Kinetic modeling of Chinese hamster ovary cell culture: factors and principles

Modeling of cell cultivation for monoclonal antibody production processes considering lactate metabolic shifts

Demand for monoclonal antibodies (mAbs) is rapidly increasing. To achieve higher productivity, there have been improvements to cell lines, operating modes, media, and cultivation conditions. Representative mathematical models are needed to narrow down the growing number of process alternatives. Previous studies have proposed mechanistic models to depict cell metabolic shifts (e.g., lactate production to consumption). However, the impacts of variations of some operating conditions have not yet been fully incorporated in such models. This paper offers a new mechanistic model considering variations in dissolved oxygen and glutamine depletion on cell metabolism applied to a novel Chinese hamster ovary (CHO) cell line. Expressions for the specific rates of lactate production, glutamine consumption, and mAb production were formulated for stirred and shaken-tank reactors. A deeper understanding of lactate metabolic shifts was obtained under different combinations of experimental conditions. Lactate consumption was more pronounced in conditions with higher DO and low glutamine concentrations. The model offers mechanistic insights that are useful for designing advanced operation strategies. It can be used in design space generation and process optimization for better productivity and product quality.

Debottlenecking and reformulating feed media for improved CHO cell growth and titer by data-driven and model-guided analyses

Designing and selecting cell culture media along with their feeding are a key strategy to maximize culture performance in biopharmaceutical processes. However, the sensitivity of mammalian cells to their culture environment necessitates specific nutritional requirements for their growth and the production of high-quality proteins such as antibodies, depending on the cell lines and operational conditions employed. In this regard, previously we developed a data-driven and in-silico model-guided systematic framework to investigate the effect of growth media on Chinese hamster ovary (CHO) cell culture performance, allowing us to design and reformulate basal media. To expand our exploration for media development research, we evaluated two chemically defined feed media, A and B, using a monoclonal antibody-producing CHO-K1 cell line in ambr15 bioreactor runs. We observed a significant impact of the feed media on various aspects of cell culture, including growth, longevity, viability, productivity, and the production of toxic metabolites. Specifically, the concentrated feed A was inadequate in sustaining prolonged cell culture and achieving high titers when compared to feed B. Within our framework, we systematically investigated the major metabolic bottlenecks in the tricarboxylic acid cycle and relevant amino acid transferase reactions. This analysis identified target components that play a crucial role in alleviating bottlenecks and designing highly productive cell cultures, specifically the addition of glutamate to feed A and asparagine to feed B. Based on our findings, we reformulated the feeds by adjusting the amounts of the targeted amino acids and successfully validated the effectiveness of the strategy in promoting cell growth, life span, and/or titer.

Advances in bioreactor control for production of biotherapeutic products

Advanced control strategies are well established in chemical, pharmaceutical, and food processing industries. Over the past decade, the application of these strategies is being explored for control of bioreactors for manufacturing of biotherapeutics. Most of the industrial bioreactor control strategies apply classical control techniques, with the control system designed for the facility at hand. However, with the recent progress in sensors, machinery, and industrial internet of things, and advancements in deeper understanding of the biological processes, coupled with the requirement of flexible production, the need to develop a robust and advanced process control system that can ease process intensification has emerged. This has further fuelled the development of advanced monitoring approaches, modeling techniques, process analytical technologies, and soft sensors. It is seen that proper application of these concepts can significantly improve bioreactor process performance, productivity, and reproducibility. This review is on the recent advancements in bioreactor control and its related aspects along with the associated challenges. This study also offers an insight into the future prospects for development of control strategies that can be designed for industrial-scale production of biotherapeutic products.

