Computational fluid dynamics simulation improves the design and characterization of a plug-flow-type scale-down reactor for microbial cultivation processes

The scale-up of bioprocesses remains one of the major obstacles in the biotechnology industry. Scale-down bioreactors have been identified as valuable tools to investigate the heterogeneities observed in large-scale tanks at the laboratory scale. Additionally, computational fluid dynamics (CFD) simulations can be used to gain information about fluid flow in tanks used for production. Here, we present the rational design and comprehensive characterization of a scale-down setup, in which a flexible and modular plug-flow reactor was connected to a stirred-tank bioreactor. With the help of CFD using the realizable k-ε model, the mixing time difference between a 20 and 4000 L bioreactor was evaluated and used as scale-down criterion. CFD simulations using a shear stress transport (SST) k-ω turbulence model were used to characterize the plug-flow reactor in more detail, and the model was verified using experiments. Additionally, the model was used to simulate conditions where experiments technically could not be performed due to sensor limitations. Nevertheless, verification is difficult in this case as well. This was the first time a scale-down setup was tested on high-cell-density Escherichia coli cultivations to produce industrially relevant antigen-binding fragments (Fab). Biomass yield was reduced by 11% and specific product yield was reduced by 20% during the scale-down cultivations. Additionally, the intracellular Fab fraction was increased by using the setup. The flexibility of the introduced scale-down setup in combination with CFD simulations makes it a valuable tool for investigating scale effects at the laboratory scale. More information about the large scale is still necessary to further refine the setup and to speed up bioprocess scale-up in the future.     

Coupled metabolic-hydrodynamic modeling enabling rational scale-up of industrial bioprocesses

Metabolomics aims to address what and how regulatory mechanisms are coordinated to achieve flux optimality, different metabolic objectives as well as appropriate adaptations to dynamic nutrient availability. Recent decades have witnessed that the integration of metabolomics and fluxomics within the goal of synthetic biology has arrived at generating the desired bioproducts with improved bioconversion efficiency. Absolute metabolite quantification by isotope dilution mass spectrometry represents a functional readout of cellular biochemistry and contributes to the establishment of metabolic (structured) models required in systems metabolic engineering. In industrial practices, population heterogeneity arising from fluctuating nutrient availability frequently leads to performance losses, that is reduced commercial metrics (titer, rate, and yield). Hence, the development of more stable producers and more predictable bioprocesses can benefit from a quantitative understanding of spatial and temporal cell-to-cell heterogeneity within industrial bioprocesses. Quantitative metabolomics analysis and metabolic modeling applied in computational fluid dynamics (CFD)-assisted scale-down simulators that mimic industrial heterogeneity such as fluctuations in nutrients, dissolved gases, and other stresses can procure informative clues for coping with issues during bioprocessing scale-up. In previous studies, only limited insights into the hydrodynamic conditions inside the industrial-scale bioreactor have been obtained, which makes case-by-case scale-up far from straightforward. Tracking the flow paths of cells circulating in large-scale bioreactors is a highly valuable tool for evaluating cellular performance in production tanks. The “lifelines” or “trajectories” of cells in industrial-scale bioreactors can be captured using Euler-Lagrange CFD simulation. This novel methodology can be further coupled with metabolic (structured) models to provide not only a statistical analysis of cell lifelines triggered by the environmental fluctuations but also a global assessment of the metabolic response to heterogeneity inside an industrial bioreactor. For the future, the industrial design should be dependent on the computational framework, and this integration work will allow bioprocess scale-up to the industrial scale with an end in mind.     

Characterization and feasibility of a miniaturized stirred tank bioreactor to perform E. coli high cell density fed-batch fermentations

