Automated dynamic fed‐batch process and media optimization for high productivity cell culture process development

Current industry practices for large‐scale mammalian cell cultures typically employ a standard platform fed‐batch process with fixed volume bolus feeding. Although widely used, these processes are unable to respond to actual nutrient consumption demands from the culture, which can result in accumulation of by‐products and depletion of certain nutrients. This work demonstrates the application of a fully automated cell culture control, monitoring, and data processing system to achieve significant productivity improvement via dynamic feeding and media optimization. Two distinct feeding algorithms were used to dynamically alter feed rates. The first method is based upon on‐line capacitance measurements where cultures were fed based on growth and nutrient consumption rates estimated from integrated capacitance. The second method is based upon automated glucose measurements obtained from the Nova Bioprofile FLEX® autosampler where cultures were fed to maintain a target glucose level which in turn maintained other nutrients based on a stoichiometric ratio. All of the calculations were done automatically through in‐house integration with a Delta V process control system. Through both media and feed strategy optimization, a titer increase from the original platform titer of 5 to 6.3 g/L was achieved for cell line A, and a substantial titer increase of 4 to over 9 g/L was achieved for cell line B with comparable product quality. Glucose was found to be the best feed indicator, but not all cell lines benefited from dynamic feeding and optimized feed media was critical to process improvement. Our work demonstrated that dynamic feeding has the ability to automatically adjust feed rates according to culture behavior, and that the advantage can be best realized during early and rapid process development stages where different cell lines or large changes in culture conditions might lead to dramatically different nutrient demands. Biotechnol. Bioeng. 2013; 110: 191–205. © 2012 Wiley Periodicals, Inc.     

Enhanced process understanding and multivariate prediction of the relationship between cell culture process and monoclonal antibody quality

This work investigates the insights and understanding which can be deduced from predictive process models for the product quality of a monoclonal antibody based on designed high‐throughput cell culture experiments performed at milliliter (ambr‐15^®) scale. The investigated process conditions include various media supplements as well as pH and temperature shifts applied during the process. First, principal component analysis (PCA) is used to show the strong correlation characteristics among the product quality attributes including aggregates, fragments, charge variants, and glycans. Then, partial least square regression (PLS1 and PLS2) is applied to predict the product quality variables based on process information (one by one or simultaneously). The comparison of those two modeling techniques shows that a single (PLS2) model is capable of revealing the interrelationship of the process characteristics to the large set product quality variables. In order to show the dynamic evolution of the process predictability separate models are defined at different time points showing that several product quality attributes are mainly driven by the media composition and, hence, can be decently predicted from early on in the process, while others are strongly affected by process parameter changes during the process. Finally, by coupling the PLS2 models with a genetic algorithm first the model performance can be further improved and, most importantly, the interpretation of the large‐dimensioned process–product‐interrelationship can be significantly simplified. The generally applicable toolset presented in this case study provides a solid basis for decision making and process optimization throughout process development. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:1368–1380, 2017     

Integrating metabolome dynamics and process data to guide cell line selection in biopharmaceutical process development

The successful development of mammalian cell culture for the production of therapeutic antibodies is a resource-intensive and multistage process which requires the selection of high performing and stable cell lines at different scale-up stages. Accordingly, science-based approaches exploiting biological information, such as metabolomics, can support and accelerate the selection of promising cell lines to progress. In fact, the integration of dynamic biological information with process data can provide valuable insights on the cell physiological changes as a consequence of the cultivation process.This work studies the industrial development of monoclonal antibodies at micro-bioreactor scale (Ambr®15) and aims at accelerating the selection of the better performing cell lines. To that end, we apply a machine learning approach to integrate time-varying process and biological information (i.e., metabolomics), explicitly exploiting their dynamics.Strikingly, cell line performance during the cultivation can be predicted from early process timepoints by exploiting the gradual temporal evolution of metabolic phenotypes. Furthermore, product titer is estimated with good accuracy at late process timepoints, providing insights into its relationship with underlying metabolic mechanisms and enabling the identification of biomarkers to be further investigated. The biological insights obtained through the proposed machine learning approach provide data-driven metabolic understanding allowing early identification of high performing cell lines. Additionally, this analysis offers the opportunity to identify key metabolites which could be used as biomarkers for industrially relevant phenotypes and onward fit into our commercial manufacturing platforms.     

