Study on the development and integration of 3D‐printed optics in small‐scale productions of single‐use cultivation vessels

Integrating optical sensors and 3D‐printed optics into single‐use (SU) cultivation vessels for customized, tailor‐made equipment could be a next big step in the bioreactor and screening platform development enabling online bioprocess monitoring. Many different parameters such as pH, oxygen, carbon dioxide and optical density (OD) can be monitored more easily using online measuring instruments compared to offline sampling. Space‐saving integrated sensors in combination with adapted optics such as prisms open up vastly new possibilities to precisely guide light through SU vessels. This study examines how optical prisms can be 3D‐printed with a 3D‐inkjet printer, modified and then evaluated in a custom made optical bench. The prisms are coated or bonded with thin cover glasses. For the examination of reflectance performance and conformity prisms are compared on the basis of measured characteristics of a conventional glass prism. In addition, the most efficient and reproducible prism geometry and modification technique is applied to a customized 3D‐printed cultivation vessel. The vessel is evaluated on a commercial sensor‐platform, a shake flask reader (SFR) vario, to investigate its sensing‐characteristics while monitoring scattered light with the turbidity standard formazine and a cell suspension of Saccharomyces cerevisiae as model organism. It is demonstrated that 3D‐printed prisms can be used in combination with commercial scattered light sensor‐platforms to determine OD of a microbial culture and that a 3D‐printed unibody design with integrated optics in a cultivation vessel is feasible. In the range of OD₆₀₀ 0–1.16 rel.AU a linear correlation between sensor amplitude and offline determined OD can be achieved. Thus, enabling for the first time a measurement of low cell densities with the SFR vario platform. Moreover, sensitivity is also at least three times higher compared to the commonly used method.     

A predictive high‐throughput scale‐down model of monoclonal antibody production in CHO cells

Multi‐factorial experimentation is essential in understanding the link between mammalian cell culture conditions and the glycoprotein product of any biomanufacturing process. This understanding is increasingly demanded as bioprocess development is influenced by the Quality by Design paradigm. We have developed a system that allows hundreds of micro‐bioreactors to be run in parallel under controlled conditions, enabling factorial experiments of much larger scope than is possible with traditional systems. A high‐throughput analytics workflow was also developed using commercially available instruments to obtain product quality information for each cell culture condition. The micro‐bioreactor system was tested by executing a factorial experiment varying four process parameters: pH, dissolved oxygen, feed supplement rate, and reduced glutathione level. A total of 180 micro‐bioreactors were run for 2 weeks during this DOE experiment to assess this scaled down micro‐bioreactor system as a high‐throughput tool for process development. Online measurements of pH, dissolved oxygen, and optical density were complemented by offline measurements of glucose, viability, titer, and product quality. Model accuracy was assessed by regressing the micro‐bioreactor results with those obtained in conventional 3 L bioreactors. Excellent agreement was observed between the micro‐bioreactor and the bench‐top bioreactor. The micro‐bioreactor results were further analyzed to link parameter manipulations to process outcomes via leverage plots, and to examine the interactions between process parameters. The results show that feed supplement rate has a significant effect (P < 0.05) on all performance metrics with higher feed rates resulting in greater cell mass and product titer. Culture pH impacted terminal integrated viable cell concentration, titer and intact immunoglobulin G titer, with better results obtained at the lower pH set point. The results demonstrate that a micro‐scale system can be an excellent model of larger scale systems, while providing data sets broader and deeper than are available by traditional methods. Biotechnol. Bioeng. 2009; 104: 1107–1120. © 2009 Wiley Periodicals, Inc.     

Downscaling screening cultures in a multifunctional bioreactor array-on-a-chip for speeding up optimization of yeast-based lactic acid bioproduction

A key challenge for bioprocess engineering is the identification of the optimum process conditions for the production of biochemical and biopharmaceutical compounds using prokaryotic as well as eukaryotic cell factories. Shake flasks and bench-scale bioreactor systems are still the golden standard in the early stage of bioprocess development, though they are known to be expensive, time-consuming, and labor-intensive as well as lacking the throughput for efficient production optimizations. To bridge the technological gap between bioprocess optimization and upscaling, we have developed a microfluidic bioreactor array to reduce time and costs, and to increase throughput compared with traditional lab-scale culture strategies. We present a multifunctional microfluidic device containing 12 individual bioreactors (V_t = 15 µl) in a 26 mm × 76 mm area with in-line biosensing of dissolved oxygen and biomass concentration. Following initial device characterization, the bioreactor lab-on-a-chip was used in a proof-of-principle study to identify the most productive cell line for lactic acid production out of two engineered yeast strains, evaluating whether it could reduce the time needed for collecting meaningful data compared with shake flasks cultures. Results of the study showed significant difference in the strains' productivity within 3 hr of operation exhibiting a 4- to 6-fold higher lactic acid production, thus pointing at the potential of microfluidic technology as effective screening tool for fast and parallelizable industrial bioprocess development.     

