Approach to designing rotating drum bioreactors for solid-state fermentation on the basis of dimensionless design factors

The development of large-scale solid-state fermentation (SSF) processes is hampered by the lack of simple tools for the design of SSF bioreactors. The use of semifundamental mathematical models to design and operate SSF bioreactors can be complex. In this work, dimensionless design factors are used to predict the effects of scale and of operational variables on the performance of rotating drum bioreactors. The dimensionless design factor (DDF) is a ratio of the rate of heat generation to the rate of heat removal at the time of peak heat production. It can be used to predict maximum temperatures reached within the substrate bed for given operational variables. Alternatively, given the maximum temperature that can be tolerated during the fermentation, it can be used to explore the combinations of operating variables that prevent that temperature from being exceeded. Comparison of the predictions of the DDF approach with literature data for operation of rotating drums suggests that the DDF is a useful tool. The DDF approach was used to explore the consequences of three scale-up strategies on the required air flow rates and maximum temperatures achieved in the substrate bed as the bioreactor size was increased on the basis of geometric similarity. The first of these strategies was to maintain the superficial flow rate of the process air through the drum constant. The second was to maintain the ratio of volumes of air per volume of bioreactor constant. The third strategy was to adjust the air flow rate with increase in scale in such a manner as to maintain constant the maximum temperature attained in the substrate bed during the fermentation.     

A survey of computational and physical methods applied to solid-state fermentation

During the last decade, significant effort has been made to apply computational and physical methods to solid-state fermentation (SSF). This had positive impact both on our understanding of the basic principles underlying this old technology, and on the latest progress made in industrial bioengineering. Guidelines on bioreactor design and operation including scale-up, new methods for biomonitoring and advanced control strategies are among the most important outcomes of practical use. Nevertheless, there still is a lack of experimental data, which hampers parameter identification and thus broader use of mathematical modeling. More attention should therefore be paid to combining and concentrating modern physical techniques and computational approaches in order to allow better model validation and thus further progress in rational bioengineering of SSF.     

A review of recent developments in modeling of microbial growth kinetics and intraparticle phenomena in solid-state fermentation

Mathematical models are important tools for optimizing the design and operation of solid-state fermentation (SSF) bioreactors. Such models must describe the kinetics of microbial growth, how this is affected by the environmental conditions and how this growth affects the environmental conditions. This is done at two levels of sophistication. In many bioreactor models the kinetics are described by simple empirical equations. However, other models that address the interaction of growth with intraparticle diffusion of enzymes, hydrolysis products and O₂ with the use of mechanistic equations have also been proposed, and give insights into how these microscale processes can potentially limit the overall performance of a bioreactor. The current article reviews the advances that have been made in both the empirical- and mechanistic-type kinetic models and discusses the insights that have been achieved through the modeling work and the improvements to models that will be necessary in the future.     

Two-phase partitioning bioreactors in fermentation technology

The two-phase partitioning bioreactor concept appears to have a great potential in enhancing the productivity of many bioprocesses. The proper selection of an organic solvent is the key to successful application of this approach in industrial practice. The integration of fermentation and a primary product separation step has a positive impact on the productivity of many fermentation processes. The controlled substrate delivery from the organic to the aqueous phase opens a new area of application of this strategy to biodegradation of xenobiotics. In this review, the most recent advances in the application of two-liquid phase partitioning bioreactors for product or substrate partitioning are discussed. Modeling and performance optimization studies related to those bioreactor systems are also reviewed.     

Mathematical models of ABE fermentation: review and analysis

Among different liquid biofuels that have emerged in the recent past, biobutanol produced via fermentation processes is of special interest due to very similar properties to that of gasoline. For an effective design, scale-up, and optimization of the acetone–butanol–ethanol (ABE) fermentation process, it is necessary to have insight into the micro- and macro-mechanisms of the process. The mathematical models for ABE fermentation are efficient tools for this purpose, which have evolved from simple stoichiometric fermentation equations in the 1980s to the recent sophisticated and elaborate kinetic models based on metabolic pathways. In this article, we have reviewed the literature published in the area of mathematical modeling of the ABE fermentation. We have tried to present an analysis of these models in terms of their potency in describing the overall physiology of the process, design features, mode of operation along with comparison and validation with experimental results. In addition, we have also highlighted important facets of these models such as metabolic pathways, basic kinetics of different metabolites, biomass growth, inhibition modeling and other additional features such as cell retention and immobilized cultures. Our review also covers the mathematical modeling of the downstream processing of ABE fermentation, i.e. recovery and purification of solvents through flash distillation, liquid–liquid extraction, and pervaporation. We believe that this review will be a useful source of information and analysis on mathematical models for ABE fermentation for both the appropriate scientific and engineering communities.     

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.     

