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.

A Novel, Site-Specific N-Linked Glycosylation Model Provides Mechanistic Insights Into the Process-Condition Dependent Distinct Fab and Fc Glycosylation of an IgG1 Monoclonal Antibody Produced by CHO VRC01 Cells

The CHO VRC01 cell line produces an anti-HIV IgG1 monoclonal antibody containing N-linked glycans on both the Fab (variable) and Fc (constant) regions. Site-specific glycan analysis was used to measure the complex effects of cell culture process conditions on Fab and Fc glycosylation. Experimental data revealed major differences in glycan fractions across the two sites. Bioreactor pH was found to influence fucosylation, galactosylation, and sialylation in the Fab region and galactosylation in the Fc region. To understand the complex effects of process conditions on site-specific N-linked glycosylation, a kinetic model of site-specific N-linked glycosylation was developed. The model parameters provided mechanistic insights into the differences in glycan fractions observed in the Fc and Fab regions. Enzyme activities calculated from the model provided insights into the effect of bioreactor pH on site-specific N-linked glycosylation. Model predictions were experimentally tested by measuring glycosyltransferase-enzyme mRNA-levels and intracellular nucleotide sugar concentrations. The model was used to demonstrate the effect of increasing galactosyltransferase activity on site-specific N-linked glycan fractions. Experiments involving galactose and MnCl2 supplementation were used to test model predictions. The model is capable of providing insights into experimentally measured data and also of making predictions that can be used to design media supplementation strategies.

Perfusion Process Intensification for Lentivirus Production Using a Novel Scale-Down Model

Process intensification has become an important strategy to lower production costs and increase manufacturing capacities for biopharmaceutical products. In particular for the production of viral vectors like lentiviruses (LVs), the transition from (fed-)batch to perfusion processes is a key strategy to meet the increasing demands for cell and gene therapy applications. However, perfusion processes are associated with higher medium consumption. Therefore, it is necessary to develop appropriate small-scale models to reduce development costs. In this work, we present the use of the acoustic wave separation technology in combination with the Ambr 250 high throughput bioreactor system for intensified perfusion process development using stable LV producer cells. The intensified perfusion process developed in the Ambr 250 model, performed at a harvest rate of 3 vessel volumes per day (VVD) and high cell densities, resulted in a 1.4-fold higher cell-specific functional virus yield and 2.8-fold higher volumetric virus yield compared to the control process at a harvest rate of 1 VVD. The findings were verified at bench scale after optimizing the bioreactor set-up, resulting in a 1.4-fold higher cell-specific functional virus yield and 3.1-fold higher volumetric virus yield.

Flux balance analysis and peptide mapping elucidate the impact of bioreactor pH on Chinese hamster ovary (CHO) cell metabolism and N-linked glycosylation in the fab and Fc regions of the produced IgG

Culture conditions have a profound impact on therapeutic protein production and glycosylation, a critical therapeutic-quality attribute, especially for monoclonal antibodies (mAbs). While the critical culture parameter of pH has been known since the early 1990s to affect protein glycosylation and production, detailed glycan and metabolic characterization and mechanistic understanding are critically lacking. Here, Chinese Hamster Ovary (CHO) cells were grown in bioreactors at pH 6.75, 7, and 7.25 (± 0.03) to examine how pH affects cell metabolism and site-specific N-linked glycosylation of the produced broadly neutralizing anti-HIV IgG1 mAb. VRC01 has N-linked glycosylation sites in both the Fc region and the Fab region, a situation not previously examined with respect to mAb glycosylation as affected by culture conditions. Using parsimonious Flux Balance Analysis (pFBA) and Flux Variability Analysis (FVA), we dissect and quantitate the impact of pH on cell growth, glucose/lactate metabolism, accumulation of the toxic metabolite ammonia, IgG production rates, and nonessential amino acid metabolism. pFBA revealed that beyond the established mechanism of glutamine conversion to glutamate, ammonia is also produced by the reaction converting serine to pyruvate, especially in the later phases of culture. pFBA also provided insights into the switch from ammonia production to consumption, notably due to depletion of glutamine, and consumption of glutamate and aspartate. We document that culture duration and pH alter the complex bimodal patterns (production/uptake) of several essential and non-essential amino acids. Site-specific N-linked glycan analysis using glycopeptide mapping demonstrated that pH significantly affects the glycosylation profiles of the two IgG1 sites. Fc region glycans were completely fucosylated but did not contain any sialylation. The Fab region glycans were not completely fucosylated but contained sialylated glycans. Bioreactor pH affected both the fucosylation and sialylation indexes in the Fab region and the galactosylation index of the Fc region. However, fucosylation in the Fc region was unaffected thus demonstrating that the effect of pH on site-specific N-linked glycosylation is complex.