Rational optimization of culture conditions for the most efficient ethanol production in Scheffersomyces stipitis using design of experiments

Optimization of culture parameters for achieving the most efficient ethanol fermentation is challenging due to multiple variables involved. Here we presented a rationalized methodology for multi‐variables optimization through the design of experiments DoE approach. Three critical parameters, pH, temperature, and agitation speed, affecting ethanol fermentation in S. stipitis was investigated. A predictive model showed that agitation speed significantly affected ethanol synthesis. Reducing pH and temperature also improved ethanol production. The model identified the optimum culture conditions for the most efficient ethanol production with the yield and productivity of 0.46 g/g and 0.28 g/l h, respectively, which is consistent with experimental observation. The results also indicated the scalability of the model from shake flask to bioreactor. Thus, DoE is a promising tool permitting the rapid establishment of culture conditions for the most efficient ethanol fermentation in S. stipitis. The approach could be useful to reduce process development time in lignocellulosic ethanol industry. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2012     

Application of high‐throughput mini‐bioreactor system for systematic scale‐down modeling,process characterization,and control strategy development

High‐throughput systems and processes have typically been targeted for process development and optimization in the bioprocessing industry. For process characterization, bench scale bioreactors have been the system of choice. Due to the need for performing different process conditions for multiple process parameters, the process characterization studies typically span several months and are considered time and resource intensive. In this study, we have shown the application of a high‐throughput mini‐bioreactor system viz. the Advanced Microscale Bioreactor (ambr15^TM), to perform process characterization in less than a month and develop an input control strategy. As a pre‐requisite to process characterization, a scale‐down model was first developed in the ambr system (15 mL) using statistical multivariate analysis techniques that showed comparability with both manufacturing scale (15,000 L) and bench scale (5 L). Volumetric sparge rates were matched between ambr and manufacturing scale, and the ambr process matched the pCO₂ profiles as well as several other process and product quality parameters. The scale‐down model was used to perform the process characterization DoE study and product quality results were generated. Upon comparison with DoE data from the bench scale bioreactors, similar effects of process parameters on process yield and product quality were identified between the two systems. We used the ambr data for setting action limits for the critical controlled parameters (CCPs), which were comparable to those from bench scale bioreactor data. In other words, the current work shows that the ambr15^TM system is capable of replacing the bench scale bioreactor system for routine process development and process characterization. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1623–1632, 2015     

Bioprocess development for endospore production by Bacillus coagulans using an optimized chemically defined medium

Bacillus coagulans is a promising probiotic, because it combines probiotic properties of Lactobacillus and the ability of Bacillus to form endospores. Due to this hybrid relationship, cultivation of this organism is challenging. As the probiotics market continues to grow, there is a new focus on the production of these microorganisms. In this work, a strain-specific bioprocess for B. coagulans was developed to support growth on one hand and ensure sporulation on the other hand. This circumstance is not trivial, since these two metabolic states are contrary. The developed bioprocess uses a modified chemically defined medium which was further investigated in a one-factor-at-a-time assay after adaptation. A transfer from the shake flask to the bioreactor was successfully demonstrated in the scope of this work. The investigated process parameters included temperature, agitation and pH-control. Especially the pH-control improved the sporulation in the bioreactor when compared to shake flasks. The bioprocess resulted in a sporulation efficiency of 80%–90%. This corresponds to a sevenfold increase in sporulation efficiency due to a transfer to the bioreactor with pH-control. Additionally, a design of experiment (DoE) was conducted to test the robustness of the bioprocess. This experiment validated the beforementioned sporulation efficiency for the developed bioprocess. Afterwards the bioprocess was then scaled up from a 1 L scale to a 10 L bioreactor scale. A comparable sporulation efficiency of 80% as in the small scale was achieved. The developed bioprocess facilitates the upscaling and application to an industrial scale, and can thus help meet the increasing market for probiotics.     