The use of small scale bioreactors that are mechanically and functionally similar to large scale reactors is highly desirable to accelerate bioprocess development because they enable well-defined scale translations. In this study, a 25-mL miniaturized stirred tank bioreactor (MSBR) has been characterized in terms of its power input, hydrodynamics, and volumetric oxygen transfer coefficient (k(L)a) to assess its potential to grow high cell density (HCD) cultures using adequate scale-down criteria. Engineering characterization results show scale down, based on matched specific power input (P(G)/V), is feasible from a 20-L pilot scale stirred tank bioreactor. Results from fed-batch fermentations performed using Fab' producing E. coli W3110 at matched (P(G)/V) in the MSBR and 20-L STR demonstrated that the MSBR can accurately scale down the 20-L fermentation performance in terms of growth and Fab' production. Successful implementation of a fed-batch strategy in the MSBR resulted in maximum optical density of ca. 114 and total Fab' concentration of 940 μg/mL compared with ca. 118 and 990 μg/mL in 20-L STR. Furthermore, the use of the MSBR in conjunction with primary recovery scale-down tools to assess the harvest material of both reactors showed comparable shear sensitivity and centrifugation performance. The conjoint use of the MSBR with ultra scale-down (USD) centrifugation mimics can provide a cost-efficient manner in which to design and develop bioprocesses that account for good upstream performance as well as their manufacturability downstream.     

Prediction of the pilot-scale recovery of a recombinant yeast enzyme using integrated models

This article describes the rapid prediction of recovery process performance for a new recombinant enzyme product on the basis of a broad portfolio of computer models and highly targeted experimentation. A process model for the recombinant system was generated by linking unit operation models in an integrated fashion, with required parameter estimation and physical property determination accomplished using data from scale-down studies. This enabled the generic modeling framework established for processing of a natural enzyme from bakers' yeast to be applied. An experimental study of the same operations at the pilot scale showed that the process model gave a conservative prediction of recombinant enzyme recovery. The model successfully captured interactions leading to a low overall product yield and indicated the need for further study of precipitate breakage in the feed zone of a disc stack centrifuge in order to improve performance. The utility of scale-down units as an aid to fast model generation and the advantage of integrating computer modeling and scale-down studies to accelerate bioprocess development are highlighted.     

Extracellular vesicles concentration is a promising and important parameter for industrial bioprocess monitoring

Extracellular vesicles (EVs) are membrane vesicles that are produced by cells to be released into their microenvironment. In this study, we present the EV concentration as a new factor for optimization of industrial bioprocess control. The release of EVs depends on many cell properties, including cell activation and stress status, and cell death. Therefore, the EV concentration might provide a readout for identification of the cell state and the conditions during a bioprocess. Our data show that the EV concentration increased during the bioprocess, which indicated deteriorating conditions in the bioreactor. This increase in EV concentration in the fermentation broth was the consequence of two different processes: cell activation, and cell death. However, the release of EVs from activated living cells had a much weaker impact on EV concentration in the bioreactor than those released during cell death. EVs and cells in the bioprocess environment were quantified by flow cytometry. The most accurate data were obtained directly from unprocessed samples, making the monitoring of the EV concentration a rapid, easy, and cheap method. These EV concentrations reflect the conditions in the bioreactor and provide new information regarding the state of the bioprocess. Therefore, we suggest EV concentration as a new and important parameter for the monitoring of industrial bioprocesses.     

A methodology for the design of scale-down bioreactors by the use of mixing and circulation stochastic models

Scale-up is traduced in practice by an increase of the dimensions of the bioreactors, leading to a modification of the time scale and thus of the process dynamics. In the present work, a methodology to study the effect of scale-up on bioreactors hydrodynamics and to put in place scale-down reactors representative of the flow properties encountered in real scales bioreactors is detailed.In order to simplify the analysis, we have proposed the use of a stochastic model which is directly affected by the time scale. Indeed, to run simulations with such models, we have to specify the time taken to achieve a transition Δt. Stochastic models are thus reliable to study scale-up effect on stirred reactors hydrodynamics. In addition, these models permit to have an insight on the internal dynamic of the process.In the case of the circulation process, qualitative aspects have to be taken into account and induce a modification of the flow regions arrangement of the model. The stochastic analysis of large-scale bioreactors permits to propose a translating methodology into a scale-down context. Optimised scale-down reactors can be used further to carry out fermentation tests with the hydrodynamic conditions of the industrial scale. In a general rule, the performances of stochastic model allow to facilitate greatly the analysis of the scale-up effect and the hydrodynamic characteristics of both large-scale and scale-down reactors.     

