Jens Fricke

Investigation of the interactions of critical scale-up parameters (pH, pO2 and pCO2) on CHO batch performance and critical quality attributes.

Understanding process parameter interactions and their effects on mammalian cell cultivations is an essential requirement for robust process scale-up. Furthermore, knowledge of the relationship between the process parameters and the product critical quality attributes (CQAs) is necessary to satisfy quality by design guidelines. So far, mainly the effect of single parameters on CQAs was investigated. Here, we present a comprehensive study to investigate the interactions of scale-up relevant parameters as pH, pO2 and pCO2 on CHO cell physiology, process performance and CQAs, which was based on design of experiments and extended product quality analytics. The study used a novel control strategy in which process parameters were decoupled from each other, and thus allowed their individual control at defined set points. Besides having identified the impact of single parameters on process performance and product quality, further significant interaction effects of process parameters on specific cell growth, specific productivity and amino acid metabolism could be derived using this method. Concerning single parameter effects, several monoclonal antibody (mAb) charge variants were affected by process pCO2 and pH. N-glycosylation analysis showed positive correlations between mAb sialylation and high pH values as well as a relationship between high mannose variants and process pH. This study additionally revealed several interaction effects as process pH and pCO2 interactions on mAb charge variants and N-glycosylation pattern. Hence, through our process control strategy and multivariate investigation, novel significant process parameter interactions and single effects were identified which have to be taken into account especially for process scale-up.

Prediction of filamentous process performance attributes by CSL quality assessment using mid-infrared spectroscopy and chemometrics

Every biopharmaceutical production process aims for control strategies to achieve process robustness in order to ensure consistent product quality. Process variability can origin from process parameters, the biological nature as well as from high lot-to-lot variability of raw materials. In filamentous processes raw materials with very complex matrices, such as corn steep liquor (CSL), are used, which are especially challenging to characterize. In this study, CSL was characterized in detail for its ingredients presenting an overall composition of its matrix of 50 analyzed components (19 amino acids, 5 organic acids, 8 reducing sugars, 7 water-soluble vitamins and 11 trace elements/minerals) in order to facilitate analytical reduction to fingerprinting methods FT-MIR was evaluated as fast and non-destructive spectroscopic fingerprinting method for adequate assessment of CSL quality. Feasibility of this method was shown by the correlation of certain bands in the spectra to substance groups present in CSL, such as the Amide I and II band and amino acids, respectively. Additionally, applicability of FT-MIR could be shown for classification of different CSL lots differing in provider and corn quality as well as for predictability of process performance attributes. The latter was demonstrated on a fed-batch filamentous fungi process for the production of antibiotics. By multivariate data analysis, it could be shown that CSL quality assessment via FT-MIR can be used for the prediction of maximal biomass generated in the process, with a correlation coefficient R2 of 0.964, as well as for the prediction of an unwanted impurity. The combination of a fast and easy method for CSL quality assessment and correlations of this quality with process performance attributes may facilitate the establishment of a risk-based acceptance criteria for raw material quality release of CSL. As CSL is a frequent used raw material, we believe that this method will also be useful for other processes and that CSL quality assessment is of high relevance in academia and industry.

The impact of pH inhomogeneities on CHO cell physiology and fed‐batch process performance – two‐compartment scale‐down modelling and intracellular pH excursion

Due to high mixing times and base addition from top of the vessel, pH inhomogeneities are most likely to occur during large-scale mammalian processes. The goal of this study was to set-up a scale-down model of a 10-12 m3 stirred tank bioreactor and to investigate the effect of pH perturbations on CHO cell physiology and process performance. Short-term changes in extracellular pH are hypothesized to affect intracellular pH and thus cell physiology. Therefore, batch fermentations, including pH shifts to 9.0 and 7.8, in regular one-compartment systems are conducted. The short-term adaption of the cells intracellular pH are showed an immediate increase due to elevated extracellular pH. With this basis of fundamental knowledge, a two-compartment system is established which is capable of simulating defined pH inhomogeneities. In contrast to state-of-the-art literature, the scale-down model is included parameters (e.g. volume of the inhomogeneous zone) as they might occur during large-scale processes. pH inhomogeneity studies in the two-compartment system are performed with simulation of temporary pH zones of pH 9.0. The specific growth rate especially during the exponential growth phase is strongly affected resulting in a decreased maximum viable cell density and final product titer. The gathered results indicate that even short-term exposure of cells to elevated pH values during large-scale processes can affect cell physiology and overall process performance. In particular, it could be shown for the first time that pH perturbations, which might occur during the early process phase, have to be considered in scale-down models of mammalian processes.