Modulating antibody N-glycosylation through feed additives using a multi-tiered approach

Glycosylation of recombinant proteins is a post-translational modification that affects multiple physicochemical and biological properties of proteins. As such, it is a critical quality attribute that must be carefully controlled during protein production in the pharmaceutical industry. Glycosylation can be modulated by various conditions, including the composition of production media and feeds. In this study, the N-glycosylation-modulating effects of numerous compounds, including metal enzyme cofactors, enzyme inhibitors, and metabolic intermediates, were evaluated. Chinese hamster ovary cells producing three different IgG antibodies were cultivated in a fed-batch mode. First, a one-factor-at-a-time experiment was performed in 24-well deep well plates to identify the strongest modulators and appropriate concentration ranges. Then, a full response surface experiment was designed to gauge the effects and interactions of the 14 most effective hit compounds in an Ambr® 15 bioreactor system. A wide range of glycoform content was achieved, with an up to eight-fold increase in individual glycoforms compared to controls. The resulting model can be used to determine modulator combinations that will yield desired glycoforms in the final product.

Continuous multi-column capture of monoclonal antibodies with convective diffusive membrane adsorbers

Downstream processing is the bottleneck in the continuous manufacturing of monoclonal antibodies (mAbs). To overcome throughput limitations, two different continuous processes with a novel convective diffusive protein A membrane adsorber (MA) were investigated: the rapid cycling parallel multi-column chromatography (RC-PMCC) process and the rapid cycling simulated moving bed (RC-BioSMB) process. First, breakthrough curve experiments were performed to investigate the influence of the flow rate on the mAb dynamic binding capacity and to calculate the duration of the loading steps. In addition, customized control software was developed for an automated MA exchange in case of pressure increase due to membrane fouling to enable robust, uninterrupted, and continuous processing. Both processes were performed for 4 days with 0.61 g L-1 mAb-containing filtrate and process performance, product purity, productivity, and buffer consumption were compared. The mAb was recovered with a yield of approximately 90% and productivities of 1010 g L-1 d-1 (RC-PMCC) and 574 g L-1 d-1 (RC-BioSMB). At the same time, high removal of process-related impurities was achieved with both processes, whereas the buffer consumption was lower for the RC-BioSMB process. Finally, the attainable productivity for perfusion bioreactors of different sizes with suitable MA sizes was calculated to demonstrate the potential to operate both processes on a manufacturing scale with bioreactor volumes of up to 2000 L.

An innovative hybrid modeling approach for simultaneous prediction of cell culture process dynamics and product quality

The use of hybrid models is extensively described in the literature to predict the process evolution in cell cultures. These models combine mechanistic and machine learning methods, allowing the prediction of complex process behavior, in the presence of many process variables, without the need to collect a large amount of data. Hybrid models cannot be directly used to predict final product critical quality attributes, or CQAs, because they are usually measured only at the end of the process, and more mechanistic knowledge is needed for many classes of CQAs. The historical models can instead predict the CQAs better; however, they cannot directly relate manipulated process parameters to final CQAs, as they require knowledge of the process evolution. In this work, we propose an innovative modeling approach based on combining a hybrid propagation model with a historical data-driven model, that is, the combined hybrid model, for simultaneous prediction of full process dynamics and CQAs. The performance of the combined hybrid model was evaluated on an industrial dataset and compared to classical black-box models, which directly relate manipulated process parameters to CQAs. The proposed combined hybrid model outperforms the black-box model by 33% on average in predicting the CQAs while requiring only around half of the data for model training to match performance. Thus, in terms of model accuracy and experimental costs, the combined hybrid model in this study provides a promising platform for process optimization applications.