Scale down of recombinant protein production: a comparative study of scaling performance

A large bioreactor is heterogeneous with respect to concentration gradients of substrates fed to the reactor such as oxygen and growth limiting carbon source. Gradient formation will highly depend on the fluid dynamics and mass transfer capacity of the reactor, especially in the area in which the substrate is added. In this study, some production-scale (12 m³ bioreactor) conditions of a recombinant Escherichia coli process were imitated on a laboratory scale. From the large-scale cultivations, it was shown that locally high concentration of the limiting substrate fed to the process, in this case glucose, existed at the level of the feedpoint. The large-scale process was scaled down from: (i) mixing time experiments performed in the large-scale bioreactor in order to identify and describe the oscillating environment and (ii) identification of two distinct glucose concentration zones in the reactor. An important parameter obtained from mixing time experiments was the residence time in the feed zone of about 10 seconds. The size of the feed zone was estimated to 10%. Based on these observations the scale-down reactor with two compartments was designed. It was composed of one stirred tank reactor and an aerated plug flow reactor, in which the effect of oscillating glucose concentration on biomass yield and acetate formation was studied. Results from these experiments indicated that the lower biomass yield and higher acetate formation obtained on a large scale compared to homogeneous small-scale cultivations were not directly caused by the cell response to the glucose oscillation. This was concluded since no acetate was accumulated during scale-down experiments. An explanation for the differences in results between the two reactor scales may be a secondary effect of high glucose concentration resulting in an increased glucose metabolism causing an oxygen consumption rate locally exceeding the transfer rate. The results from pulse response experiments and glucose concentration measurements, at different locations in the reactor, showed a great consistency for the two feeding/pulse positions used in the large-scale bioreactor. Furthermore, measured periodicity from mixing data agrees well with expected circulation times for each impeller volume. Conclusions are drawn concerning the design of the scale-down reactor.     

A model-based framework for parallel scale-down fed-batch cultivations in mini-bioreactors for accelerated phenotyping

Concentration gradients that occur in large industrial-scale bioreactors due to mass transfer limitations have significant effects on process efficiency. Hence, it is desirable to investigate the response of strains to such heterogeneities to reduce the risk of failure during process scale-up. Although there are various scale-down techniques to study these effects, scale-down strategies are rarely applied in the early developmental phases of a bioprocess, as they have not yet been implemented on small-scale parallel cultivation devices. In this study, we combine mechanistic growth models with a parallel mini-bioreactor system to create a high-throughput platform for studying the response of Escherichia coli strains to concentration gradients. As a scaled-down approach, a model-based glucose pulse feeding scheme is applied and compared with a continuous feed profile to study the influence of glucose and dissolved oxygen gradients on both cell physiology and incorporation of noncanonical amino acids into recombinant proinsulin. The results show a significant increase in the incorporation of the noncanonical amino acid norvaline in the soluble intracellular extract and in the recombinant product in cultures with glucose/oxygen oscillations. Interestingly, the amount of norvaline depends on the pulse frequency and is negligible with continuous feeding, confirming observations from large-scale cultivations. Most importantly, the results also show that a larger number of the model parameters are significantly affected by the scale-down scheme, compared with the reference cultivations. In this example, it was possible to describe the effects of oscillations in a single parallel experiment. The platform offers the opportunity to combine strain screening with scale-down studies to select the most robust strains for bioprocess scale-up.     

A systematic approach for scale-down model development and characterization of commercial cell culture processes

The objective of process characterization is to demonstrate robustness of manufacturing processes by understanding the relationship between key operating parameters and final performance. Technical information from the characterization study is important for subsequent process validation, and this has become a regulatory expectation in recent years. Since performing the study at the manufacturing scale is not practically feasible, development of scale-down models that represent the performance of the commercial process is essential to achieve reliable process characterization. In this study, we describe a systematic approach to develop a bioreactor scale-down model and to characterize a cell culture process for recombinant protein production in CHO cells. First, a scale-down model using 2-L bioreactors was developed on the basis of the 2000-L commercial scale process. Profiles of cell growth, productivity, product quality, culture environments (pH, DO, pCO2), and level of metabolites (glucose, glutamine, lactate, ammonia) were compared between the two scales to qualify the scale-down model. The key operating parameters were then characterized in single-parameter ranging studies and an interaction study using this scale-down model. Appropriate operation ranges and acceptance criteria for certain key parameters were determined to ensure the success of process validation and the process performance consistency. The process worst-case condition was also identified through the interaction study.     

