Extensive knowledge of Chinese hamster ovary (CHO) cell metabolism is required to improve process productivity and culture performance in biopharmaceutical manufacturing. However, CHO cells show a dynamic metabolism during culturing in batch and fed-batch bioreactors. CHO cell metabolism is generally described as taking place in three stages: exponential growth phase, stationary phase, and death phase. This review aims to summarize the trends of central metabolism for CHO cells during each stage. Additional insights into how culture conditions are related to phase transitions and force metabolic rewiring are provided. Understanding of CHO cell metabolism lends itself to improving culture qualities by, for example, identifying sources of toxic byproducts and pathways for cellular engineering. In summary, this review describes the changes in CHO cell central metabolism over the course of the culture.

The biopharmaceutical industry prefers to culture the mammalian cells in suspension with a serum-free media (SFM) due to improved productivity and process consistency. However, mammalian cells preferentially grow as adherent cells in a complete medium (CM) containing serum. Therefore, cells require adaptation from adherence in CM to suspension culture in SFM. This work proposes an adaptation method that includes media supplementation during the adaption of Chinese hamster ovary cells.As a result, the adaptation was accelerated compared to the traditional repetitive subculturing. Ca 2+ /Mg 2+ supplementation significantly reduced the doubling time compared to the adaptation without supplementation during the adaptation of adherent cells from 100% CM to 75% CM (p < 0.05). Furthermore, a definitive screening design (DSD) was applied to select essential nutrients during the adaptation from 10% CM to 0% CM. The main effects of Ca 2+ and Dulbecco's modified essential medium (DMEM) were found significant to both viable cell density and viability at harvest. Additionally, the interaction term between Ca 2+ and DMEM was found significant, which highlights the ability of DSD to capture interaction terms. Eventually, the media supplementation method resulted in adaptation SFM in 27 days, compared to the previously reported 66 days. Additionally, the membrane surface integrin expression was found significantly decreased when adherent cells were adapted to suspension. Moreover, the Ca 2+ /Mg 2+ supplementation correlated with faster integrin recovery after trypsinization. However, faster integrin recovery did not contribute to the accelerated cell growth when subculturing from 100% CM to 75% CM.

Core fucosylation is a highly prevalent and significant feature of N-glycosylation in therapeutic monoclonal antibodies produced by mammalian cells where its absence (afucosylation) plays a key role in treatment safety and efficacy. Notably, even slight changes in the level of afucosylation can have a considerable impact on the antibody-dependent cell-mediated cytotoxicity. Therefore, implementing control over afucosylation levels is important in upstream manufacturing to maintain consistent quality across batches of product, since standard downstream processing does not change afucosylation. In this review, the influences and strategies to control afucosylation are presented. In particular, there is emphasis on upstream manufacturing culture parameters and media supplementation, as these offer particular advantages as control strategies over alternative approaches such as cell line engineering and chemical inhibitors. The review discusses the relationship between the afucosylation influences and the underlying cellular metabolism to promote increased process understanding. Also, briefly highlighted is the value of empirical and mechanistic models in evaluating and designing control methods for core fucosylation.

Retrospective analysis of historic data for cell culture processes is a powerful tool to develop further process understanding. In particular, deploying retrospective analyses can identify important cell culture process parameters for controlling critical quality attributes, e.g., afucosylation, for the production of monoclonal antibodies (mAbs). However, a challenge of analyzing large cell culture data is the high correlation between regressors (particularly media composition), which makes traditional analyses, such as analysis of variance and multivariate linear regression, inappropriate. Instead, partial least-squares regression (PLSR) models, in combination with machine learning techniques such as variable importance metrics, are an orthogonal or alternative approach to identifying important regressors and overcoming the challenge of a highly covariant data structure. A specific workflow for the retrospective analysis of cell culture data is proposed that covers data curation, PLS regression, model analysis, and further steps. In this study, the proposed workflow was applied to data from four mAb products in an industrial cell culture process to identify significant process parameters that influence the afucosylation levels. The PLSR workflow successfully identified several significant parameters, such as temperature and media composition, to enhance process understanding of the relationship between cell culture processes and afucosylation levels.