Model-based control system design to manage process parameters in mammalian cell culture for biopharmaceutical manufacturing

To enhance the robustness and flexibility of biopharmaceutical manufacturing, a paradigm shift toward methods of continuous processing, such as perfusion, and fundamental technologies for high-throughput process development are being actively investigated. The continuous upstream process must establish an advanced control strategy to ensure a "State of Control" before operation. Specifically, feedforward and feedback control must address the complex fluctuations that occur during the culture process and maintain critical process parameters in appropriate states. However, control system design for industry-standard mammalian cell culture processes is still often performed in a laborious trial-and-error manner. This paper provides a novel control approach in which controller specifications to obtain desired control characteristics can be determined systematically by combining a culture model with control theory. In the proposed scheme, control conditions, such as PID parameters, can be specified mechanistically based on process understanding and control requirements without qualitative decision making or specific preliminary experiments. The effectiveness of the model-based control algorithm was verified by control simulations assuming perfusion Chinese hamster ovary culture. As a tool to assist in the development of control strategies, this study will reduce the high operational workload that is a serious problem in continuous culture and facilitate the digitalization of bioprocesses.

Current challenges and recent advances on the path towards continuous biomanufacturing

Continuous biopharmaceutical manufacturing is currently a field of intense research due to its potential to make the entire production process more optimal for the modern, ever-evolving biopharmaceutical market. Compared to traditional batch manufacturing, continuous bioprocessing is more efficient, adjustable, and sustainable and has reduced capital costs. However, despite its clear advantages, continuous bioprocessing is yet to be widely adopted in commercial manufacturing. This article provides an overview of the technological roadblocks for extensive adoptions and points out the recent advances that could help overcome them. In total, three key areas for improvement are identified: Quality by Design (QbD) implementation, integration of upstream and downstream technologies, and data and knowledge management. First, the challenges to QbD implementation are explored. Specifically, process control, process analytical technology (PAT), critical process parameter (CPP) identification, and mathematical models for bioprocess control and design are recognized as crucial for successful QbD realizations. Next, the difficulties of end-to-end process integration are examined, with a particular emphasis on downstream processing. Finally, the problem of data and knowledge management and its potential solutions are outlined where ontologies and data standards are pointed out as key drivers of progress.

Cell-culture process optimization via model-based predictions of metabolism and protein glycosylation

In order to meet the rising demand for biologics and become competitive on the developing biosimilar market, there is a need for process intensification of biomanufacturing processes. Process development of biologics has historically relied on extensive experimentation to develop and optimize biopharmaceutical manufacturing. Experimentation to optimize media formulations, feeding schedules, bioreactor operations and bioreactor scale up is expensive, labor intensive and time consuming. Mathematical modeling frameworks have the potential to enable process intensification while reducing the experimental burden. This review focuses on mathematical modeling of cellular metabolism and N-linked glycosylation as applied to upstream manufacturing of biologics. We review developments in the field of modeling cellular metabolism of mammalian cells using kinetic and stoichiometric modeling frameworks along with their applications to simulate, optimize and improve mechanistic understanding of the process. Interest in modeling N-linked glycosylation has led to the creation of various types of parametric and non-parametric models. Most published studies on mammalian cell metabolism have performed experiments in shake flasks where the pH and dissolved oxygen cannot be controlled. Efforts to understand and model the effect of bioreactor-specific parameters such as pH, dissolved oxygen, temperature, and bioreactor heterogeneity are critically reviewed. Most modeling efforts have focused on the Chinese Hamster Ovary (CHO) cells, which are most commonly used to produce monoclonal antibodies (mAbs). However, these modeling approaches can be generalized and applied to any mammalian cell-based manufacturing platform. Current and potential future applications of these models for Vero cell-based vaccine manufacturing, CAR-T cell therapies, and viral vector manufacturing are also discussed. We offer specific recommendations for improving the applicability of these models to industrially relevant processes.