Single‐step affinity purification of enzyme biotherapeutics: A platform methodology for accelerated process development

Downstream sample purification for quality attribute analysis is a significant bottleneck in process development for non‐antibody biologics. Multi‐step chromatography process train purifications are typically required prior to many critical analytical tests. This prerequisite leads to limited throughput, long lead times to obtain purified product, and significant resource requirements. In this work, immunoaffinity purification technology has been leveraged to achieve single‐step affinity purification of two different enzyme biotherapeutics (Fabrazyme® [agalsidase beta] and Enzyme 2) with polyclonal and monoclonal antibodies, respectively, as ligands. Target molecules were rapidly isolated from cell culture harvest in sufficient purity to enable analysis of critical quality attributes (CQAs). Most importantly, this is the first study that demonstrates the application of predictive analytics techniques to predict critical quality attributes of a commercial biologic. The data obtained using the affinity columns were used to generate appropriate models to predict quality attributes that would be obtained after traditional multi‐step purification trains. These models empower process development decision‐making with drug substance‐equivalent product quality information without generation of actual drug substance. Optimization was performed to ensure maximum target recovery and minimal target protein degradation. The methodologies developed for Fabrazyme were successfully reapplied for Enzyme 2, indicating platform opportunities. The impact of the technology is significant, including reductions in time and personnel requirements, rapid product purification, and substantially increased throughput. Applications are discussed, including upstream and downstream process development support to achieve the principles of Quality by Design (QbD) as well as integration with bioprocesses as a process analytical technology (PAT). © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:708–717, 2014     

Integration of cell line and process development to overcome the challenge of a difficult to express protein

This case study addresses the difficulty in achieving high level expression and production of a small, very positively charged recombinant protein. The novel challenges with this protein include the protein's adherence to the cell surface and its inhibitory effects on Chinese hamster ovary (CHO) cell growth. To overcome these challenges, we utilized a multi‐prong approach. We identified dextran sulfate as a way to simultaneously extract the protein from the cell surface and boost cellular productivity. In addition, host cells were adapted to grow in the presence of this protein to improve growth and production characteristics. To achieve an increase in productivity, new cell lines from three different CHO host lines were created and evaluated in parallel with new process development workflows. Instead of a traditional screen of only four to six cell lines in bioreactors, over 130 cell lines were screened by utilization of 15 mL automated bioreactors (AMBR) in an optimal production process specifically developed for this protein. Using the automation, far less manual intervention is required than in traditional bench‐top bioreactors, and much more control is achieved than typical plate or shake flask based screens. By utilizing an integrated cell line and process development incorporating medium optimized for this protein, we were able to increase titer more than 10‐fold while obtaining desirable product quality. Finally, Monte Carlo simulations were performed to predict the optimal number of cell lines to screen in future cell line development work with the goal of systematically increasing titer through enhanced cell line screening. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1201–1211, 2015     

Identification and classification of host cell proteins during biopharmaceutical process development