On-line glucose monitoring by near infrared spectroscopy during the scale up steps of mammalian cell cultivation process development

NIR spectroscopy is a non-destructive tool for in-situ, on-line bioprocess monitoring. One of its most frequent applications is the determination of metabolites during cultivation, especially glucose. Previous studies have usually investigated the applicability of Near Infrared (NIR) spectroscopy at one bioreactor scale but the effect of scale up was not explored. In this study, the complete scale up from shake flask (1 L) through 20 L, 100 L and 1000 L up to 5000 L bioreactor volume level was monitored with on-line NIR spectroscopy. The differences between runs and scales were examined using principal component analysis. The bioreactor runs were relatively similar regardless of scales but the shake flasks differed strongly from bioreactor runs. The glucose concentration throughout five 5000 L scale bioreactor runs were predicted by partial least squares regression models that were based on pre-processed spectra of bioreactor runs and combinations of them. The model that produced the lowest error of prediction (4.18 mM on a 29 mM concentration range) for all five runs in the prediction set was based on the combination of 20 L and 100 L data. This result demonstrated the capabilities and the limitations of an NIR system for glucose monitoring in mammalian cell cultivations.

     

Recent advances in microbial capture of hydrogen sulfide from sour gas via sulfur‐oxidizing bacteria

Biological desulfurization offers several remarkably environmental advantages of operation at ambient temperature and atmospheric pressure, no demand of toxic chemicals as well as the formation of biologically re‐usable sulfur (S⁰), which has attracted increasing attention compared to conventionally physicochemical approaches in removing hydrogen sulfide from sour gas. However, the low biomass of SOB, the acidification of process solution, the recovery of SOB, and the selectivity of bio‐S⁰ limit its industrial application. Therefore, more efforts should be made in the improvement of the BDS process for its industrial application via different research perspectives. This review summarized the recent research advances in the microbial capture of hydrogen sulfide from sour gas based on strain modification, absorption enhancement, and bioreactor modification. Several efficient solutions to limitations for the BDS process were proposed, which paved the way for the future development of BDS industrialization.     

Applicability of a single‐use bioreactor compared to a glass bioreactor for the fermentation of filamentous fungi and evaluation of the reproducibility of growth in pellet form

The implementation of single‐use technologies offers several major advantages, e.g. prevention of cross‐contamination, especially when spore‐forming microorganisms are present. This study investigated the application of a single‐use bioreactor in batch fermentation of filamentous fungus Penicillium sp. (IBWF 040‐09) from the Institute of Biotechnology and Drug Research (IBWF), which is capable of intracellular production of a protease inhibitor against parasitic proteases as a secondary metabolite. Several modifications to the SU bioreactor were suggested in this study to allow the fermentation in which the fungus forms pellets. Simultaneously, fermentations in conventional glass bioreactor were also conducted as reference. Although there are significant differences in the construction material and gassing system, the similarity of the two types of bioreactors in terms of fungal metabolic activity and the reproducibility of fermentations could be demonstrated using statistic methods. Under the selected cultivation conditions, growth rate, yield coefficient, substrate uptake rate, and formation of intracellular protease‐inhibiting substance in the single‐use bioreactor were similar to those in the glass bioreactor.     

Traces matter: Targeted optimization of monoclonal antibody N-glycosylation based on/by implementing automated high-throughput trace element screening

The use of high-throughput systems in cell culture process optimization offers various opportunities in biopharmaceutical process development. Here we describe the potential for acceleration and enhancement of product quality optimization and de novo bioprocess design regarding monoclonal antibody N-glycosylation by using an iterative statistical Design of Experiments (DoE) strategy based on our automated microtiter plate-based system for suspension cell culture. In our example, the combination of an initial screening of trace metal building blocks with a comprehensive DoE-based screening of 13 different trace elemental ions at three concentration levels in one run revealed most effective levers for N-glycan processing and biomass formation. Obtained results served to evaluate optimal concentration ranges and the right supplementation timing of relevant trace elements at shake flask and 2 L bioreactor scale. This setup identified manganese, copper, zinc, and iron as major factors. Manganese and copper acted as inverse key players in N-glycosylation, showing a positive effect of manganese and a negative effect of copper on glycan maturation in a zinc-dependent manner. Zinc and iron similarly improved cell growth and biomass formation. These findings allowed determining optimal concentration ranges for all four trace elements to establish control on desired product quality attributes regarding premature afucosylated and mature galactosylated glycan species. Our results demonstrates the power of combining robotics with DoE screening to enhance product quality optimization and to improve process understanding, thus, enabling targeted product quality control.     