Establishment of a Perfusion Process with Antibody-Producing CHO Cells Using a 3D-Printed Microfluidic Spiral Separator with Web-Based Flow Control

Monoclonal antibodies are increasingly dominating the market for human therapeutic and diagnostic agents. For this reason, continuous methods-such as perfusion processes-are being explored and optimized in an ongoing effort to increase product yields. Unfortunately, many established cell retention devices-such as tangential flow filtration-rely on membranes that are prone to clogging, fouling, and undesirable product retention at high cell densities. To circumvent these problems, in this work, we have developed a 3D-printed microfluidic spiral separator for cell retention, which can readily be adapted and replaced according to process conditions (i.e., a plug-and-play system) due to the fast and flexible 3D printing technique. In addition, this system was also expanded to include automatic flushing, web-based control, and notification via a cellphone application. This set-up constitutes a proof of concept that was successful at inducing a stable process operation at a viable cell concentration of 10-17 × 106 cells/mL in a hybrid mode (with alternating cell retention and cell bleed phases) while significantly reducing both shear stress and channel blockage. In addition to increasing efficiency to nearly 100%, this microfluidic device also improved production conditions by successfully separating dead cells and cell debris and increasing cell viability within the bioreactor.

Innovative Metrics for Reporting and Comparing the Glycan Structural Profile in Biotherapeutics

Glycosylation is a critical quality attribute in biotherapeutics, impacting properties such as protein stability, solubility, clearance rate, efficacy, immunogenicity, and safety. Due to the heterogenic and complex nature of protein glycosylation, comprehensive characterization is demanding. Moreover, the lack of standardized metrics for evaluating and comparing glycosylation profiles hinders comparability studies and the establishment of manufacturing control strategies. To address both challenges, we propose a standardized approach based on novel metrics for a comprehensive glycosylation fingerprint which greatly facilitates the reporting and objective comparison of glycosylation profiles. The analytical workflow is based on a liquid chromatography-mass spectrometry-based multi-attribute method. Based on the analytical data, a matrix of glycosylation-related quality attributes, both at site-specific and whole molecule level, are computed, which provide metrics for a comprehensive product glycosylation fingerprint. Two case studies illustrate the applicability of the proposed indices as a standardized and versatile approach for reporting all dimensions of the glycosylation profile. The proposed approach further facilitates the assessments of risks associated with changes in the glycosylation profile that may affect efficacy, clearance, and immunogenicity.

Perfusion culture of Chinese Hamster Ovary cells for bioprocessing applications

Much of the biopharmaceutical industry's success over the past 30 years has relied on products derived from Chinese Hamster Ovary (CHO) cell lines. During this time, improvements in mammalian cell cultures have come from cell line development and process optimization suited for large-scale fed-batch processes. Originally developed for high cell densities and sensitive products, perfusion processes have a long history. Driven by high volumetric titers and a small footprint, perfusion-based bioprocess research has regained an interest from academia and industry. The recent pandemic has further highlighted the need for such intensified biomanufacturing options. In this review, we outline the technical history of research in this field as it applies to biologics production in CHO cells. We demonstrate a number of emerging trends in the literature and corroborate these with underlying drivers in the commercial space. From these trends, we speculate that the future of perfusion bioprocesses is bright and that the fields of media optimization, continuous processing, and cell line engineering hold the greatest potential. Aligning in its continuous setup with the demands for Industry 4.0, perfusion biomanufacturing is likely to be a hot topic in the years to come.

Towards rational glyco-engineering in CHO: from data to predictive models

Metabolic modelling strives to develop modelling approaches that are robust and highly predictive. To achieve this, various modelling designs, including hybrid models, and parameter estimation methods that define the type and number of parameters used in the model, are adapted. Accurate input data play an important role so that the selection of experimental methods that provide input data of the required precision with low measurement errors is crucial. For the biopharmaceutically relevant protein glycosylation, the most prominent available models are kinetic models which are able to capture the dynamic nature of protein N-glycosylation. In this review we focus on how to choose the most suitable model for a specific research question, as well as on parameters and considerations to take into account before planning relevant experiments.