A two-compartment bioreactor system made of commercial parts for bioprocess scale-down studies: impact of oscillations on Bacillus subtilis fed-batch cultivations

This study describes an advanced version of a two-compartment scale-down bioreactor that simulates inhomogeneities present in large-scale industrial bioreactors on the laboratory scale. The system is made of commercially available parts and is suitable for sterilization with steam. The scale-down bioreactor consists of a usual stirred tank bioreactor (STR) and a plug flow reactor (PFR) equipped with static mixer modules. The PFR module with a working volume of 1.2 L is equipped with five sample ports, and pH and dissolved oxygen (DO) sensors. The concept was applied using the non-sporulating Bacillus subtilis mutant strain AS3, characterized by a SpoIIGA gene knockout. In a fed-batch process with a constant feed rate, it is found that oscillating substrate and DO concentration led to diminished glucose uptake, ethanol formation and an altered amino acid synthesis. Sampling at the PFR module allowed the detection of dynamics at different concentrations of intermediates, such as pyruvic acid, lactic acid and amino acids. Results indicate that the carbon flux at excess glucose and low DO concentrations is shifted towards ethanol formation. As a result, the reduced carbon flux entering the tricarboxylic acid cycle is not sufficient to support amino acid synthesis following the oxaloacetic acid branch point.     

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.     

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.     

Influence of bioreactor hydraulic characteristics on a Saccharomyces cerevisiae fed-batch culture: hydrodynamic modelling and scale-down investigations

Yeast is a widely used microorganism at the industrial level because of its biomass and metabolite production capabilities. However, due to its sensitivity to the glucose effect, problems occur during scale-up to the industrial scale. Hydrodynamic conditions are not ideal in large-scale bioreactors, and glucose concentration gradients can arise when these bioreactors are operating in fed-batch mode. We have studied the effects of such gradients in a scale-down reactor, which consists of a mixed part linked to a non-mixed part by a recirculation pump, in order to mimic the hydrodynamic conditions encountered at the large scale. During the fermentation tests in the scale-down reactor, there was a drop in both biomass yield (ratio between the biomass produced and the glucose added) and trehalose production and an increase in both fermentation time (time between inoculation and beginning of stationary phase) and ethanol production. We have developed a stochastic model which explains these effects as the result of an induction process determined mainly by the hydrodynamic conditions. The concentration profiles experienced by the microorganisms during the scale-down tests were expressed and linked to the biomass yields of the scale-down tests.     

Shear stress analysis of mammalian cell suspensions for prediction of industrial centrifugation and its verification

This article describes the use of ultra scale-down studies requiring milliliter quantities of process material to study the clarification of mammalian cell culture broths using industrial-scale continuous centrifuges during the manufacture of a monoclonal antibody for therapeutic use. Samples were pretreated in a small high-speed rotating-disc device in order to mimic the effect on the cells of shear stresses in the feed zone of the industrial scale centrifuges. The use of this feed mimic was shown to predict a reduction of the clarification efficiency by significantly reducing the particle size distribution of the mammalian cells. The combined use of the rotating-disc device and a laboratory-scale test tube centrifuge successfully predicted the separation characteristics of industrial-scale, disc stack centrifuges operating with different feed zones. A 70% reduction in flow rate in the industrial-scale centrifuge was shown to arise from shear effects. A predicted 2.5-fold increase in throughput for the same clarification performance, achieved by the change to a centrifuge using a feed zone designed to give gentler acceleration of the bioprocess fluid, was also verified at large-scale.     

Scale-down model qualification of ambr® 250 high-throughput mini-bioreactor system for two commercial-scale mAb processes

Recent advances in high-throughput (HTP) automated mini-bioreactor systems have significantly improved development timelines for early-stage biologic programs. Automated platforms such as the ambr® 250 have demonstrated the ability, using appropriate scale-down approaches, to provide reliable estimates of process performance and product quality from bench to pilot scale, but data sets comparing to large-scale commercial processes (>10,000 L) are limited. As development moves toward late stages, specifically process characterization (PC), a qualified scale-down model (SDM) of the commercial process is a regulatory requirement as part of Biologics License Application (BLA)-enabling activities. This work demonstrates the qualification of the ambr® 250 as a representative SDM for two monoclonal antibody (mAb) commercial processes at scales >10,000 L. Representative process performance and product quality associated with each mAb were achieved using appropriate scale-down approaches, and special attention was paid to pCO₂ to ensure consistent performance and product quality. Principal component analysis (PCA) and univariate equivalence testing were utilized in the qualification of the SDM, along with a statistical evaluation of process performance and product-quality attributes for comparability. The ambr® 250 can predict these two commercial-scale processes (at center-point condition) for cell-culture performance and product quality. The time savings and resource advantages to performing PC studies in a small-scale HTP system improves the potential for the biopharmaceutical industry to get products to patients more quickly.     

