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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. [ABSTRACT FROM AUTHOR]

Amino acids and glucose consumption, cell growth and monoclonal antibody (mAb) production in mammalian cell culture are key considerations during upstream process and particularly media optimization. Understanding the interrelations and the relevant cellular physiology will provide insight for setting strategy of robust and effective mAb production. The aim of this study was to further our understanding of nutrient consumption metabolism, since this could have significant impact on enhancing mAb titer, cell proliferation, designing feeding strategies, and development of feed media. The nutrient consumption pattern, mAb concentration, and cell growth were analyzed in three sets of cell cultures with media supplementation of glucose, methionine, threonine, tryptophan, and tyrosine. The amino acids metabolism and its impact on cell growth and mAb production during the batch and fed‐batch culture were closely analyzed. It was shown that the phenylalanine, tyrosine and tryptophan biosynthesis pathways were significantly altered under different culture conditions with different media. These changes were more apparent in the fed‐batch process in which higher mAb titer was observed due to the metabolic changes than mAb titer in the batch process. The pathway analysis approach was well utilized for evaluating the impact on the relevant pathways involved under different cell culture conditions to improve cell growth and mAb titer. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:793–805, 2018 [ABSTRACT FROM AUTHOR]

Fermentanomics is an emerging field of research and involves understanding the underlying controlled process variables and their effect on process yield and product quality. Although major advancements have occurred in process analytics over the past two decades, accurate real-time measurement of significant quality attributes for a biotech product during production culture is still not feasible. Researchers have used an amalgam of process models and analytical measurements for monitoring and process control during production. This article focuses on using multivariate data analysis as a tool for monitoring the internal bioreactor dynamics, the metabolic state of the cell, and interactions among them during culture. Quality attributes of the monoclonal antibody product that were monitored include glycosylation profile of the final product along with process attributes, such as viable cell density and level of antibody expression. These were related to process variables, raw materials components of the chemically defined hybridoma media, concentration of metabolites formed during the course of the culture, aeration-related parameters, and supplemented raw materials such as glucose, methionine, threonine, tryptophan, and tyrosine. This article demonstrates the utility of multivariate data analysis for correlating the product quality attributes (especially glycosylation) to process variables and raw materials (especially amino acid supplements in cell culture media). The proposed approach can be applied for process optimization to increase product expression, improve consistency of product quality, and target the desired quality attribute profile. [ABSTRACT FROM AUTHOR]

Fermentanomics, or a global understanding of a culture state on the molecular level empowered by advanced techniques like NMR, was employed to show that a model hybridoma culture supplied with glutamine and glucose depletes aspartate, cysteine, methionine, tryptophan, and tyrosine during antibody production. Supplementation with these amino acids prevents depletion and improves culture performance. Furthermore, no significant changes were observed in the distribution of glycans attached to the IgG3 in cultures supplemented with specific amino acids, arguing that this strategy can be implemented without fear of impact on important product quality attributes. In summary, a targeted strategy of quantifying media components and designing a supplementation strategy can improve bioprocess cell cultures when enpowered by fermentanomics tools. Published 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29:745-753, 2013 [ABSTRACT FROM AUTHOR]

Monoclonal antibodies are mainly produced by mammalian cell culture, which due to its complexity, results in a wide range of product variants/isoforms. With the growing implementation of Quality by Design (QbD) and Process Analytical Technology (PAT) in drug manufacturing, monitoring and controlling quality attributes within a predefined range during manufacturing may provide added consistency to product quality. To implement these concepts, more robust analytical tools could reduce the time needed for monitoring quality attributes during upstream processing. The formation of protein aggregates is one such quality attribute that can lead to safety and efficacy issues in the final drug product. Described in this study is a fully automated two-dimensional high performance liquid chromatography (2D-HPLC) method for characterizing protein aggregation of crude in-process bioreactor samples. It combines protein A purification and separation by size exclusion into a single analytical module that has the potential to be employed at-line within a bioprocessing system. This method utilizes a novel in-line fraction collection device allowing for the collection of up to twelve fractions from a single sample or peak which facilitates the subsequent linked analysis of multiple protein peaks of interest in one chromatography module. [ABSTRACT FROM AUTHOR]