Probabilistic model by Bayesian network for the prediction of antibody glycosylation in perfusion and fed-batch cell cultures

Glycosylation is a critical quality attribute of therapeutic monoclonal antibodies (mAbs). The glycan pattern can have a large impact on the immunological functions, serum half-life and stability. The medium components and cultivation parameters are known to potentially influence the glycosylation profile. Mathematical modelling provides a strategy for rational design and control of the upstream bioprocess. However, the kinetic models usually contain a very large number of unknown parameters, which limit their practical applications. In this article, we consider the metabolic network of N-linked glycosylation as a Bayesian network (BN) and calculate the fluxes of the glycosylation process as joint probability using the culture parameters as inputs. The modelling approach is validated with data of different Chinese hamster ovary cell cultures in pseudo perfusion, perfusion, and fed batch cultures, all showing very good predictive capacities. In cases where a large number of cultivation parameters is available, it is shown here that principal components analysis can efficiently be employed for a dimension reduction of the inputs compared to Pearson correlation analysis and feature importance by decision tree. The present study demonstrates that BN model can be a powerful tool in upstream process and medium development for glycoprotein productions.

Developments and opportunities in continuous biopharmaceutical manufacturing

Today's biologics manufacturing practices incur high costs to the drug makers, which can contribute to high prices for patients. Timely investment in the development and implementation of continuous biomanufacturing can increase the production of consistent-quality drugs at a lower cost and a faster pace, to meet growing demand. Efficient use of equipment, manufacturing footprint, and labor also offer the potential to improve drug accessibility. Although technological efforts enabling continuous biomanufacturing have commenced, challenges remain in the integration, monitoring, and control of traditionally segmented unit operations. Here, we discuss recent developments supporting the implementation of continuous biomanufacturing, along with their benefits.

Control of IgG glycosylation in CHO cell perfusion cultures by GReBA mathematical model supported by a novel targeted feed, TAFE

The N-linked glycosylation pattern is an important quality attribute of therapeutic glycoproteins. It has been reported by our group and by others that different carbon sources, such as glucose, mannose and galactose, can differently impact the glycosylation profile of glycoproteins in mammalian cell culture. Acting on the sugar feeding is thus an attractive strategy to tune the glycan pattern. However, in case of feeding of more than one carbon source simultaneously, the cells give priority to the one with the highest uptake rate, which limits the usage of this tuning, e.g. the cells favor consuming glucose in comparison to galactose. We present here a new feeding strategy (named 'TAFE' for targeted feeding) for perfusion culture to adjust the concentrations of fed sugars influencing the glycosylation. The strategy consists in setting the sugar feeding such that the cells are forced to consume these substrates at a target cell specific consumption rate decided by the operator and taking into account the cell specific perfusion rate (CSPR). This strategy is applied in perfusion cultures of Chinese hamster ovary (CHO) cells, illustrated by ten different regimes of sugar feeding, including glucose, galactose and mannose. Applying the TAFE strategy, different glycan profiles were obtained using the different feeding regimes. Furthermore, we successfully forced the cells to consume higher proportions of non-glucose sugars, which have lower transport rates than glucose in presence of this latter, in a controlled way. In previous work, a mathematical model named Glycan Residues Balance Analysis (GReBA) was developed to model the glycosylation profile based on the fed carbon sources. The present data were applied to the GReBA to design a feeding regime targeting a given glycosylation profile. The ability of the model to achieve this objective was confirmed by a multi-round of leave-one-out cross-validation (LOOCV), leading to the conclusion that the GReBA model can be used to design the feeding regime of a perfusion cell culture to obtain a desired glycosylation profile.

Traces matter: Targeted optimization of monoclonal antibody N-glycosylation based on/by implementing automated high-throughput trace element screening

The use of high-throughput systems in cell culture process optimization offers various opportunities in biopharmaceutical process development. Here we describe the potential for acceleration and enhancement of product quality optimization and de novo bioprocess design regarding monoclonal antibody N-glycosylation by using an iterative statistical Design of Experiments (DoE) strategy based on our automated microtiter plate-based system for suspension cell culture. In our example, the combination of an initial screening of trace metal building blocks with a comprehensive DoE-based screening of 13 different trace elemental ions at three concentration levels in one run revealed most effective levers for N-glycan processing and biomass formation. Obtained results served to evaluate optimal concentration ranges and the right supplementation timing of relevant trace elements at shake flask and 2 L bioreactor scale. This setup identified manganese, copper, zinc, and iron as major factors. Manganese and copper acted as inverse key players in N-glycosylation, showing a positive effect of manganese and a negative effect of copper on glycan maturation in a zinc-dependent manner. Zinc and iron similarly improved cell growth and biomass formation. These findings allowed determining optimal concentration ranges for all four trace elements to establish control on desired product quality attributes regarding premature afucosylated and mature galactosylated glycan species. Our results demonstrates the power of combining robotics with DoE screening to enhance product quality optimization and to improve process understanding, thus, enabling targeted product quality control.