As significant improvements in volumetric antibody productivity have been achieved by advances in upstream processing over the last decade, and harvest material has become progressively more difficult to recover with these intensified upstream operations, the segregation of upstream and downstream processing has remained largely unchanged. By integrating upstream and downstream process development, product purification issues are given consideration during the optimization of upstream operating conditions, which mitigates the need for extensive and expensive clearance strategies downstream. To investigate the impact of cell culture duration on critical quality attributes, CHO-expressed IgG1 was cultivated in two 2 L bioreactors with samples taken on days 8, 10, 13, 15, and 17. The material was centrifuged, filtered and protein A purified on a 1 ml HiTrap column. Host cell protein (HCP) identification by mass spectrometry (MS) was applied to this system to provide insights into cellular behavior and HCP carryover during protein A purification. It was shown that as cultivation progressed from day 8 to 17 and antibody titer increased, product quality declined due to an increase in post-protein A HCPs (from 72 to 475 peptides detected by MS) and a decrease in product monomer percentage (from 98% to 95.5%). Additionally, the MS data revealed an increase in the abundance of several classes of post-protein A HCPs (e.g., stress response proteins and indicators of cell age), particularly on days 15 and 17 of culture, which were associated with significant increases in total overall HCP levels. This provides new insight into the specific types of HCPs that are retained during mAb purification and may be used to aid process development strategies.     

Fermentanomics: Relating quality attributes of a monoclonal antibody to cell culture process variables and raw materials using multivariate data analysis

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. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1586–1599, 2015     

High-throughput process development for biopharmaceutical drug substances

Quality by Design (QbD) is gaining industry acceptance as an approach towards development and commercialization of biotechnology therapeutic products that are expressed via microbial or mammalian cell lines. In QbD, the process is designed and controlled to deliver specified quality attributes consistently. To acquire the enhanced understanding that is necessary to achieve the above, however, requires more extensive experimentation to establish the design space for the process and the product. With biotechnology companies operating under ever-increasing pressure towards lowering the cost of manufacturing, the use of high-throughput tools has emerged as a necessary enabler of QbD in a time- and resource-constrained environment. We review this topic for those in academia and industry that are engaged in drug substance process development.     

Impact of cell culture process changes on endogenous retrovirus expression

Cell culture process changes (e.g., changes in scale, medium formulation, operational conditions) and cell line changes are common during the development life cycle of a therapeutic protein. To ensure that the impact of such process changes on product quality and safety is minimal, it is standard practice to compare critical product quality and safety attributes before and after the changes. One potential concern introduced by cell culture process improvements is the possibility of increased endogenous retrovirus expression to a level above the clearance capability of the subsequent purification process. To address this, retrovirus expression was measured in scaled down and full production scaled Chinese hamster ovary (CHO) cell cultures of four monoclonal antibodies and one recombinant protein before and after process changes. Two highly sensitive, quantitative (Q)-PCR-based assays were used to measure endogenous retroviruses. It is shown that cell culture process changes that primarily alter media components, nutrient feed volume, seed density, cell bank source (i.e., master cell bank vs. working cell bank), and vial size, or culture scale, singly or in combination, do not impact the rate of retrovirus expression to an extent greater than the variability of the Q-PCR assays (0.2-0.5 log(10)). Cell culture changes that significantly alter the metabolic state of the cells and/or rates of protein expression (e.g., pH and temperature shifts, NaButyrate addition) measurably impact the rate of retrovirus synthesis (up to 2 log(10)). The greatest degree of variation in endogenous retrovirus expression was observed between individual cell lines (up to 3 log(10)). These data support the practice of measuring endogenous retrovirus output for each new cell line introduced into manufacturing or after process changes that significantly increase product-specific productivity or alter the metabolic state, but suggest that reassessment of retrovirus expression after other process changes may be unnecessary.     

Impact of mammalian cell culture conditions on monoclonal antibody charge heterogeneity: an accessory monitoring tool for process development

Recombinant monoclonal antibodies are predominantly produced in mammalian cell culture bioprocesses. Post-translational modifications affect the micro-heterogeneity of the product and thereby influence important quality attributes, such as stability, solubility, pharmacodynamics and pharmacokinetics. The analysis of the surface charge distribution of monoclonal antibodies provides aggregated information about these modifications. In this work, we established a direct injection pH gradient cation exchange chromatography method, which determines charge heterogeneity from cell culture supernatant without any purification steps. This tool was further applied to monitor processes that were performed under certain process conditions. Concretely, we were able to provide insights into charge variant formation during a fed-batch process of a Chinese hamster ovary cell culture, in turn producing a monoclonal antibody under varying temperatures and glucose feed strategies. Glucose concentration impacted the total emergence of acidic variants, whereas the variation of basic species was mainly dependent on process temperature. The formation rates of acidic species were described with a second-order reaction, where a temperature increase favored the conversion. This platform method will aid as a sophisticated optimization tool for mammalian cell culture processes. It provides a quality fingerprint for the produced mAb, which can be tested, compared to the desired target and confirmed early in the process chain.