Generic biomass estimation methods targeting physiologic process control in induced bacterial cultures

Advanced bioprocess development strategies focus on the control of physiological entities, which rely on accurate real‐time determination of the biomass concentration. Various methods have been proposed in literature but up to this date a comprehensive and differentiated comparison of biomass estimation approaches for early stage bioprocess development is missing. In this study, we compared hard sensor, soft‐sensor, and data‐driven approaches for real‐time biomass estimation in respect to accuracy, transferability, and costs. The outlined methods were tested with two different microbial strains and recombinant products using Escherichia coli. To investigate the applicability of the outlined methods, method performance was assessed in correspondence to metabolic activity. Based on statistical descriptors the methods were compared and discussed. The results indicate no significant impact of strain or biomass estimation approach on the measurement quality. The average relative error of 11–13% can be greatly reduced by over 85% combining the outlined methods by the means of weighted average. This approach proved to be highly robust even during highly dynamic process conditions of oscillating specific substrate uptake rates. Concluding, the combination of low cost first principle soft‐sensor approaches in combination with a hybrid soft‐sensor yields the best information‐to‐effort ratio.

A combination of HPLC and automated data analysis for monitoring the efficiency of high-pressure homogenization

BackgroundCell disruption is a key unit operation to make valuable, intracellular target products accessible for further downstream unit operations. Independent of the applied cell disruption method, each cell disruption process must be evaluated with respect to disruption efficiency and potential product loss. Current state-of-the-art methods, like measuring the total amount of released protein and plating-out assays, are usually time-delayed and involve manual intervention making them error-prone. An automated method to monitor cell disruption efficiency at-line is not available to date.ResultsIn the current study we implemented a methodology, which we had originally developed to monitor E. coli cell integrity during bioreactor cultivations, to automatically monitor and evaluate cell disruption of a recombinant E. coli strain by high-pressure homogenization. We compared our tool with a library of state-of-the-art methods, analyzed the effect of freezing the biomass before high-pressure homogenization and finally investigated this unit operation in more detail by a multivariate approach.ConclusionA combination of HPLC and automated data analysis describes a valuable, novel tool to monitor and evaluate cell disruption processes. Our methodology, which can be used both in upstream (USP) and downstream processing (DSP), describes a valuable tool to evaluate cell disruption processes as it can be implemented at-line, gives results within minutes after sampling and does not need manual intervention.

Impact of cell lysis on the description of cell growth and death in cell culture

The primary task of process development is a process design that guarantees product quality and maximizes product quantity. One part of the process development is the identification of critical process parameters. Especially in cell culture processes, unwanted cell damage as critical process parameter is still challenging in stirred tank reactors and needs therefore to be considered. Nevertheless, this topic and its effects on process performance are currently not well discussed and not verified in literature until now.

Impact of Glycerol as Carbon Source onto Specific Sugar and Inducer Uptake Rates and Inclusion Body Productivity in E. coli BL21(DE3)

The Gram-negative bacterium E. coli is the host of choice for a multitude of used recombinant proteins. Generally, cultivation is easy, media are cheap, and a high product titer can be obtained. However, harsh induction procedures using isopropyl β-d-1 thiogalactopyranoside as inducer are often referred to cause stress reactions, leading to a phenomenon known as “metabolic” or “product burden”. These high expressions of recombinant proteins mainly result in decreased growth rates and cell lysis at elevated induction times. Therefore, approaches tend to use “soft” or “tunable” induction with lactose and reduce the stress level of the production host. The usage of glucose as energy source in combination with lactose as induction reagent causes catabolite repression effects on lactose uptake kinetics and as a consequence reduced product titer. Glycerol—as an alternative carbon source—is already known to have positive impact on product formation when coupled with glucose and lactose in auto-induction systems, and has been referred to show no signs of repression when cultivated with lactose concomitantly. In recent research activities, the impact of different products on the lactose uptake using glucose as carbon source was highlighted, and a mechanistic model for glucose-lactose induction systems showed correlations between specific substrate uptake rate for glucose or glycerol (qs,C) and the maximum specific lactose uptake rate (qs,lac,max). In this study, we investigated the mechanistic of glycerol uptake when using the inducer lactose. We were able to show that a product-producing strain has significantly higher inducer uptake rates when being compared to a non-producer strain. Additionally, it was shown that glycerol has beneficial effects on viability of cells and on productivity of the recombinant protein compared to glucose.

