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The conventional fed-batch process characterized by a low titer currently challenges pharmaceutical development. Process optimization by applying a perfusion process in the pre-stage and subsequent production phase at a high seeding density (HSD) can meet this challenge. In this study, we employed a simplified approach based on measured experiments, namely segmented modeling, to systematically analyze an HSD fed-batch process compared to a standard process. A comparison indicated that the metabolic phases of HSD processes are not only shifted in time, but metabolite trends show an altered metabolism. In an extended study, we integrated the intracellular fluxes determined by a metabolic flux analysis into the segmented modeling approach. Compared to using only extracellular rates, similar phases are identified, and this highlights the reliability of phase identification modeling using extracellular rates only. Furthermore, the segmented linear regression approach is used to create a model that describes cellular behavior and that can be used to predict potential improvements in the feeding strategy and in harvest viability. Here, overfeeding was eliminated and a significantly higher titer was achieved. This work provides insights into the overall metabolic changes in the HSD process and paves the way towards the optimization of the feeding regime.

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. The metabolite analysis of HSD N‐stage cultures revealed accumulation of inhibiting metabolites early in the process and flux balance analysis led to the assumption that reactive oxygen species (ROS) were contributing to the fast decrease in cell viability. Based on the metabolic analysis an optimized feeding strategy with lactate and cysteine supplementation was applied, resulting in an increase in antibody titer of up to 47%. Flux balance analysis was further used to elucidate the surprisingly strong synergistic effect of lactate and cysteine, indicating that increased lactate uptake led to reduced ROS formation under these conditions whilst additional cysteine actively reduced ROS via the glutathione pathway. The presented results finally demonstrate the benefit of modeling approaches for process intensification as well as the potential of HSD cultivations for biopharmaceutical manufacturing., Extended metabolite analysis in combination with flux balance analysis was applied for targeted optimization of High Seeding Density (HSD) CHO cell cultures. Flux balance analysis revealed distinct metabolic phases with high reactive oxygen species (ROS) formation and increased cell specific productivities. Based on the metabolic analysis an optimized feeding strategy with lactate and cysteine supplementation was applied leading to an increase in product titer of up to 47%.

Biopharmaceutical manufacturing processes can be affected by variability in cell culture media, e.g. caused by raw material impurities. Although efforts have been made in industry and academia to characterize cell culture media and raw materials with advanced analytics, the process of industrial cell culture media preparation itself has not been reported so far. Within this publication, we first compare mid‐infrared and two‐dimensional fluorescence spectroscopy with respect to their suitability as online monitoring tools during cell culture media preparation, followed by a thorough assessment of the impact of preparation parameters on media quality. Through the application of spectroscopic methods, we can show that media variability and its corresponding root cause can be detected online during the preparation process. This methodology is a powerful tool to avoid batch failure and is a valuable technology for media troubleshooting activities. Moreover, in a design of experiments approach, including additional liquid chromatography–mass spectrometry analytics, it is shown that variable preparation parameters such as temperature, power input and preparation time can have a strong impact on the physico‐chemical composition of the media. The effect on cell culture process performance and product quality in subsequent fed‐batch processes was also investigated. The presented results reveal the need for online spectroscopic methods during the preparation process and show that media variability can already be introduced by variation in media preparation parameters, with a potential impact on scale‐up to a commercial manufacturing process.

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 × 106 cells/mL in perfusion mode. Subsequently, production in the intensified fed-batch started immediately and the product titer was almost doubled (1.9-fold) in an equivalent runtime and with comparable product quality compared to low-seeded cultures. Driven by mechanistic modelling and next-generation sequencing (NGS) the process had been optimized by selecting the media composition in a way that minimized cellular adaptation between perfusion and production culture. As a main feature, lactate feeding was applied in the intensified approach to promote cell culture performance and process scalability was proven via transfer to pilot-scale i.e., 20 L pre-stage perfusion and 80 L production reactor. Moreover, an earlier shift from a growth associated to a production stage associated gene expression pattern was identified for uHSD cultures compared to the reference. Overall, we showed that the described intensification strategy yielded in a higher volumetric productivity and is applicable for existing or already approved molecules in common, commercial fed-batch facilities. This work provides an in-depth molecular understanding of cellular processes that are detrimental during process intensification. Electronic supplementary material The online version of this article (10.1007/s00449-020-02337-1) contains supplementary material, which is available to authorized users.