     

Defining process design space for monoclonal antibody cell culture

The concept of design space has been taking root as a foundation of in‐process control strategies for biopharmaceutical manufacturing processes. During mapping of the process design space, the multidimensional combination of operational variables is studied to quantify the impact on process performance in terms of productivity and product quality. An efficient methodology to map the design space for a monoclonal antibody cell culture process is described. A failure modes and effects analysis (FMEA) was used as the basis for the process characterization exercise. This was followed by an integrated study of the inoculum stage of the process which includes progressive shake flask and seed bioreactor steps. The operating conditions for the seed bioreactor were studied in an integrated fashion with the production bioreactor using a two stage design of experiments (DOE) methodology to enable optimization of operating conditions. A two level Resolution IV design was followed by a central composite design (CCD). These experiments enabled identification of the edge of failure and classification of the operational parameters as non‐key, key or critical. In addition, the models generated from the data provide further insight into balancing productivity of the cell culture process with product quality considerations. Finally, process and product‐related impurity clearance was evaluated by studies linking the upstream process with downstream purification. Production bioreactor parameters that directly influence antibody charge variants and glycosylation in CHO systems were identified. Biotechnol. Bioeng. 2010;106: 894–905. © 2010 Wiley Periodicals, Inc.     

Methods in mammalian cell line engineering: from random mutagenesis to sequence-specific approaches

Due to the increasing demand for recombinant proteins, the interest in mammalian cell culture, especially of Chinese hamster ovary cells, grows rapidly. This is accompanied by the desire to improve cell lines in order to achieve higher titers and a better product quality. Until recently, most cell line development procedures were based on random integration and gene amplification, but several methods for targeted genetic modification of cells have been developed. Some of those are homologous recombination, RNA interference and zinc-finger nucleases. Especially the latter two have evolved considerably and will soon become a standard for cell line engineering in research and industrial application. This review presents an overview of established as well as new and promising techniques for targeted genetic modification of mammalian cells.     

CRISPR/Cas12a-mediated CHO genome engineering can be effectively integrated at multiple stages of the cell line generation process for bioproduction

Most biopharmaceuticals produced today are generated using Chinese hamster ovary (CHO) cells, therefore significant attention is focused on methods to improve CHO cell productivity and product quality. The discovery of gene-editing tools, such as CRISPR/Cas9, offers new opportunities to improve CHO cell bioproduction through cell line engineering. Recently an additional CRISPR-associated protein, Cas12a (Cpf1), was shown to be effective for gene editing in eukaryotic cells, including CHO. In this study, we demonstrate the successful application of CRISPR/Cas12a for the generation of clonally derived CHO knockout (KO) cell lines with improved product quality attributes. While we found Cas12a efficiency to be highly dependent on the targeting RNA used, we were able to generate CHO KO cell lines using small screens of only 96–320 clonally derived cell lines. Additionally, we present a novel bulk culture analysis approach that can be used to quickly assess CRISPR RNA efficiency and determine ideal screen sizes for generating genetic KO cell lines. Most critically, we find that Cas12a can be directly integrated into the cell line generation process through cotransfection with no negative impact on titer or screen size. Overall, our results show CRISPR/Cas12a to be an efficient and effective CHO genome editing tool.     

