechnology Review and Research II, Silver Spring, Maryland, USA;2. U.S. Food and Drug Administration, Center for Drug Evaluation and Research, Office of Product Quality, Office of Biotechnology Products, Division of Biotechnology Review and Research II, Silver Spring, Maryland, USA
Contribution: Data curation (equal), Formal analysis (equal), Investigation (equal), Methodology (equal), Resources (equal), Visualization (equal), Writing - original draft (equal), Writing - review & editing (equal);3. U.S. Food and Drug Administration, Center for Drug Evaluation and Research, Office of Product Quality, Office of Biotechnology Products, Division of Biotechnology Review and Research II, Silver Spring, Maryland, USA Contribution: Conceptualization (equal), Data curation (equal), Funding acquisition (equal), Methodology (equal), Project administration (equal), Resources (equal), Supervision (equal), Visualization (equal), Writing - review & editing (supporting);4. U.S. Food and Drug Administration, Center for Drug Evaluation and Research, Office of Product Quality, Office of Biotechnology Products, Division of Biotechnology Review and Research II, Silver Spring, Maryland, USA U.S. Food and Drug Administration, Center for Biologics Evaluation and Research (CBER), Office of Tissues and Advanced Therapies (OTAT), Division of Cellular and Gene Therapies (DCGT), Silver Spring, Maryland, USA Contribution: Conceptualization (equal), Data curation (equal), Methodology (equal), Resources (equal), Writing - original draft (supporting);5. U.S. Food and Drug Administration, Center for Drug Evaluation and Research, Office of Product Quality, Office of Biotechnology Products, Division of Biotechnology Review and Research II, Silver Spring, Maryland, USA Contribution: Data curation (equal), Formal analysis (supporting), Resources (supporting);6. U.S. Food and Drug Administration, Center for Drug Evaluation and Research, Office of Product Quality, Office of Biotechnology Products, Division of Biotechnology Review and Research II, Silver Spring, Maryland, USA Contribution: Data curation (equal), Resources (equal) |
| Abstract: | Bioreactor parameters can have significant effects on the quantity and quality of biotherapeutics. Monoclonal antibody products have one particularly important critical quality attribute being the distribution of product glycoforms. N-linked glycosylation affects the therapeutic properties of the antibody including effector function, immunogenicity, stability, and clearance rate. Our past work revealed that feeding different amino acids to bioreactors altered the productivity and glycan profiles. To facilitate real-time analysis of bioreactor parameters and the glycosylation of antibody products, we developed an on-line system to pull cell-free samples directly from the bioreactors, chemically process them, and deliver them to a chromatography-mass spectroscopy system for rapid identification and quantification. We were able to successfully monitor amino acid concentration on-line within multiple reactors, evaluate glycans off-line, and extract four principal components to assess the amino acid concentration and glycosylation profile relationship. We found that about a third of the variability in the glycosylation data can be predicted from the amino acid concentration. Additionally, we determined that the third and fourth principal component accounts for 72% of our model's predictive power, with the third component indicated to be positively correlated with latent metabolic processes related to galactosylation. Here we present our work on rapid online spent media amino acid analysis and use the determined trends to collate with glycan time progression, further elucidating the correlation between bioreactor parameters such as amino acid nutrient profiles, and product quality. We believe such approaches may be useful for maximizing efficiency and reducing production costs for biotherapeutics. |
| Keywords: | amino acids bioprocessing glycosylation PCA process analytical technology |