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. Specifically, we analysed CHO cells undergoing butyrate treatment which is known to affect cell cycle regulation and to increase the specific productivity of recombinant proteins. By this means, we identified sequences for >13,000 CHO genes which added sequence information of approximately 5000 novel genes to the CHO model. More than 6000 transcript sequences are predicted to be complete, as they covered >95% of the corresponding mouse orthologs. Detailed analysis of selected biological functions such as DNA replication and cell cycle control, demonstrated the potential of NGS expression profiling in organisms without extended genome sequence to improve both data quantity and quality.

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. We found that gene expression (i) significantly differed in HT versus LT process conditions due to differences in applied chemically defined, serum-free media, (ii) changed over the time course of the fed batch processes, and that (iii) both metabolic pathways and 14 biological functions such as cellular growth or cell death were affected. Furthermore, detailed analysis of metabolism in a standard process format revealed the potential use of transcriptomics for rational media design as is shown for the case of lipid metabolism where the product titer could be increased by about 20% based on a lipid modified basal medium. The results demonstrate that gene expression profiling can be an important tool for mammalian biopharmaceutical process analysis and optimization.

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. Intracellular steady state concentrations were quantified for 12 metabolic intermediates. A total of 90 LC-MS mass isotopomers were quantified at sampling times t = 0, 91, 226, 346, 589 s and at isotopic stationary conditions. Isotopic stationarity was reached within 10 min in glycolytic and PPP metabolites. Consistent flux solutions were obtained by ID-13C MFA using isotopic dynamic and isotopic stationary 13C labeling data and by isotopic stationary 13C MFA (IS-13C MFA) using solely isotopic stationary data. It is demonstrated that integration of dynamic 13C labeling data increases the sensitivity of flux estimation, particularly at the glucose-6-phosphate branch point. The identified split ratio between glycolysis and PPP was 55%:44%. These results were confirmed by IS-13C MFA additionally using labeling data in proteinogenic amino acids (GC-MS) obtained after 5 h from sampled biomass. Biotechnol. Bioeng. 2008;99: 1170–1185. © 2007 Wiley Periodicals, Inc.

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. This data analysis platform was applied in a process development project with an IgG-producing Chinese hamster ovary (CHO) cell line in which the maximal product titer could be increased from about 5 to 8 g/L.Principal component analysis (PCA), k-means clustering, and partial least-squares (PLS) models were applied to analyze the macroscopic bioprocess data. MFA and gene expression analysis revealed intracellular information on the characteristics of high-performance cell cultivations. By MVDA, for example, correlations between several essential amino acids and the product concentration were observed. Also, a grouping into rather cell specific productivity-driven and process control-driven processes could be unraveled. By MFA, phenotypic characteristics in glycolysis, glutaminolysis, pentose phosphate pathway, citrate cycle, coupling of amino acid metabolism to citrate cycle, and in the energy yield could be identified. By gene expression analysis 247 deregulated metabolic genes were identified which are involved, inter alia, in amino acid metabolism, transport, and protein synthesis.

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.

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. However, even for the well-studied bacteria Escherichia coli only limited growth-rate dependent intracellular metabolite information is currently available, thereby impeding comprehensive metabolome analysis. Here, we present intracellular metabolite concentration data of representative glycolytic intermediates in E. coli cultivated in glucose-limited chemostats, (i) at systematic variation of growth-rate (D = 0.1, 0.2, 0.3, and 0.4 h(-1)) and (ii) at both steady-state and after a glucose pulse applying a recently introduced integrated sampling procedure and LC-MS analytical method. Whereas intracellular steady-state concentrations of upper part glycolytic intermediates FBP and DHAP+GAP increased 2.3-fold, respectively 2.8-fold, when specific growth-rate is raised from micro = 0.1 h(-1) to micro = 0.4 h(-1), the opposite trend was observed for 2PG+3PG and PEP pools with a decrease by a factor of 2.1, respectively 1.9. In glucose pulse experiments FBP and DHAP+GAP showed a 3.3 (1.8)-fold, respectively 2.8 (2.0)-fold, increase relative to the steady-state level at micro = 0.1 (0.4) h(-1). Also, the dynamics changed with growth-rate for these two metabolite pools. In contrast, 2PG+3PG and PEP were characterized by decreased concentrations in response to a glucose pulse and the relative changes related to steady-state values were significantly smaller compared with FBP and DHAP+GAP. The observed growth-rate dependency of our data clearly indicates the necessity for metabolome studies covering a broader range of physiological growth conditions.