Micro biochemical engineering to accelerate the design of industrial-scale downstream processes for biopharmaceutical proteins

The article examines how a small set of easily implemented micro biochemical engineering procedures combined with regime analysis and bioprocess models can be used to predict industrial scale performance of biopharmaceutical protein downstream processing. This approach has been worked on in many of our studies of individual operations over the last 10 years and allows preliminary evaluation to be conducted much earlier in the development pathway because of lower costs. It then permits the later large scale trials to be more highly focused. This means that the risk of delays during bioprocess development and of product launch are reduced. Here we draw the outcomes of this research together and illustrate its use in a set of typical operations; cell rupture, centrifugation, filtration, precipitation, expanded bed adsorption, chromatography and for common sources, E. coli, two yeasts and mammalian cells (GS-NSO). The general approach to establishing this method for other operations is summarized and new developments outlined. The technique is placed against the background of the scale-down methods that preceded it and complementary ones that are being examined in parallel. The article concludes with a discussion of the advantages and limitations of the micro biochemical engineering approach versus other methods.     

Realistic model of a solid substrate fermentation packed-bed pilot bioreactor

For any given large-scale solid substrate fermentation (SSF) bioreactor, to assess how well a control system will work in practice requires the most realistic model possible. This model needs to account fully for complicated dynamic reactor behaviour and, in addition, has to include a specific noise model that is capable of reproducing the disturbances observed in SSF bioreactor measurements. In this work, noisy data collected historically from SSF pilot scale fermentations was used to develop such a model. Applying standard signal processing techniques, each measured variable was separated into deterministic and noise signals. Deterministic signals were used to calibrate a previously developed phenomenological model of the bioreactor. Noise signals were used to construct a realistic noise model for each measured variable in turn. Finally, the two models were combined to attain simulations that compared well with real measurements. This integrated model will provide realistic simulations that will prove useful in the design of effective control systems for intermittently mixed SSF bioreactors.     

Toward a stochastic formulation of microbial growth in relation to bioreactor performances: case study of an E. coli fed-batch process

A stochastic microbial growth model has been elaborated in the case of the culture of E. coli in fed-batch and scale-down reactors. This model is based on the stochastic determination of the generation time of the microbial cells. The determination of generation time is determined by choosing the appropriate value on a log-normal distribution. The appropriateness of such distribution is discussed and growth curves are obtained that show good agreement compared with the experimental results. The mean and the standard deviation of the log-normal distribution can be considered to be constant during the batch phase of the culture, but they vary when the fed-batch mode is started. It has been shown that the parameters related to the log-normal distribution are submitted to an exponential evolution. The aim of this study is to explore the bioreactor hydrodynamic effect on microbial growth. Thus, in a second time, the stochastic growth model has been reinforced by data coming from a previous stochastic bioreactor mixing model (1). The connection of these hydrodynamic data with the actual stochastic growth model has allowed us to explain the scale-down effect associated with the glucose concentration fluctuations. It is important to point out that the scale-down effect is induced differently according to the feeding strategy involved in the fed-batch experiments.     

A methodical approach to ultra-scale-down of process sequences: application to casein removal from the milk of transgenic animals

Scale-down models of individual operations are widely used in biopharmaceutical process development to obtain information about the performance of production-scale equipment on the basis of inexpensive and efficient laboratory-scale tests, for the purposes of validation or optimization or characterization studies. We have investigated the ability of scale-down models of whole process sequences to provide reliable information for process scale-up from laboratory- to pilot-scales of operation. Using the example of the recovery of a protein from transgenic milk, we have conducted an a priori scale-down analysis of a projected pilot-scale process sequence. A systematic approach was developed to ensure that all critical aspects of process behavior were included in the scale-down model, resulting in the creation of an accurate and reliable scale-down representation of the pilot-scale process. The data from scale-down process trials conducted at 70 and 200 mL scales of operation served to highlight crucial factors determining process performance, and proved reliable in predicting the performance of the pilot-scale process over a scaling factor of 1000.