Investigation of cell line specific responses to pH inhomogeneity and consequences for process design

With increasing bioreactor volumes, the mixing time of the reactor increases as well, which creates an inhomogeneous environment for the cells. This can result in impaired process performance in large‐scale production reactors. Particularly the addition of base through the reactor headspace can be problematic, since it creates an area, where cells are repeatedly exposed to an increased pH. The aim of this study is to simulate this large‐scale phenomenon at lab‐scale and investigate its impact. Two different cell lines were exposed to pH amplitudes of a maximal magnitude of 0.05 units (pH of 6.95). Both cell lines showed similar responses, like decreased viable cell counts, but unaffected lactate levels. However, cell line B showed an initially increased specific productivity in response to the introduced amplitudes, whereas cell line A showed a consistently lower specific productivity. Furthermore, the time point at which base addition is started influences the impact, which pH amplitudes have on process performance. When pH control was started earlier in the process, maximal viable cell counts decreased and the lactate metabolic shift was less pronounced. These results show that the potential negative impact of pH amplitudes can be minimized by strategic process design.     

Development,characterization, and application of a 2‐Compartment system to investigate the impact of pH inhomogeneities in large‐scale CHO‐based processes

Large‐scale bioreactors for the production of monoclonal antibodies reach volumes of up to 25 000 L. With increasing bioreactor size, mixing is however affected negatively, resulting in the formation of gradients throughout the reactor. These gradients can adversely affect process performance at large scale. Since mammalian cells are sensitive to changes in pH, this study investigated the effects of pH gradients on process performance. A 2‐Compartment System was established for this purpose to expose only a fraction of the cell population to pH excursions and thereby mimicking a large‐scale bioreactor. Cells were exposed to repeated pH amplitudes of 0.4 units (pH 7.3), which resulted in decreased viable cell counts, as well as the inhibition of the lactate metabolic shift. These effects were furthermore accompanied by increased absolute lactate levels. Continuous assessment of molecular attributes of the expressed target protein revealed that subunit assembly or N‐glycosylation patterns were only slightly influenced by the pH excursions. The exposure of more cells to the same pH amplitudes further impaired process performance, indicating this is an important factor, which influences the impact of pH inhomogeneity. This knowledge can aid in the design of pH control strategies to minimize the effects of pH inhomogeneity in large‐scale bioreactors.     

Characterization of TAP Ambr 250 disposable bioreactors,as a reliable scale‐down model for biologics process development

Demands for development of biological therapies is rapidly increasing, as is the drive to reduce time to patient. In order to speed up development, the disposable Automated Microscale Bioreactor (Ambr 250) system is increasingly gaining interest due to its advantages, including highly automated control, high throughput capacity, and short turnaround time. Traditional early stage upstream process development conducted in 2 ‐ 5 L bench‐top bioreactors requires high foot‐print, and running cost. The establishment of the Ambr 250 as a scale‐down model leads to many benefits in process development. In this study, a comprehensive characterization of mass transfer coefficient (k_La) in the Ambr 250 was conducted to define optimal operational conditions. Scale‐down approaches, including dimensionless volumetric flow rate (vvm), power per unit volume (P/V) and k_La have been evaluated using different cell lines. This study demonstrates that the Ambr 250 generated comparable profiles of cell growth and protein production, as seen at 5‐L and 1000‐L bioreactor scales, when using k_La as a scale‐down parameter. In addition to mimicking processes at large scales, the suitability of the Ambr 250 as a tool for clone selection, which is traditionally conducted in bench‐top bioreactors, was investigated. Data show that cell growth, productivity, metabolite profiles, and product qualities of material generated using the Ambr 250 were comparable to those from 5‐L bioreactors. Therefore, Ambr 250 can be used for clone selection and process development as a replacement for traditional bench‐top bioreactors minimizing resource utilization during the early stages of development in the biopharmaceutical industry. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:478–489, 2017     

Process adapted calibration improves fluorometric pH sensor precision in sophisticated fermentation processes