Background and novelty Product quality is a result of the entire production process including protein sequence, cell substrate and process parameters. Many of the desired product properties are defined by posttranslational modifications with impact on biological activity, immunogenicity, half-life or stability. In-depth process understanding enables the targeted modulation of product quality attributes by rationally designed bioprocesses. This is valuable for new biological molecules in order to improve efficacy, reduce side effects, access new patient populations. For biosimilars this allows developing into defined quality attribute profiles. The identification of suitable process parameters and media compositions to modulate quality attributes is challenging due to the complexity of cell culture processes. Here, this challenge was approached by comprehensive data analysis, in-depth characterization of charge variant formation and high-throughput screening of process parameters and media compounds.

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. In addressing these requirements, we propose an integrated sampling procedure. Simultaneous quenching and quantitative extraction of intracellular metabolites were realized by short-time exposure of cells to temperatures < or =95 degrees C, where intracellular metabolites are released quantitatively. Based on these findings, we combined principles of heat transfer with knowledge on physiology, for example, turnover rates of energy metabolites, to develop an optimized sampling procedure based on a coiled single tube heat exchanger. As a result, this sampling procedure enables reliable and reproducible measurements through (i) the integration of three unit operations into a one unit operation, (ii) the avoidance of any alteration of the sample due to chemical reagents in quenching and extraction, and (iii) automation. A sampling frequency of 5 s(-)(1) and an overall individual sample processing time faster than 30 s allow observing responses of intracellular metabolite concentrations to extracellular stimuli on a subsecond time scale. Recovery and reliability of the unit operations were analyzed. Impact of sample conditioning on subsequent IC-MS analysis of metabolites was examined as well. The integrated sampling procedure was validated through consistent results from steady-state metabolite analysis of Escherichia coli cultivated in a chemostat at D = 0.1 h(-)(1).

Background Despite the succes story of therapeutic monoclonal antibodies (mAbs), a medical need remains to improve their efficacy. One possibility to achieve this is to modulate important effector functions such as the antibody dependent cellular cytotoxicity (ADCC). The advantage of highly active biotherapeutic molecules is apart from the enhanced efficacy the reduction of side effects due to lower administered doses. Furthermore, these therapeutic antibodies may enable treatment of current nonresponders, e.g. patients with low antigen bearing tumors. Enhancement of the effector functions of antibodies can be achieved either by directly mutating the antibody’s amino acid sequence or by modifying its glycosylation pattern, e.g. by using a novel host cell line able to attach a desired glycostructure to the product. The latter approach has the advantage of not impacting the antibody structure itself, thereby avoiding negative effects on the PK/PD of the molecule. During the last decade it has been shown that antibodies with a reduced level of glycan fucosylation are much more potent in mediating ADCC, a mode of action particularly relevant for cancer therapeutics. Therefore, defucosylated antibodies are of major interest for biotherapeutics developers. To produce such antibodies, Boehringer Ingelheim has inlicensed the GlymaxX system from ProBioGen, Germany. This technology utilises the bacterial protein RMD (GDP-6-deoxy-D-lyxo-4-hexulose reductase) which, when stably integrated into host cell lines, inhibits fucose de-novo biosynthesis. The enzyme deflects the fucosylation pathway by turning an intermediate (GDP-4-Keto-6-Deoxymannose) into GDP-Rhamnose, a sugar that cannot be metabolised by CHO cells. As a consequence, recombinant antibodies generated by such host cells exhibit reduced glycan fucosylation and 20100 fold higher ADCC activity. Here, we show the establishment of a new host cell line, termed BI-HEXGlymaxX which is capable of producing highly active therapeutic antibodies. We furthermore present data on the cell line properties concerning cell culture performance (e.g. titer, growth, transfection efficiency), process robustness and product quality reproducibility.