Development of a novel,high-throughput screening tool for efficient perfusion-based cell culture process development

Perfusion technology has been successfully used for the commercial production of biotherapeutics, in particular unstable recombinant proteins, for more than a decade. However, there has been a general lack of high-throughput cell culture tools specifically for perfusion-based cell culture processes. Here, we have developed a high-throughput cell retention operation for use with the ambr® 15 bioreactor system. Experiments were run in both 24 and 48 reactor configurations for comparing perfusion mimic models, media development, and clone screening. Employing offline centrifugation for cell retention and a variable volume model developed with MATLAB computational software, the established screening model has demonstrated cell culture performance, productivity, and product quality were comparable to bench scale bioreactors. The automated, single use, high-throughput perfusion mimic is a powerful tool that enables us to have rapid and efficient process development of perfusion-based cell culture processes.     

Use of a small molecule cell cycle inhibitor to control cell growth and improve specific productivity and product quality of recombinant proteins in CHO cell cultures

The continued need to improve therapeutic recombinant protein productivity has led to ongoing assessment of appropriate strategies in the biopharmaceutical industry to establish robust processes with optimized critical variables, that is, viable cell density (VCD) and specific productivity (product per cell, qP). Even though high VCD is a positive factor for titer, uncontrolled proliferation beyond a certain cell mass is also undesirable. To enable efficient process development to achieve consistent and predictable growth arrest while maintaining VCD, as well as improving qP, without negative impacts on product quality from clone to clone, we identified an approach that directly targets the cell cycle G1‐checkpoint by selectively inhibiting the function of cyclin dependent kinases (CDK) 4/6 with a small molecule compound. Results from studies on multiple recombinant Chinese hamster ovary (CHO) cell lines demonstrate that the selective inhibitor can mediate a complete and sustained G0/G1 arrest without impacting G2/M phase. Cell proliferation is consistently and rapidly controlled in all recombinant cell lines at one concentration of this inhibitor throughout the production processes with specific productivities increased up to 110 pg/cell/day. Additionally, the product quality attributes of the mAb, with regard to high molecular weight (HMW) and glycan profile, are not negatively impacted. In fact, high mannose is decreased after treatment, which is in contrast to other established growth control methods such as reducing culture temperature. Microarray analysis showed major differences in expression of regulatory genes of the glycosylation and cell cycle signaling pathways between these different growth control methods. Overall, our observations showed that cell cycle arrest by directly targeting CDK4/6 using selective inhibitor compound can be utilized consistently and rapidly to optimize process parameters, such as cell growth, qP, and glycosylation profile in recombinant antibody production cultures. Biotechnol. Bioeng. 2015;112: 141–155. © 2014 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.     

大规模动物细胞培养的问题及对策

大规模动物细胞培养在生物技术产业化进程中显示出强大的潜力。本文综述了大规模动物细胞培养过程中出现的问题及其解决办法 ,包括细胞培养环境、基因工程途径改建细胞系及过程监控等。对于这些进展的充分了解对优化细胞培养工艺、提高产品质量具有重要意义     

Systematic development of temperature shift strategies for Chinese hamster ovary cells based on short duration cultures and kinetic modeling

Temperature shift (TS) to a hypothermic condition has been widely used during protein production processes that use Chinese hamster ovary (CHO) cells. The effect of temperature on cell growth, metabolites, protein titer and quality depends on cell line, product, and other bioreactor conditions. Due to the large numbers of experiments, which typically last 2–3 weeks each, limited systematic TS studies have been reported with multiple shift temperatures and steps at different times. Here, we systematically studied the effect of temperature on cell culture performance for the production of two monoclonal antibodies by industrial GS and DG44 CHO cell lines. Three 2–8 day short-duration methods were developed and validated for researching the effect of many different temperatures on CHO cell culture and quality attributes. We found that minor temperature differences (1–1.5 °C) affected cell culture performance. The kinetic parameters extracted from the short duration data were subsequently used to compute and predict cell culture performance in extended duration of 10–14 days with multiple TS conditions for both CHO cell lines. These short-duration culture methods with kinetic modeling tools may be used for effective TS optimization to achieve the best profiles for cell growth, metabolites, titer and quality attributes. Although only three short-duration methods were developed with two CHO cell lines, similar short-duration methods with kinetic modeling may be applied for different hosts, including both microbial and other mammalian cells.     