Morphological analysis of the filamentous fungus Penicillium chrysogenum using flow cytometry—the fast alternative to microscopic image analysis

An important parameter in filamentous bioreactor cultivations is the morphology of the fungi, due to its interlink to productivity and its dependency on process conditions. Filamentous fungi show a large variety of morphological forms in submerged cultures. These range from dispersed hyphae, to interwoven mycelial aggregates, to denser hyphal aggregates, the so-called pellets. Depending on the objective function of the bioprocess, different characteristics of the morphology are favorable and need to be quantified accurately. The most common method to quantitatively characterize morphology is image analysis based on microscopy. This method is work intensive and time consuming. Therefore, we developed a faster, at-line applicable, alternative method based on flow cytometry. Within this contribution, this novel method is compared to microscopy for a penicillin production process. Both methods yielded in comparable distinction of morphological sub-populations and described their morphology in more detail. In addition to the appropriate quantification of size parameters and the description of the hyphal region around pellets, the flow cytometry method even revealed a novel compactness parameter for fungal pellets which is not accessible via light microscopy. Hence, the here presented flow cytometry method for morphological analysis is a fast and reliable alternative to common tools with some new insights in the pellet morphology, enabling at-line use in production environments.

Elevated pCO2 affects the lactate metabolic shift in CHO cell culture processes

The shift from lactate production to consumption in CHO cell metabolism is a key event during cell culture cultivations and is connected to increased culture longevity and final product titers. However, the mechanisms controlling this metabolic shift are not yet fully understood. Variations in lactate metabolism have been mainly reported to be induced by process pH and availability of substrates like glucose and glutamine. The aim of this study was to investigate the effects of elevated pCO2 concentrations on the lactate metabolic shift phenomena in CHO cell culture processes. In this publication, we show that at elevated pCO2 in batch and fed‐batch cultures, the lactate metabolic shift was absent in comparison to control cultures at lower pCO2 values. Furthermore, through metabolic flux analysis we found a link between the lactate metabolic shift and the ratio of NADH producing and regenerating intracellular pathways. This ratio was mainly affected by a reduced oxidative capacity of cultures at elevated pCO2. The presented results are especially interesting for large‐scale and perfusion processes where increased pCO2 concentrations are likely to occur. Our results suggest, that so far unexplained metabolic changes may be connected to increased pCO2 accumulation in larger scale fermentations. Finally, we propose several mechanisms through which increased pCO2 might affect the cell metabolism and briefly discuss methods to enable the lactate metabolic shift during cell cultivations.

Workflow for target-oriented parametrization of an enhanced mechanistic cell culture model†

The goal of this study is to develop a macroscopic mechanistic model describing growth and production within fed-batch cultivations of CHO cells. The model should be used for process characterization as well as for process monitoring including real-time parameter adaptations. The model proved to be able to describe a data-set of 40 processes differing in clones, scales, and process conditions with a normalized root mean square error of approximately 10%. However, due to limited parameter identifiability and limited knowledge about physiologically meaningful parameter values, a broad range of parameters could describe the data with similar quality. This hampered comparison of the model parameters as well as their real-time estimation. Therefore an iterative workflow combining techniques like sensitivity and identifiability analysis, analysis of the specific rates as well as structural adaptations of the parameter space is developed. By applying it the parameter variability could be reduced by 80% with similar predictive power as the original parameters. Summing up, based on a mechanistic CHO model, a generic and transferrable workflow is created for target-oriented parameter estimation in case of limited parameter identifiability. Finally, we suggest a methodology, which fits ideally into the frame of Process Analytical Technology aiming to increase process understanding.