Stress‐induced increase of monoclonal antibody production in CHO cells

Monoclonal antibodies (mAbs) are of great interest to the biopharmaceutical industry due to their widely used application as human therapeutic and diagnostic agents. As such, mAb require to exhibit human‐like glycolization patterns. Therefore, recombinant Chinese hamster ovary (CHO) cells are the favored production organisms; many relevant biopharmaceuticals are already produced by this cell type. To optimize the mAb yield in CHO DG44 cells a corelation between stress‐induced cell size expansion and increased specific productivity was investigated. CO₂ and macronutrient supply of the cells during a 12‐day fed‐batch cultivation process were tested as stress factors. Shake flasks (500 mL) and a small‐scale bioreactor system (15 mL) were used for the cultivation experiments and compared in terms of their effect on cell diameter, integral viable cell concentration (IVCC), and cell‐specific productivity. The achieved stress‐induced increase in cell‐specific productivity of up to 94.94.9%–134.4% correlates to a cell diameter shift of up to 7.34 μm. The highest final product titer of 4 g/L was reached by glucose oversupply during the batch phase of the process.     

Dynamic process conditions in bioprocess development

In this review, we summarise recent studies that purposefully employed dynamic conditions, such as shifts, pulses, ramps and oscillations, for fast physiological strain characterisation and bioprocess development. We show the broad applicability of dynamic conditions and the various objectives that can thereby be investigated in a short time. Dynamic processes reveal information about the analysed system faster than traditional strategies, like continuous cultivations, as process parameters can directly be linked to platform and product parameters. Furthermore, we demonstrate that dynamic operations can result in increased productivity and high product quality, making this strategy a valuable tool for bioprocess development. With this review, we would like to encourage bioprocess engineers to an increased use of dynamic conditions in bioprocess development.     

Identification of upstream culture conditions and harvest time parameters that affect host cell protein clearance

During early stage bioprocess development, characterizing interactions between unit operations is a key challenge. Such interactions include the release of host cell enzymes early in the process causing losses in product quality downstream. Using a CHO-expressed IgG1 system, the impact of cell culture duration was investigated using a 50 L bioreactor and performing scale-down protein A purification. While antibody titer doubled during the last week of culture, the post-protein A host cell protein (HCP) levels increased from 243 to 740 ppm. Effects of pH and temperature were then explored using fed-batch ambr250 bioreactors, and parameters enabling higher titers were linked to a decrease in post-protein A product purity. These trade-offs between titer and product quality were visualized using a window of operation. The downstream space was explored further by exposing shake flask material to shear representative of disc stack centrifugation, prior to purification, and by adding polishing chromatography. While product quality decreased with progressing cultivation, cells became more shear resistant. Polishing chromatography resulted in product fragmentation which increased fourfold from Day 10 to 24, adding constraint to achieving both efficient HCP clearance as well as high monomer purities. These examples highlight the importance of adopting integrated approaches to upstream and downstream development strategies to enable whole process optimization.     

Age‐dependent aneuploidy in mammalian oocytes instigated at the second meiotic division

Ageing severely affects the chromosome segregation process in human oocytes resulting in aneuploidy, infertility and developmental disorders. A considerable amount of segregation errors in humans are introduced at the second meiotic division. We have here compared the chromosome segregation process in young adult and aged female mice during the second meiotic division. More than half of the oocytes in aged mice displayed chromosome segregation irregularities at anaphase II, resulting in dramatically increased level of aneuploidy in haploid gametes, from 4% in young adult mice to 30% in aged mice. We find that the post‐metaphase II process that efficiently corrects aberrant kinetochore‐microtubule attachments in oocytes in young adult mice is approximately 10‐fold less efficient in aged mice, in particular affecting chromosomes that show small inter‐centromere distances at the metaphase II stage in aged mice. Our results reveal that post‐metaphase II processes have critical impact on age‐dependent aneuploidy in mammalian eggs.     