Reduction of medium consumption in perfusion mammalian cell cultures using a perfusion rate equivalent concentrated nutrient feed

Media preparation for perfusion cell culture processes contributes significantly to operational costs and the footprint of continuous operations for therapeutic protein manufacturing. In this study, definitions are given for the use of a perfusion equivalent nutrient feed stream which, when used in combination with basal perfusion medium, supplements the culture with targeted compounds and increases the medium depth. Definitions to compare medium and feed depth are given in this article. Using a concentrated nutrient feed, a 1.8-fold medium consumption (MC) decrease and a 1.67-fold increase in volumetric productivity (PR) were achieved compared to the initial condition. Later, this strategy was used to push cell densities above 100 × 10⁶ cells/ml while using a perfusion rate below 2 RV/day. In this example, MC was also decreased 1.8-fold compared to the initial condition, but due to the higher cell density, PR was increased 3.1-fold and to an average PR value of 1.36 g L^-1  day^-1 during a short stable phase, and versus 0.46 g L^-1  day^-1 in the initial condition. Overall, the performance improvements were aligned with the given definitions. This multiple feeding strategy can be applied to gain some flexibility during process development and also in a manufacturing set-up to enable better control on nutrient addition.

N-Glycosylation of IgG and IgG-Like Recombinant Therapeutic Proteins: Why Is It Important and How Can We Control It?

Regulatory bodies worldwide consider N-glycosylation to be a critical quality attribute for immunoglobulin G (IgG) and IgG-like therapeutics. This consideration is due to the importance of posttranslational modifications in determining the efficacy, safety, and pharmacokinetic properties of biologics. Given its critical role in protein therapeutic production, we review N-glycosylation beginning with an overview of the myriad interactions of N-glycans with other biological factors. We examine the mechanism and drivers for N-glycosylation during biotherapeutic production and the several competing factors that impact glycan formation, including the abundance of precursor nucleotide sugars, transporters, glycosidases, glycosyltransferases, and process conditions. We explore the role of these factors with a focus on the analytical approaches used to characterize glycosylation and associated processes, followed by the current state of advanced glycosylation modeling techniques. This combination of disciplines allows for a deeper understanding of N-glycosylation and will lead to more rational glycan control.

Harnessing the potential of artificial neural networks for predicting protein glycosylation

Kinetic models offer incomparable insight on cellular mechanisms controlling protein glycosylation. However, their ability to reproduce site-specific glycoform distributions depends on accurate estimation of a large number of protein-specific kinetic parameters and prior knowledge of enzyme and transport protein levels in the Golgi membrane. Herein we propose an artificial neural network (ANN) for protein glycosylation and apply this to four recombinant glycoproteins produced in Chinese hamster ovary (CHO) cells, two monoclonal antibodies and two fusion proteins. We demonstrate that the ANN model accurately predicts site-specific glycoform distributions of up to eighteen glycan species with an average absolute error of 1.1%, correctly reproducing the effect of metabolic perturbations as part of a hybrid, kinetic/ANN, glycosylation model (HyGlycoM), as well as the impact of manganese supplementation and glycosyltransferase knock out experiments as a stand-alone machine learning algorithm. These results showcase the potential of machine learning and hybrid approaches for rapidly developing performance-driven models of protein glycosylation.