Deep learning in drug discovery: an integrative review and future challenges

Recently, using artificial intelligence (AI) in drug discovery has received much attention since it significantly shortens the time and cost of developing new drugs. Deep learning (DL)-based approaches are increasingly being used in all stages of drug development as DL technology advances, and drug-related data grows. Therefore, this paper presents a systematic Literature review (SLR) that integrates the recent DL technologies and applications in drug discovery Including, drug-target interactions (DTIs), drug-drug similarity interactions (DDIs), drug sensitivity and responsiveness, and drug-side effect predictions. We present a review of more than 300 articles between 2000 and 2022. The benchmark data sets, the databases, and the evaluation measures are also presented. In addition, this paper provides an overview of how explainable AI (XAI) supports drug discovery problems. The drug dosing optimization and success stories are discussed as well. Finally, digital twining (DT) and open issues are suggested as future research challenges for drug discovery problems. Challenges to be addressed, future research directions are identified, and an extensive bibliography is also included.

Kinetic modeling: A tool for temperature shift and feeding optimization in cell culture process development

Mammalian cells have dominated the biopharmaceutical industry for biotherapeutic protein production and tremendous efforts have been devoted to enhancing productivity during the cell culture process development. However, determining the optimal process conditions is still a huge challenge. Constrained by the limited resources and timeline, usually it is impossible to fully explore the optimal range of all process parameters (temperature, pH, dissolved oxygen, basal and feeding medium, additives, etc.). Kinetic modeling, which finds out the global optimum by systematically screening all potential conditions for cell culture process, provides a solution to this dilemma. However, studies on optimizing temperature shift and feeding strategies simultaneously using this approach have not been reported. In this study, we built up a kinetic model of fed-batch culture process for simultaneous optimization of temperature shift and feeding strategies. The fitting results showed high accuracy and demonstrated that the kinetic model can be used to describe the mammalian cell culture performance. In addition, five more fed-batch experiments were conducted to test this model's predicting power on different temperature shift and feeding strategies. It turned out that the predicted data matched well with experimental ones on viable cell density (VCD), metabolites, and titer for the entire culture duration and allowed selecting the same best condition with the experimental results. Therefore, adopting this approach can potentially reduce the number of experiments required for culture process optimization.

Recent developments in miRNA based recombinant protein expression in CHO

It is widely accepted that the growing demand for recombinant therapeutic proteins has led to the expansion of the biopharmaceutical industry and the development of strategies to increase recombinant protein production in mammalian cell lines such as SP2/0 HEK and particularly Chinese hamster ovary cells. For a long time now, most investigations have been focused on increasing host cell productivity using genetic manipulating of cellular processes like cell cycle, apoptosis, cell growth, protein secretory and other pathways. In recent decades MicroRNAs beside different genetic engineering tools (e.g., TALEN, ZFN, and Crisper/Cas) have attracted further attention as a tool in the genetic engineering of host cells to increase protein expression levels. Their ability to simultaneously target multiple mRNAs involved in one or more cellular processes made them a favorable tool in this field. Accordingly, this study aimed to review the methods of selecting target miRNA for cell line engineering, miRNA gain- or loss-of-function strategies, examples of laboratory and pilot studies in this field and discussed advantages and disadvantages of this technology.

Exploring synthetic biology for the development of a sensor cell line for automated bioprocess control

Unfavorable process conditions lead to adverse cultivation states, limited cell growth and thus hamper biotherapeutic protein production. Oxygen deficiency or hyperosmolality are among the most critical process conditions and therefore require continuous monitoring. We established a novel sensor CHO cell line with the ability to automatically sense and report unwanted process conditions by the expression of destabilized fluorescent proteins. To this end, an inducible real-time system to detect hypoxia by hypoxia response elements (HREs) of vascular endothelial growth factor (VEGF) origin reporting limitations by the expression of destabilized green fluorescent protein (GFP) was created. Additionally, we established a technique for observing hyperosmolality by exploiting osmotic response elements (OREs) for the expression of unstable blue fluorescent protein (BFP, FKBP-BFP), enabling the simultaneous automated supervision of two bioprocess parameters by using a dual sensor CHO cell line transfected with a multiplexable monitoring system. We finally also provided a fully automated in-line fluorescence microscopy-based setup to observe CHO cells and their response to varying culture conditions. In summary, we created the first CHO cell line, reporting unfavorable process parameters to the operator, and provided a novel and promising sensor technology accelerating the implementation of the process analytical technology (PAT) initiative by innovative solutions.