Quantification of power consumption and oxygen transfer characteristics of a stirred miniature bioreactor for predictive fermentation scale-up

Miniature parallel bioreactors are becoming increasingly important as tools to facilitate rapid bioprocess design. Once the most promising strain and culture conditions have been identified a suitable scale-up basis needs to be established in order that the cell growth rates and product yields achieved in small scale optimization studies are maintained at larger scales. Recently we have reported on the design of a miniature stirred bioreactor system capable of parallel operation [Gill et al. (2008); Biochem Eng J 39:164-176]. In order to enable the predictive scale-up of miniature bioreactor results the current study describes a more detailed investigation of the bioreactor mixing and oxygen mass transfer characteristics and the creation of predictive engineering correlations useful for scale-up studies. A Power number of 3.5 for the miniature turbine impeller was first established based on experimental ungassed power consumption measurements. The variation of the measured gassed to ungassed power ratio, P(g)/P(ug), was then shown to be adequately predicted by existing correlations proposed by Cui et al. [Cui et al. (1996); Chem Eng Sci 51:2631-2636] and Mockel et al. [Mockel et al. (1990); Acta Biotechnol 10:215-224]. A correlation relating the measured oxygen mass transfer coefficient, k(L)a, to the gassed power per unit volume and superficial gas velocity was also established for the miniature bioreactor. Based on these correlations a series of scale-up studies at matched k(L)a (0.06-0.11 s(-1)) and P(g)/V (657-2,960 W m(-3)) were performed for the batch growth of Escherichia coli TOP10 pQR239 using glycerol as a carbon source. Constant k(L)a was shown to be the most reliable basis for predictive scale-up of miniature bioreactor results to conventional laboratory scale. This gave good agreement in both cell growth and oxygen utilization kinetics over the range of k(L)a values investigated. The work described here thus gives further insight into the performance of the miniature bioreactor design and will aid its use as a tool for rapid fermentation process development.     

Fed-batch bioreactor process scale-up from 3-L to 2,500-L scale for monoclonal antibody production from cell culture

This case study focuses on the scale-up of a Sp2/0 mouse myeloma cell line based fed-batch bioreactor process, from the initial 3-L bench scale to the 2,500-L scale. A stepwise scale-up strategy that involved several intermediate steps in increasing the bioreactor volume was adopted to minimize the risks associated with scale-up processes. Careful selection of several available mixing models from literature, and appropriately applying the calculated results to our settings, resulted in successful scale-up of agitation speed for the large bioreactors. Consideration was also given to scale-up of the nutrient feeding, inoculation, and the set-points of operational parameters such as temperature, pH, dissolved oxygen, dissolved carbon dioxide, and aeration in an integrated manner. It has been demonstrated through the qualitative and the quantitative side-by-side comparison of bioreactor performance as well as through a panel of biochemical characterization tests that the comparability of the process and the product was well controlled and maintained during the process scale-up. The 2,500-L process is currently in use for the routine clinical production of Epratuzumab in support of two global Phase III clinical trials in patients with lupus. Today, the 2,500 L, fed-batch production process for Epratuzumab has met all scheduled batch releases, and the quality of the antibody is consistent and reproducible, meeting all specifications, thus confirming the robustness of the process.     

Modeling of heat and mass transfer for solid state fermentation process in tray bioreactor

A mathematical model is developed to simulate oxygen consumption, heat generation and cell growth in solid state fermentation (SSF). The fungal growth on the solid substrate particles results in the increase of the cell film thickness around the particles. The model incorporates this increase in the biofilm size which leads to decrease in the porosity of the substrate bed and diffusivity of oxygen in the bed. The model also takes into account the effect of steric hindrance limitations in SSF. The growth of cells around single particle and resulting expansion of biofilm around the particle is analyzed for simplified zero and first order oxygen consumption kinetics. Under conditions of zero order kinetics, the model predicts upper limit on cell density. The model simulations for packed bed of solid particles in tray bioreactor show distinct limitations on growth due to simultaneous heat and mass transport phenomena accompanying solid state fermentation process. The extent of limitation due to heat and/or mass transport phenomena is analyzed during different stages of fermentation. It is expected that the model will lead to better understanding of the transport processes in SSF, and therefore, will assist in optimal design of bioreactors for SSF.     

Microbial community analysis of a full-scale DEMON bioreactor

Full-scale applications of autotrophic nitrogen removal technologies for the treatment of digested sludge liquor have proliferated during the last decade. Among these technologies, the aerobic/anoxic deammonification process (DEMON) is one of the major applied processes. This technology achieves nitrogen removal from wastewater through anammox metabolism inside a single bioreactor due to alternating cycles of aeration. To date, microbial community composition of full-scale DEMON bioreactors have never been reported. In this study, bacterial community structure of a full-scale DEMON bioreactor located at the Apeldoorn wastewater treatment plant was analyzed using pyrosequencing. This technique provided a higher-resolution study of the bacterial assemblage of the system compared to other techniques used in lab-scale DEMON bioreactors. Results showed that the DEMON bioreactor was a complex ecosystem where ammonium oxidizing bacteria, anammox bacteria and many other bacterial phylotypes coexist. The potential ecological role of all phylotypes found was discussed. Thus, metagenomic analysis through pyrosequencing offered new perspectives over the functioning of the DEMON bioreactor by exhaustive identification of microorganisms, which play a key role in the performance of bioreactors. In this way, pyrosequencing has been proven as a helpful tool for the in-depth investigation of the functioning of bioreactors at microbiological scale.     