Screening and assessment of performance and molecule quality attributes of industrial cell lines across different fed‐batch systems

The major challenge in the selection process of recombinant cell lines for the production of biologics is the choice, early in development, of a clonal cell line presenting a high productivity and optimal cell growth. Most importantly, the selected candidate needs to generate a product quality profile which is adequate with respect to safety and efficacy and which is preserved across cell culture scales. We developed a high‐throughput screening and selection strategy of recombinant cell lines, based on their productivity in shaking 96‐deepwell plates operated in fed‐batch mode, which enables the identification of cell lines maintaining their high productivity at larger scales. Twelve recombinant cell lines expressing the same antibody with different productivities were selected out of 470 clonal cell lines in 96‐deepwell plate fed‐batch culture. They were tested under the same conditions in 50 mL vented shake tubes, microscale and lab‐scale bioreactors in order to confirm the maintenance of their performance at larger scales. The use of a feeding protocol and culture conditions which are essentially the same across the different scales was essential to maintain productivity and product quality profiles across scales. Compared to currently used approaches, this strategy has the advantage of speeding up the selection process and increases the number of screened clones for getting high‐producing recombinant cell lines at manufacturing scale with the desired performance and quality. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 32:160–170, 2016     

A systematic approach for scale-down model development and characterization of commercial cell culture processes

The objective of process characterization is to demonstrate robustness of manufacturing processes by understanding the relationship between key operating parameters and final performance. Technical information from the characterization study is important for subsequent process validation, and this has become a regulatory expectation in recent years. Since performing the study at the manufacturing scale is not practically feasible, development of scale-down models that represent the performance of the commercial process is essential to achieve reliable process characterization. In this study, we describe a systematic approach to develop a bioreactor scale-down model and to characterize a cell culture process for recombinant protein production in CHO cells. First, a scale-down model using 2-L bioreactors was developed on the basis of the 2000-L commercial scale process. Profiles of cell growth, productivity, product quality, culture environments (pH, DO, pCO2), and level of metabolites (glucose, glutamine, lactate, ammonia) were compared between the two scales to qualify the scale-down model. The key operating parameters were then characterized in single-parameter ranging studies and an interaction study using this scale-down model. Appropriate operation ranges and acceptance criteria for certain key parameters were determined to ensure the success of process validation and the process performance consistency. The process worst-case condition was also identified through the interaction study.     

An integrated strategy for the process development of a recombinant antibody-cytokine fusion protein expressed in BHK cells

Recombinant fusion proteins offer important new therapeutic approaches for the future. This report describes the use of three different genetic strategies (i.e. “mono-”, “bi-” and “tri-cistronic” vectors) to achieve stable secretion from BHK cells of a glycosylated antibody-cytokine fusion protein designed for use in anti-tumour therapy. It describes selection of a robust and effective production cell line based on stability of secretion of the product, quality of mRNA and protein products and performance in in vitro bioassays for potency. The data obtained at this stage were utilised in the selection of a suitable candidate production cell line. The relative productivity and general performance of the cells in stirred tank and fixed bed culture systems indicated that a variety of cell culture technologies provided robust tools for production of a highly selected cell clone. Consistency of the product glycosylation was determined by analysis of released oligosaccharides using matrix-assisted laser desorption ionisation – time of flight mass spectrometry and high-performance anion exchange chromatography. These investigations showed consistent expression of three glycoforms of the fusion protein which varied in their relative proportions in different culture systems and at different time points in a fixed bed reactor with continuous perfusion. In conclusion, this study dealt with a range of important scientific and technical issues which are essential for regulatory approval and commercial success of a recombinant protein and elucidates some useful markers for process development for similar recombinant biologicals. Received: 25 March 1999 / Accepted: 23 April 1999