Truly continuous low pH viral inactivation for biopharmaceutical process integration

Continuous virus inactivation (VI) has received little attention in the efforts to realize fully continuous biomanufacturing in the future. Implementation of continuous VI must assure a specific minimum incubation time, typically 60 min. To guarantee the minimum incubation time, we implemented a packed bed continuous viral inactivation reactor (CVIR) with narrow residence time distribution (RTD) for low pH incubation. We show that the RTD does not broaden significantly over a wide range of linear flow velocities-which highlights the flexibility and robustness of the design. Prolonged exposure to acidic pH has no impact on bed stability, assuring constant RTD throughout long term operation. The suitability of the packed bed CVIR for low pH inactivation is shown with two industry-standard model viruses, that is xenotropic murine leukemia virus and pseudorabies virus. Controls at neutral pH showed no system-induced VI. At low pH, significant VI is observed, even after only 15 min. Based on the low pH inactivation kinetics, the continuous process is equivalent to traditional batch operation. This study establishes a concept for continuous low pH inactivation and, together with previous reports, highlights the versatility of the packed bed reactor for continuous VI, regardless of the inactivation method.

Interaction analysis of glycoengineered antibodies with CD16a: a native mass spectrometry approach

Minor changes in the quality of biologically manufactured monoclonal antibodies (mAbs) can affect their bioactivity and efficacy. One of the most important variations concerns the N-glycosylation pattern, which directly affects an anti-tumor mechanism called antibody-dependent cell-meditated cytotoxicity (ADCC). Thus, careful engineering of mAbs is expected to enhance both protein-receptor binding and ADCC. The specific aim of this study is to evaluate the influence of terminal carbohydrates within the Fc region on the interaction with the FcγRIIIa/CD16a receptor in native and label-free conditions. The single mAb molecule comprises variants with minimal and maximal galactosylation, as well as α2,3 and α2,6-sialic acid isomers. Here, we apply native electrospray ionization mass spectrometry to determine the solution-phase antibody-receptor equilibria and by using temperature-controlled nanoelectrospray, a thermal stability of the complex is examined. Based on these, we prove that the galactosylation of a fucosylated Fc region increases the binding to CD16a 1.5-fold when compared with the non-galactosylated variant. The α2,6-sialylation has no significant effect on the binding, whereas the α2,3-sialylation decreases it 1.72-fold. In line with expectation, the galactoslylated and α2,6-sialylated mAb:CD16a complex exhibit higher thermal stability when measured in the temperature gradient from 20 to 50°C. The similar binding pattern is observed based on surface plasmon resonance analysis and immunofluorescence staining using natural killer cells. The results of our study provide new insight into N-glycosylation-based interaction of the mAb:CD16a complex.

Glycan Residues Balance Analysis - GReBA: A novel model for the N-linked glycosylation of IgG produced by CHO cells

The structure of N-linked glycosylation is a very important quality attribute for therapeutic monoclonal antibodies. Different carbon sources in cell culture media, such as mannose and galactose, have been reported to have different influences on the glycosylation patterns. Accurate prediction and control of the glycosylation profile are important for the process development of mammalian cell cultures. In this study, a mathematical model, that we named Glycan Residues Balance Analysis (GReBA), was developed based on the concept of Elementary Flux Mode (EFM), and used to predict the glycosylation profile for steady state cell cultures. Experiments were carried out in pseudo-perfusion cultivation of antibody producing Chinese Hamster Ovary (CHO) cells with various concentrations and combinations of glucose, mannose and galactose. Cultivation of CHO cells with mannose or the combinations of mannose and galactose resulted in decreased lactate and ammonium production, and more matured glycosylation patterns compared to the cultures with glucose. Furthermore, the growth rate and IgG productivity were similar in all the conditions. When the cells were cultured with galactose alone, lactate was fed as well to be used as complementary carbon source, leading to cell growth rate and IgG productivity comparable to feeding the other sugars. The data of the glycoprofiles were used for training the model, and then to simulate the glycosylation changes with varying the concentrations of mannose and galactose. In this study we showed that the GReBA model had a good predictive capacity of the N-linked glycosylation. The GReBA can be used as a guidance for development of glycoprotein cultivation processes.

Consequences of trace metal variability and supplementation on Chinese hamster ovary (CHO) cell culture performance: A review of key mechanisms and considerations

Trace metals are supplied to chemically-defined media (CDM) for optimal Chinese hamster ovary (CHO) cell culture performance during the production of monoclonal antibodies and other therapeutic proteins. However, lot-to-lot and vendor-to-vendor variability in raw materials consequently leads to an imbalance of trace metals that are supplied to CDM. This imbalance can yield detrimental effects rooted in several primary mechanisms and pathways including oxidative stress, apoptosis, lactate accumulation, and unfavorable glycan synthesis. Recent research endeavors involve supplying zinc, copper, and manganese to CDM in excess to further maximize culture productivity and product quality. These treatments significantly impact critical quality attributes and furthermore highlight the degree to which trace metal availability can affect CHO cell culture performance. This review highlights the role of trace metal variability, supplementation, and interplay on key cellular mechanisms responsible for overall culture performance and the production and quality of therapeutic proteins.

