Lipidomics for robust high performance process development

As the biopharmaceutical industry reduces the risk of potential contaminations by adventitious agents and increases process yields, high performance cell culture processes have been developed that rely on animal-free peptide-free, protein-free chemically defined and lipid-free media. These processes rely on cell lines that have been adapted to these lipid-free production conditions and have developed very effective lipid production capacities. These lipid-production capacities result in new challenges in the harvest and purification steps such as filterability, ability to clean resins and resin reuse. This oral presentation will show case how lipidomics can provide insights and opportunities to control the interactions between high performance bioreactor production processes, harvest conditions and purification. Results obtained across large scale production processes of three different monoclonal antibodies will be displayed. The importance of controlling lipid biosynthesis and the presence of lipids in the cell culture fluid prior to affinity capture chromatography will be discussed. Three different control strategies will be showcased and their pros and cons in terms of process yields, robustness of the harvest and impact on the purification process post-harvest explaine

Curation of a CHO DG44 genome scale model and application to support cell culture development process

Genome scale models (GSM) have become a useful tool to connect different omics dataset into a single computational framework, thus giving a good overview of the flux distribution and metabolites interconnections in a specific environmental condition. A community genome-scale metabolic network reconstruction of Cricetulus griseus and cell line specific models have been recently developed 1. The main objectives with the use of the published CHO DG44 model were to enhance industrial bioprocess performance by suggesting genetic or metabolic targets, as well as strategies for medium optimization, and by bringing more fundamental knowledge about CHO cell metabolism. In a first step, some corrections were required in order to improve the biological relevancy of the predicted intracellular fluxes. The optimization method chosen was Parsimonious Flux Balance Analysis, based on the assumption that the cell is using a minimum amount of enzymes to reach a maximized objective value, under steady state. As the predictions were generating a lot of infeasible cycles, silencing of amino acid transporters that do not involve protons or sodium in the model allowed to reduce the incoming flow of amino acids and led to disappearance of infeasible cycles in the flux distribution solution. Four reactions involved in central carbon metabolism were manually added in the model, and some reactions were removed from the model to improve predictions such as the cytosolic enzyme fumarase, mainly localized in mitochondria, or L-asparaginase which is not reported to be present in CHO cells. As initial predictions for lactate production rate were overestimated compared to experimental measurements, the assumption of lipid accumulation during cell culture was added in the form of a constraint for a minimal level of triglyceride synthesis in the model (Figure 1). In a second step, the accuracy of the prediction from the curated model was tested with three independent data set obtained from a fed-batch experiment with a CHO DG44 cell line producing a monoclonal antibody in 2L stirred tank glass bioreactors. For modelling with GSM, pre-calculated input values are required in order to constraint the model with the environmental conditions, and thus to give a prediction that is representative of the experimental condition. Uptake rates of essential nutrients initially present in extracellular medium and consumed as the cells grow were used as the limit for a maximum uptake rate in the model. The objective function chosen was maximization of growth rate or maximization of specific productivity. As a result, correlation coefficients between experimental value and prediction indicate a good fit for growth rate and specific productivity (Qp) (Figure 2). Predicted amino acid consumption rates were comparable to experimental values, indicating the accuracy of the predicted stoichiometric requirements for cell growth and energy, except for 19% of the fluxes studied (Figure 3). As the extracellular flux values seem to correlate with experimental data, prediction of intracellular flux rates were analyzed at different timepoints of the culture, showing the activation of multiple metabolic pathways. Based on the results obtained, optimization of cell culture medium was performed to identify the limiting metabolites during the process that could lead to an increased growth rate and Qp. Please click Additional Files below to see the full abstract

Novel modeling methodology to predict product quality and cell culture performance in fed-batch and perfusion cultures

The acceleration of biopharmaceutical process development is difficult when traditional experience-based sequential approaches are used. As a result, fully optimized and well understood cell culture processes prior to scale-up are rare. Here we show that an accurate, scalable and simple model able to predict cell growth, cell metabolism, titer and some product quality attributes will significantly accelerate process development, improve process development outcomes and reduce development and production costs. Please click Additional Files below to see the full abstract

Predictive macroscopic models of cell growth, metabolism and monoclonal antibody production of fed-batch processes at various scales

