Long term culturing of CHO cells: phenotypic drift and quality attributes of the expressed monoclonal antibody.

OBJECTIVE: Establishing cell lines with enhanced protein production requires a deep understanding of the cellular dynamics and cell line stability. The aim of the study is to investigate the impact of long term culturing (LTC) on cell morphology and altered cellular functions possibly leading to phenotypic drift, impacting product yield and quality. Study highlights the orthogonal cellular and analytical assay toolbox to define cell line stability for optimal culture performance and product quality. METHODS: We investigated recombinant monoclonal antibody (mAb) expressing CHO cells for 60 passages or 180 generations and assessed the cell growth characteristics and morphology by confocal and scanning electron microscopy. Quality attributes of expressed mAb is accessed by performing charge variants, glycan, and host cell protein analysis. RESULTS: We observed a 1.65-fold increase in viable cell population and 1.3-fold increase in cell specific growth rate. A 2.5-fold decrease in antibody titer and abatement of actin filament indicate cellular phenotypic drift. Mitochondrial membrane potential (∆ΨM) signified cell health and metabolic activity during LTC. Host cell protein production is reduced by 1.8-fold. Charge heterogeneity was perturbed with 12.5% and 43% reduction in abundance of acidic and basic charge variants respectively. Glycan profile indicated a decline in fucosylation with 17% increase in galactosylated species as compared with early passaged cells. CONCLUSION: LTC impinges on cellular phenotype as well as the quality of the expressed antibody, suggesting a defined subculturing limit to retain stable protein expression and cell morphology to achieve consistent product quality. Study signifies the changes in cellular and metabolic markers, suggesting cellular and analytical toolbox which could play a significant role in defining cell characteristics and ensured product quality.

Effect of vitamins and metal ions on productivity and charge heterogeneity of IgG1 expressed in CHO cells.

Recombinant monoclonal antibodies have emerged as the most successful modality of biotherapeutics. They are primarily expressed in Chinese Hamster Ovary (CHO) cells. It is well known that post-translational modifications (PTM) contribute significantly to heterogeneity with respect to charge, glycosylation, and size. These attributes in turn impact stability, pharmacokinetics, and pharmacodynamics of the biotherapeutic product. Cell culture media components are known to significantly contribute to both cellular productivity as well as post-translational modifications. Thus, it is highly desirable to understand how media components affect product quality. This study aims to explore the impact of vitamins and metal ions on protein expression and post-translational modifications specifically charge heterogeneity. Biotin, choline chloride, D-calcium pantothenate, folic acid, pyridoxine hydrochloride, thiamine hydrochloride vitamins and Fe, Cu, Mg, Co, Zn, Mn, Ni metal ions were examined in this study. The results indicate that pyridoxine enhances productivity while Zn, Cu, Fe, Mn, and biotin impact charge heterogeneity. While, Fe, Mn and Ni enhance production of the acidic variants, Cu and biotin inhibit it. Zn reduces formation of basic variants while biotin enhances it. The results from this investigation could be used for process control so as to get consistent charge variant profile, in particular for biosimilars.

Neural network-based fingerprinting of monoclonal antibody aggregation using biolayer interferometry.

Aggregates are widely accepted to be a critical quality attribute (CQA) for biotherapeutics and believed to impact product immunogenicity. Monitoring of aggregates is typically performed using multiple orthogonal tools as any single tool is unable to offer comprehensive characterization of aggregate species over the entire size and morphology range that they can exist in. Researchers have attempted to categorize monoclonal antibody (mAb) aggregates into six classes based on their respective physicochemical properties. In this study, we have developed model based on artificial neural network (ANN) to predict the stress history of mAb contributing to the aggregate formation, based on binding sensogram profiles obtained with biolayer interferometry (BLI). It was observed that each class of mAb aggregates exhibited unique binding profiles that were characteristic fingerprint of that class. The proposed model uses principal components extracted from the mAb-Fcγ receptor binding sensogram (106 profiles from 9 stressed mAb samples) as inputs while the unique identification codes in the form of binary coded numbers are used as model outputs. The latter served as a fingerprint for each class of mAb aggregates generated by subjecting to specific stress conditions. The ANN was trained using Levenberg-Marquardt algorithm with Bayesian regularization, using 86 sensogram profiles, in the ratio of 80:10:10 for internal training, validation, and testing. The trained ANN accurately identified each single stress condition that the samples were subjected to based on their binding sensogram profiles. The model was also able to predict stress history for samples that had been subjected to more than one kind of stress with reasonable accuracy. The proposed approach therefore can be effectively employed for control of product quality in biopharmaceutical industry as well as for prediction of stress history of a sample.

Understanding the mechanism of copurification of "difficult to remove" host cell proteins in rituximab biosimilar products.

Host cell proteins (HCPs) are considered a critical quality attribute and are linked to safety and efficacy of biotherapeutic products. Researchers have identified 10 HCPs in Chinese hamster ovary (CHO) that exhibit common characteristics of product association, coelution, and age-dependent expression and therefore are "difficult to remove" during downstream purification. These include cathepsin D, clusterin, galectin-3-binding protein, G-protein coupled receptor 56, lipoprotein lipase, metalloproteinase inhibitor, nidogen-1 secreted protein acidic and rich in cysteine (SPARC), sulfated glycoprotein, and insulin-like growth factor-2 RNA-binding protein. While the levels of HCPs in the investigated biosimilars were within the acceptable range of <100 ppm, certain "difficult to remove" HCPs were found in the biosimilar samples. This article aims to elucidate the underlying interactions between these "difficult to remove" HCPs and the mAb product. Surface study of rituximab exhibited unstable discontinuous patches of residues on the protein surface that have high propensity to get buried and lower the solvent exposed area. The higher order structure and the receptor binding were not affected, except for one of the biosimilars, owing to extremely low-HCP levels in its final drug product. Finally, based on the combined experimental and computational data from this study, a probable mechanism of retention for the 10 HCPs is proposed. The results presented here can guide downstream process design or avenues for protein engineering during product discovery to achieve more effective removal of the impurities.