Miniaturization and automation have become increasingly popular in bioprocess development in recent years, enabling rapid high‐throughput screening and optimization of process conditions. In addition, advances in the bioprocessing industry have led to increasingly complex process designs, such as pH and temperature shifts, in microbial fed‐batch fermentations for optimal soluble protein expression in a range of hosts. However, in order to develop an accurate scale‐down model for bioprocess screening and optimization, small‐scale bioreactors must be able to accurately reproduce these complex process designs. Monitoring methods, such as fluorometric‐based pH sensors, provide elegant solutions for the miniaturization of bioreactors, however, previous research suggests that the intrinsic fluorescence of biomass alters the sigmoidal calibration curve of fluorometric pH sensors, leading to inaccurate pH control. In this article, we present results investigating the impact of biomass on the accuracy of a commercially available fluorometric pH sensor. Subsequently, we present our calibration methodology for more precise online measurement and provide recommendations for improved pH control in sophisticated fermentation processes.     

Scale‐down simulators for mammalian cell culture as tools to access the impact of inhomogeneities occurring in large‐scale bioreactors

During the scale‐up of a bioprocess, not all characteristics of the process can be kept constant throughout the different scales. This typically results in increased mixing times with increasing reactor volumes. The poor mixing leads in turn to the formation of concentration gradients throughout the reactor and exposes cells to varying external conditions based on their location in the bioreactor. This can affect process performance and complicate process scale‐up. Scale‐down simulators, which aim at replicating the large‐scale environment, expose the cells to changing environmental conditions. This has the potential to reveal adaptation mechanisms, which cells are using to adjust to rapidly fluctuating environmental conditions and can identify possible root causes for difficulties maintaining similar process performance at different scales. This understanding is of utmost importance in process validation. Additionally, these simulators also have the potential to be used for selecting cells, which are most robust when encountering changing extracellular conditions. The aim of this review is to summarize recent work in this interesting and promising area with the focus on mammalian bioprocesses, since microbial processes have been extensively reviewed.     

Development of a small-scale bioreactor: application to in vivo NMR measurement

A perfused bioreactor allowing in vivo NMR measurement was developed and validated for Eschscholtzia californica cells. The bioreactor was made of a 10-mm NMR tube. NMR measurement of the signal-to-noise ratio was optimized using a sedimented compact bed of cells that were retained in the bioreactor by a supporting filter. Liquid medium flow through the cell bed was characterized from a mass balance on oxygen and a dispersive hydrodynamic model. Cell bed oxygen demand for 4 h perfusion required a minimal medium flow rate of 0.8 mL/min. Residence time distribution assays at 0.8-2.6 mL/min suggest that the cells are subjected to a uniform nutrient environment along the cell bed. Cell integrity was maintained for all culture conditions since the release of intracellular esterases was not significant even after 4 h of perfusion. In vivo NMR was performed for (31)P NMR and the spectrum can be recorded after only 10 min of spectral accumulation (500 scans) with peaks identified as G-6P, F-6P, cytoplasmic Pi, vacuolar Pi, ATP(gamma) and ADP(beta), ATP(alpha) and ADP(alpha), NADP and NDPG, NDPG and ATP(beta). Cell viability was shown to be maintained as (31)P chemical shifts were constant with time for all the identified nuclei, thus suggesting constant intracellular pH.     

A novel in vitro pharmacokinetic/pharmacodynamic model based on two-compartment open model used to simulate serum drug concentration-time profiles

An in vitro pharmacokinetic/pharmacodynamic perfusion model that simulates a two-compartment open model of serum drug concentration-time profiles following intravenous bolus injection and infusion was developed and mathematically described. In the present apparatus model, flow was kept in a one-way mode to avoid liquid traffic, and the washout effect seen in dilution models was overcome by embedding the tested bacteria in low melting point agarose gel. The validity of the equations and the reproducibility of the apparatus model were ascertained by simulating the concentration-time profiles of cefazolin and fosfomycin by substitution of their pharmacokinetic parameters obtained from humans for the equations. An empirical regimen 1X(q24h) of 1 g with cefazolin administered by intravenous infusion effectively killed a Staphylococcus aureus strain. The same regimen with fosfomycin produced a marked kill-curve with a fosfomycin-susceptible enterohaemorrhagic Escherichia coli O157:H7, whereas considerable regrowth was observed with a resistant strain. These results indicated that the present model was able to provide a convenient and reliable method for evaluating the efficacy of antimicrobial agents administered by intravenous infusion.     