Recently, the pharmaceutical industry is increasingly focusing on early drug development which comes with increasing constraints to accelerate process development, reduce costs and demonstrate a deep understanding cell culture processes. However, cellular metabolism is very complex and by far not fully understood. Cells can be cultivated in various types of bioreactors applying sophisticated feeding strategies mostly based on experience and series of experiments. Modern systems biology promises modeling of such processes on the basis of a system-wide understanding of cellular processes but is still unable to deliver predictive models in due time at reasonable cost. Practically applicable, predictive models are highly demanded in industry for the purpose of process optimization and control. To this end, we developed a systematic methodology for metabolic and cell growth modeling that is directly applicable in an industrial environment. We demonstrate that the models developed are able to predict a wide range of new experimental cell culture conditions. Please click Additional Files below to see the full abstract

A novel mammalian expression system derived from components coordinating nicotine degradation in arthrobacter nicotinovorans pAO1

We describe the design and detailed characterization of 6-hydroxy-nicotine (6HNic)-adjustable transgene expression (NICE) systems engineered for lentiviral transduction and in vivo modulation of angiogenic responses. Arthrobacter nicotinovorans pAO1 encodes a unique catabolic machinery on its plasmid pAO1, which enables this Gram-positive soil bacterium to use the tobacco alkaloid nicotine as the exclusive carbon source. The 6HNic-responsive repressor-operator (HdnoR-ONIC) interaction, controlling 6HNic oxidase production in A.nicotinovorans pAO1, was engineered for generic 6HNic-adjustable transgene expression in mammalian cells. HdnoR fused to different transactivation domains retained its ONIC-binding capacity in mammalian cells and reversibly adjusted transgene transcription from chimeric ONIC-containing promoters (PNIC; ONIC fused to a minimal eukaryotic promoter [Pmin]) in a 6HNic-responsive manner. The combination of transactivators containing various transactivation domains with promoters differing in the number of operator modules as well as in their relative inter-ONIC and/or ONIC-Pmin spacing revealed steric constraints influencing overall NICE regulation performance in mammalian cells. Mice implanted with microencapsulated cells engineered for NICE-controlled expression of the human glycoprotein secreted placental alkaline phosphatase (SEAP) showed high SEAP serum levels in the absence of regulating 6HNic. 6HNic was unable to modulate SEAP expression, suggesting that this nicotine derivative exhibits control-incompatible pharmacokinetics in mice. However, chicken embryos transduced with HIV-1-derived self-inactivating lentiviral particles transgenic for NICE-adjustable expression of the human vascular endothelial growth factor 121 (VEGF121) showed graded 6HNic response following administration of different 6HNic concentrations. Owing to the clinically inert and highly water-soluble compound 6HNic, NICE-adjustable transgene control systems may become a welcome alternative to available drug-responsive homologs in basic research, therapeutic cell engineering and biopharmaceutical manufacturin

A novel mammalian expression system derived from components coordinating nicotine degradation in arthrobacter nicotinovorans pAO1

We describe the design and detailed characterization of 6-hydroxy-nicotine (6HNic)-adjustable transgene expression (NICE) systems engineered for lentiviral transduction and in vivo modulation of angiogenic responses. Arthrobacter nicotinovorans pAO1 encodes a unique catabolic machinery on its plasmid pAO1, which enables this Gram-positive soil bacterium to use the tobacco alkaloid nicotine as the exclusive carbon source. The 6HNic-responsive repressor-operator (HdnoR-O(NIC)) interaction, controlling 6HNic oxidase production in A.nicotinovorans pAO1, was engineered for generic 6HNic-adjustable transgene expression in mammalian cells. HdnoR fused to different transactivation domains retained its O(NIC)-binding capacity in mammalian cells and reversibly adjusted transgene transcription from chimeric O(NIC)-containing promoters (P(NIC); O(NIC) fused to a minimal eukaryotic promoter [P(min)]) in a 6HNic-responsive manner. The combination of transactivators containing various transactivation domains with promoters differing in the number of operator modules as well as in their relative inter-O(NIC) and/or O(NIC)-P(min) spacing revealed steric constraints influencing overall NICE regulation performance in mammalian cells. Mice implanted with microencapsulated cells engineered for NICE-controlled expression of the human glycoprotein secreted placental alkaline phosphatase (SEAP) showed high SEAP serum levels in the absence of regulating 6HNic. 6HNic was unable to modulate SEAP expression, suggesting that this nicotine derivative exhibits control-incompatible pharmacokinetics in mice. However, chicken embryos transduced with HIV-1-derived self-inactivating lentiviral particles transgenic for NICE-adjustable expression of the human vascular endothelial growth factor 121 (VEGF(121)) showed graded 6HNic response following administration of different 6HNic concentrations. Owing to the clinically inert and highly water-soluble compound 6HNic, NICE-adjustable transgene control systems may become a welcome alternative to available drug-responsive homologs in basic research, therapeutic cell engineering and biopharmaceutical manufacturing