Productivity improvement and charge variant modulation for intensified cell culture processes by adding a carboxypeptidase B (CpB) treatment step

The goal of cell culture process intensification is to improve productivity while maintaining acceptable quality attributes. In this report, four processes, namely a conventional manufacturing Process A, and processes intensified by enriched N-1 seed (Process B), by perfusion N-1 seed (Process C), and by perfusion production (Process D) were developed for the production of a monoclonal antibody. The three intensified processes substantially improved productivity, however, the product either failed to meet the specification for charge variant species (main peak) for Process D or the production process required early harvest to meet the specification for charge variant species, Day 10 or Day 6 for Processes B and C, respectively. The lower main peak for the intensified processes was due to higher basic species resulting from higher C-terminal lysine. To resolve this product quality issue, we developed an enzyme treatment method by introducing carboxypeptidase B (CpB) to clip the C-terminal lysine, leading to significantly increased main peak and an acceptable and more homogenous product quality for all the intensified processes. Additionally, Processes B and C with CpB treatment extended bioreactor durations to Day 14 increasing titer by 38% and 108%, respectively. This simple yet effective enzyme treatment strategy could be applicable to other processes that have similar product quality issues.

Digital Twins in Pharmaceutical and Biopharmaceutical Manufacturing: A Literature Review

The development and application of emerging technologies of Industry 4.0 enable the realization of digital twins (DT), which facilitates the transformation of the manufacturing sector to a more agile and intelligent one. DTs are virtual constructs of physical systems that mirror the behavior and dynamics of such physical systems. A fully developed DT consists of physical components, virtual components, and information communications between the two. Integrated DTs are being applied in various processes and product industries. Although the pharmaceutical industry has evolved recently to adopt Quality-by-Design (QbD) initiatives and is undergoing a paradigm shift of digitalization to embrace Industry 4.0, there has not been a full DT application in pharmaceutical manufacturing. Therefore, there is a critical need to examine the progress of the pharmaceutical industry towards implementing DT solutions. The aim of this narrative literature review is to give an overview of the current status of DT development and its application in pharmaceutical and biopharmaceutical manufacturing. State-of-the-art Process Analytical Technology (PAT) developments, process modeling approaches, and data integration studies are reviewed. Challenges and opportunities for future research in this field are also discussed.

Development of an intensified fed-batch production platform with doubled titers using N-1 perfusion seed for cell culture manufacturing

The goal of cell culture process intensification is to increase volumetric productivity, generally by increasing viable cell density (VCD), cell specific productivity or production bioreactor utilization in manufacturing. In our previous study, process intensification in fed-batch production with higher titer or shorter duration was demonstrated by increasing the inoculation seeding density (SD) from ~ 0.6 (Process A) to 3–6 × 106 cells/mL (Process B) in combination with media enrichment. In this study, we further increased SD to 10–20 × 106 cells/mL (Process C) using perfusion N-1 seed cultures, which increased titers already at industrially relevant levels by 100% in 10–14 day bioreactor durations for four different mAb-expressing CHO cell lines. Redesigned basal and feed media were critical for maintaining higher VCD and cell specific productivity during the entire production duration, while medium enrichment, feeding strategies and temperature shift optimization to accommodate high VCDs were also important. The intensified Process C was successfully scaled up in 500-L bioreactors for 3 of the 4 mAbs, and quality attributes were similar to the corresponding Process A or Process B at 1000-L scale. The fed-batch process intensification strategies developed in this study could be applied for manufacturing of other mAbs using CHO and other host cells.