Application of microelectrode technique to measure pH and oxidoreduction potential gradients in gelled systems as model food

A microelectrode system is used in order to simultaneously measure pH and oxidoreduction potential (Eh) gradients developed during growth by Escherichia coli and Lactobacillus plantarum immobilized in gelled media used as model food. Unlike E. coli, L. plantarum steadily decreased medium pH independently of depth of measurement and time of incubation. Both bacteria brought about the creation of an Eh gradient throughout the gelled medium. This gradient was much more important for E. coli (700 mV) than for L. plantarum (80 mV) but more transitory.     

Scale-up from shake flasks to fermenters in batch and continuous mode with Corynebacterium glutamicum on lactic acid based on oxygen transfer and pH

Scale-up from shake flasks to fermenters has been hampered by the lack of knowledge concerning the influence of operating conditions on mass transfer, hydromechanics, and power input. However, in recent years the properties of shake flasks have been described with empirical models. A practical scale-up strategy for everyday use is introduced for the scale-up of aerobic cultures from shake flasks to fermenters in batch and continuous mode. The strategy is based on empirical correlations of the volumetric mass transfer coefficient (k(L) a) and the pH. The accuracy of the empirical k(L) a correlations and the assumptions required to use these correlations for an arbitrary biological medium are discussed. To determine the optimal pH of the culture medium a simple laboratory method based on titration curves of the medium and a mechanistic pH model, which is solely based on the medium composition, is applied. The effectiveness of the scale-up strategy is demonstrated by comparing the behavior of Corynebacterium glutamicum on lactic acid in shake flasks and fermenters in batch and continuous mode. The maximum growth rate (micro(max) = 0.32 h(-1)) and the oxygen substrate coefficient (Y O2 /S= 0.0174 mol/l) of C. glutamicum on lactic acid were equal for shake flask, fermenter, batch, and continuous cultures. The biomass substrate yield was independent of the scale, but was lower in batch cultures (Y(X/S) = 0.36 g/g) than in continuous cultures (Y(X/S) = 0.45 g/g). The experimental data (biomass, respiration, pH) could be described with a simple biological model combined with a mechanistic pH model.     

Identifyability measures to select the parameters to be estimated in a solid‐state fermentation distributed parameter model

Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid‐state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905–917, 2016     

Disregarding the edaphic dimension in species distribution models leads to the omission of crucial spatial information under climate change: the case of Quercus pubescens in France

Species distribution modelling is an easy, persuasive and useful tool for anticipating species distribution shifts under global change. Numerous studies have used only climate variables to predict future potential species range shifts and have omitted environmental factors important for determining species distribution. Here, we assessed the importance of the edaphic dimension in the niche‐space definition of Quercus pubescens and in future spatial projections under global change over the metropolitan French forest territory. We fitted two species distribution models (SDM) based on presence/absence data (111 013 plots), one calibrated from climate variables only (mean temperature of January and climatic water balance of July) and the other one from both climate and edaphic (soil pH inferred from plants) variables. Future predictions were conducted under two climate scenarios (PCM B2 and HadCM3 A2) and based on 100 simulations using a cellular automaton that accounted for seed dispersal distance, landscape barriers preventing migration and unsuitable land cover. Adding the edaphic dimension to the climate‐only SDM substantially improved the niche‐space definition of Q. pubescens, highlighting an increase in species tolerance in confronting climate constraints as the soil pH increased. Future predictions over the 21st century showed that disregarding the edaphic dimension in SDM led to an overestimation of the potential distribution area, an underestimation of the spatial fragmentation of this area, and prevented the identification of local refugia, leading to an underestimation of the northward shift capacity of Q. pubescens and its persistence in its current distribution area. Spatial discrepancies between climate‐only and climate‐plus‐edaphic models are strengthened when seed dispersal and forest fragmentation are accounted for in predicting a future species distribution area. These discrepancies highlight some imprecision in spatial predictions of potential distribution area of species under climate change scenarios and possibly wrong conclusions for conservation and management perspectives when climate‐only models are used.