A hybrid mechanistic-empirical model for in silico mammalian cell bioprocess simulation

In cell culture processes cell growth and metabolism drive changes in the chemical environment of the culture. These environmental changes elicit reactor control actions, cell growth response, and are sensed by cell signaling pathways that influence metabolism. The interplay of these forces shapes the culture dynamics through different stages of cell cultivation and the outcome greatly affects process productivity, product quality, and robustness. Developing a systems model that describes the interactions of those major players in the cell culture system can lead to better process understanding and enhance process robustness. Here we report the construction of a hybrid mechanistic-empirical bioprocess model which integrates a mechanistic metabolic model with subcomponent models for cell growth, signaling regulation, and the bioreactor environment for in silico exploration of process scenarios. Model parameters were optimized by fitting to a dataset of cell culture manufacturing process which exhibits variability in metabolism and productivity. The model fitting process was broken into multiple steps to mitigate the substantial numerical challenges related to the first-principles model components. The optimized model captured the dynamics of metabolism and the variability of the process runs with different kinetic profiles and productivity. The variability of the process was attributed in part to the metabolic state of cell inoculum. The model was then used to identify potential mitigation strategies to reduce process variability by altering the initial process conditions as well as to explore the effect of changing CO₂ removal capacity in different bioreactor scales on process performance. By incorporating a mechanistic model of cell metabolism and appropriately fitting it to a large dataset, the hybrid model can describe the different metabolic phases in culture and the variability in manufacturing runs. This approach of employing a hybrid model has the potential to greatly facilitate process development and reactor scaling.     

Model-based workflow for scale-up of process strategies developed in miniaturized bioreactor systems

Miniaturized bioreactor (MBR) systems are routinely used in the development of mammalian cell culture processes. However, scale-up of process strategies obtained in MBR- to larger scale is challenging due to mainly non-holistic scale-up approaches. In this study, a model-based workflow is introduced to quantify differences in the process dynamics between bioreactor scales and thus enable a more knowledge-driven scale-up. The workflow is applied to two case studies with antibody-producing Chinese hamster ovary cell lines. With the workflow, model parameter distributions are estimated first under consideration of experimental variability for different scales. Second, the obtained individual model parameter distributions are tested for statistical differences. In case of significant differences, model parametric distributions are transferred between the scales. In case study I, a fed-batch process in a microtiter plate (4 ml working volume) and lab-scale bioreactor (3750 ml working volume) was mathematically modeled and evaluated. No significant differences were identified for model parameter distributions reflecting process dynamics. Therefore, the microtiter plate can be applied as scale-down tool for the lab-scale bioreactor. In case study II, a fed-batch process in a 24-Deep-Well-Plate (2 ml working volume) and shake flask (40 ml working volume) with two feed media was investigated. Model parameter distributions showed significant differences. Thus, process strategies were mathematically transferred, and model predictions were simulated for a new shake flask culture setup and confirmed in validation experiments. Overall, the workflow enables a knowledge-driven evaluation of scale-up for a more efficient bioprocess design and optimization.     

Process parameter shifting: Part II. Biphasic cultivation-A tool for enhancing the volumetric productivity of batch processes using Epo-Fc expressing CHO cells

Regulation of cell growth and protein expression potentially results in a sustainable enhancement of the volumetric productivity in a fermentation process. Following a biphasic cultivation strategy the process initially passes through a cell proliferation phase to generate a sufficiently high viable cell mass. In the subsequent production phase cells are maintained viable and productive without significant cell proliferation leading to increased viable cell days and product yields. In a previous work we have shown that the well directed alteration of the process environment based on process parameter shifting is a promising tool to regulate cell growth and protein expression. In continuation of this work we investigated process parameters which have been identified to affect cell proliferation in favor of an increased specific productivity and total product yield in a series of biphasic batch cultivation experiments. In most of these processes the integral of viable cells and the specific productivity were increased leading to a significant improvement of both final product concentration and volumetric productivity. In addition, combined parameter shifts (pH 6.90/30 degrees C and pH 6.90/33 degrees C) exerted a synergistic effect on product quality. The loss of product sialylation which occurred at reduced temperatures was prevented by simultaneously reducing the external pH. In conclusion, biphasic cultivation based on combined shifting of process parameters is a suitable tool for controlling cell proliferation and protein expression of mammalian cells in a batch bioreactor leading to enhanced volumetric productivities and therefore offers an enormous potential for bioprocess optimization.