Monitoring of antibody glycosylation pattern based on microarray MALDI-TOF mass spectrometry

Biologically manufactured monoclonal antibodies (mAb) can strongly vary in their efficacy and affinity. Therefore, engineering and production of the mAb is highly regulated and requires product monitoring, especially in terms of N-glycosylation patterns. In this work, we present a high-throughput matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) method based on a microarray technology to monitor N-glycopeptides of IgG1 produced in a perfusion cell culture. A bottom-up approach combined with zwitterionic-hydrophilic interaction liquid chromatography for sample purification was used to determine the day-by-day variation of the terminal galactose within two major N-glycoforms. Our results show that microarrays for mass spectrometry (MAMS) are a robust platform for the rapid determination of the carbohydrate distribution. The spectral repeatability is characterized by a low coefficient of variations (1.7% and 7.1% for the FA2 and FA2G1 structures, respectively) and allows to detect the N-glycosylation variability resulting from operating conditions during the bioreactor process. The observed trend of released N-glycans was confirmed using capillary gel electrophoresis with laser-induced fluorescence detection. Therefore, the microarray technology is a promising analytical tool for glycosylation control during the production process of recombinant proteins.

Transcriptome and proteome analysis of steady-state in a perfusion CHO cell culture process

Long-term continuous protein production can be reached by perfusion operation. Through the continuous removal of waste metabolites and supply of nutrients, steady-state (SS) conditions are achieved after a certain transient period, where the conditions inside the reactor are not only uniform in space but also constant in time. Such stable conditions may have beneficial influences on the reduction of product heterogeneities. In this study, we investigated the impact of perfusion cultivation on the intracellular physiological state of a CHO cell line producing a monoclonal antibody (mAb) by global transcriptomics and proteomics. Despite stable viable cell density was maintained right from the beginning of the cultivation time, productivity decrease, and a transition phase for metabolites and product quality was observed before reaching SS conditions. These were traced back to three sources of transient behaviors being hydrodynamic flow rates, intracellular dynamics of gene expression as well as metabolism and cell line instability, superimposing each other. However, 99.4% of all transcripts and proteins reached SS during the first week or were at SS from the beginning. These results demonstrate that the stable extracellular conditions of perfusion lead to SS also of the cellular level.

Isotope labeling to determine the dynamics of metabolic response in CHO cell perfusion bioreactors using MALDI-TOF-MS

The steady-state operation of Chinese hamster ovary (CHO) cells in perfusion bioreactors requires the equilibration of reactor dynamics and cell metabolism. Accordingly, in this work we investigate the transient cellular response to changes in its environment and their interactions with the bioreactor hydrodynamics. This is done in a benchtop perfusion bioreactor using MALDI-TOF MS through isotope labeling of complex intracellular nucleotides (ATP, UTP) and nucleotide sugars (UDP-Hex, UDP-HexNAc). By switching to a ¹³ C₆ glucose containing feed media during constant operation at 20 × 10⁶ cells and a perfusion rate of 1 reactor volume per day, isotopic steady state was studied. A step change to the ¹³ C₆ glucose medium in spin tubes allowed the determination of characteristic times for the intracellular turnover of unlabeled metabolites pools, τST (≤0.56 days), which were confirmed in the bioreactor. On the other hand, it is shown that the reactor residence time τR (1 day) and characteristic time for glucose uptake τGlc (0.33 days), representative of the bioreactor dynamics, delayed the consumption of ¹³ C₆ glucose in the bioreactor and thus the intracellular ¹³ C enrichment. The proposed experimental approach allowed the decoupling of bioreactor hydrodynamics and intrinsic dynamics of cell metabolism in response to a change in the cell culture environment. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:1630-1639, 2017.