Deciphering Metabolic Pathways in High-Seeding-Density Fed-Batch Processes for Monoclonal Antibody Production: A Computational Modeling Perspective.

Due to their high specificity, monoclonal antibodies (mAbs) have garnered significant attention in recent decades, with advancements in production processes, such as high-seeding-density (HSD) strategies, contributing to improved titers. This study provides a thorough investigation of high seeding processes for mAb production in Chinese hamster ovary (CHO) cells, focused on identifying significant metabolites and their interactions. We observed high glycolytic fluxes, the depletion of asparagine, and a shift from lactate production to consumption.

Application of metabolic modeling for targeted optimization of high seeding density processes.

Process intensification by application of perfusion mode in pre-stage bioreactors and subsequent inoculation of cell cultures at high seeding densities (HSD) has the potential to meet the increasing requirements of future manufacturing demands. However, process development is currently restrained by a limited understanding of the cell's requirements under these process conditions. The goal of this study was to use extended metabolite analysis and metabolic modeling for targeted optimization of HSD cultivations.

Towards robust cell culture processes - Unraveling the impact of media preparation by spectroscopic online monitoring.

Biopharmaceutical manufacturing processes can be affected by variability in cell culture media, e.g. caused by raw material impurities.

Pre-stage perfusion and ultra-high seeding cell density in CHO fed-batch culture: a case study for process intensification guided by systems biotechnology.

Process intensification strategies are needed in the field of therapeutic protein production for higher productivities, lower cost of goods and improved facility utilization. This work describes an intensification approach, which connects a tangential-flow-filtration (TFF) based pre-stage perfusion process with a concentrated fed-batch production culture inoculated with an ultra-high seeding density (uHSD). This strategy shifted biomass production towards the pre-stage, reaching up to 45 × 10 cells/mL in perfusion mode.

A global RNA-seq-driven analysis of CHO host and production cell lines reveals distinct differential expression patterns of genes contributing to recombinant antibody glycosylation.

Boehringer Ingelheim uses two CHO-DG44 lines for manufacturing biotherapeutics, BI-HEX-1 and BI-HEX-2, which produce distinct cell type-specific antibody glycosylation patterns. A recently established CHO-K1 descended host, BI-HEX-K1, generates antibodies with glycosylation profiles differing from CHO-DG44. Manufacturing process development is significantly influenced by these unique profiles.

Advancing biopharmaceutical process development by system-level data analysis and integration of omics data.

Development of efficient bioprocesses is essential for cost-effective manufacturing of recombinant therapeutic proteins. To achieve further process improvement and process rationalization comprehensive data analysis of both process data and phenotypic cell-level data is essential. Here, we present a framework for advanced bioprocess data analysis consisting of multivariate data analysis (MVDA), metabolic flux analysis (MFA), and pathway analysis for mapping of large-scale gene expression data sets.

Into the unknown: expression profiling without genome sequence information in CHO by next generation sequencing.

The arrival of next-generation sequencing (NGS) technologies has led to novel opportunities for expression profiling and genome analysis by utilizing vast amounts of short read sequence data. Here, we demonstrate that expression profiling in organisms lacking any genome or transcriptome sequence information is feasible by combining Illumina's mRNA-seq technology with a novel bioinformatics pipeline that integrates assembled and annotated Chinese hamster ovary (CHO) sequences with information derived from related organisms. We applied this pipeline to the analysis of CHO cells which were chosen as a model system owing to its relevance in the production of therapeutic proteins.

CHO gene expression profiling in biopharmaceutical process analysis and design.

Increase in both productivity and product yields in biopharmaceutical process development with recombinant protein producing mammalian cells can be mainly attributed to the advancements in cell line development, media, and process optimization. Only recently, genome-scale technologies enable a system-level analysis to elucidate the complex biomolecular basis of protein production in mammalian cells promising an increased process understanding and the deduction of knowledge-based approaches for further process optimization. Here, the use of gene expression profiling for the analysis of a low titer (LT) and high titer (HT) fed batch process using the same IgG producing CHO cell line was investigated.

In vivo dynamics of glycolysis in Escherichia coli shows need for growth-rate dependent metabolome analysis.

Metabolomics emerges to become an important profiling technique in bio(techno)logical systems. In addition to intracellular metabolite concentrations at (quasi) stationary conditions, stimulus-response experiments provide information on the dynamic behavior of metabolic pathways. These data are relevant for bioprocess analysis on the level of metabolism and for application of metabolic engineering principles aiming at a metabolic redesign of producer cells.

Metabolic flux analysis in Escherichia coli by integrating isotopic dynamic and isotopic stationary 13C labeling data.

The novel concept of isotopic dynamic 13C metabolic flux analysis (ID-13C MFA) enables integrated analysis of isotopomer data from isotopic transient and/or isotopic stationary phase of a 13C labeling experiment, short-time experiments, and an extended range of applications of 13C MFA. In the presented work, an experimental and computational framework consisting of short-time 13C labeling, an integrated rapid sampling procedure, a LC-MS analytical method, numerical integration of the system of isotopomer differential equations, and estimation of metabolic fluxes was developed and applied to determine intracellular fluxes in glycolysis, pentose phosphate pathway (PPP), and citric acid cycle (TCA) in Escherichia coli grown in aerobic, glucose-limited chemostat culture at a dilution rate of D = 0.10 h(-1).

Integrated sampling procedure for metabolome analysis.

Metabolome analysis, the analysis of large sets of intracellular metabolites, has become an important systems analysis method in biotechnological and pharmaceutical research. In metabolic engineering, the integration of metabolome data with fluxome and proteome data into large-scale mathematical models promises to foster rational strategies for strain and cell line improvement. However, the development of reproducible sampling procedures for quantitative analysis of intracellular metabolite concentrations represents a major challenge, accomplishing (i) fast transfer of sample, (ii) efficient quenching of metabolism, (iii) quantitative metabolite extraction, and (iv) optimum sample conditioning for subsequent quantitative analysis.