Semi-continuous scale-down models for clone and operating parameter screening in perfusion bioreactors

Perfusion cell culture, confined traditionally to the production of fragile molecules, is currently gaining broader attention in the biomanufacturing of therapeutic proteins. The development of these processes is made difficult by the limited availability of appropriate scale-down models. This is due to the continuous operation that requires complex control and cell retention capacity. For example, the determination of an optimal perfusion and bleed rate for continuous cell culture is often performed in scale-down bioreactors and requires a substantial amount of time and effort. To increase the experimental throughput and decrease the required workload, a semi-continuous procedure, referred to as the VCD_max (viable cell density) approach, has been developed on the basis of shake tubes (ST) and deepwell plates (96-DWP). Its effectiveness has been demonstrated for 12 different CHO-K1-SV cell lines expressing an IgG1. Further, its reliability has been investigated through proper comparisons with perfusion runs in lab-scale bioreactors. It was found that the volumetric productivity and the CSPR_min (cell specific perfusion rate) determined using the ST and 96-DWP models were successfully (mostly within the experimental error) confirmed in lab-scale bioreactors, which then covered a significant scale-up from the half milliliter to the liter scale. These scale-down models are very useful to design and scale-up optimal bioreactor operating conditions as well as screening for different media and cell lines.     

The influence of process parameters in production of lipopeptide iturin A using aerated packed bed bioreactors in solid-state fermentation

The strain Bacillus iso 1 co-produces the lipopeptide iturin A and biopolymer poly-γ-glutamic acid (γ-PGA) in solid-state fermentation of substrate consisting of soybean meal, wheat bran with rice husks as an inert support. The effects of pressure drop, oxygen consumption, medium permeability and temperature profile were studied in an aerated packed bed bioreactor to produce iturin A, diameter of which was 50 mm and bed height 300 mm. The highest concentrations of iturin A and γ-PGA were 5.58 and 3.58 g/kg-dry substrate, respectively, at 0.4 L/min after 96 h of fermentation. The low oxygen uptake rates, being 23.34 and 22.56 mg O₂/kg-dry solid substrate for each air flow rate tested generated 5.75 W/kg-dry substrate that increased the fermentation temperature at 3.7 °C. The highest pressure drop was 561 Pa/m at 0.8 L/min in 24 h. This is the highest concentration of iturin A produced to date in an aerated packed bed bioreactor in solid-state fermentation. The results can be useful to design strategies to scale-up process of iturin A in aerated packed bed bioreactors. Low concentration of γ-PGA affected seriously pressure drop, decreasing the viability of the process due to generation of huge pressure gradients with volumetric air flow rates. Also, the low oxygenation favored the iturin A production due to the reduction of free void by γ-PGA production, and finally, the low oxygen consumption generated low metabolic heat. The results show that it must control the pressure gradients to scale-up the process of iturin A production.     

Dynamic modeling and simulation of continuous airlift bioreactors

For dynamic behaviors of continuous airlift bioreactors, a mathematical model based on a tanks-in-series model with backflow has been developed. The equations describing the dynamics of airlift bioreactors are material balances for micro-organism, substrate, dissolved oxygen and oxygen in gas-phase and heat balances. Non-ideal mixing of liquid and gas phases is taken into account using a tanks-in-series model with backflow. The batch operation, startup operation and the consequence of plant failure were simulated and the effects of design and operating parameters for an airlift bioreactor on its dynamic behaviors were discussed. The concentration profiles of micro-organism, substrate, dissolved oxygen and oxygen in gas-phase and the temperature profile in an airlift bioreactors and their dynamics were obtained. The computational results indicate that the transients of a chemostat in the case of bubble column bioreactor are slower compared with those in the case of airlift bioreactor. The proposed simulator is more precise as compared with models published previously in the literature and therefore provides more reliable and rational examination of continuous airlift bioreactor performance.     

Recent advances in two-phase partitioning bioreactors for the treatment of volatile organic compounds

Biological processes are considered to be the most cost-effective technology for the off-gas treatment of volatile organic compounds (VOC) at low concentrations. Two-phase partitioning bioreactors (TPPBs) emerged in the early 1990s as innovative multiphase systems capable of overcoming some of the key limitations of traditional biological technologies such as the low mass transfer rates of hydrophobic VOCs and microbial inhibition at high VOC loading rates. Intensive research carried out in the last 5 years has helped to provide a better understanding of the mass transfer phenomena and VOC uptake mechanisms in TPPBs, which has significantly improved the VOC biodegradation processes utilizing this technology platform. This work presents an updated state-of-the-art review on the advances of TPPB technology for air pollution control. The most recent insights regarding non-aqueous phase (NAP) selection, microbiology, reactor design, mathematical modeling and case studies are critically reviewed and discussed. Finally, the key research issues required to move towards the development of efficient and stable full-scale VOC biodegradation processes in TPPBs are identified.     

Bioreactors for succinic acid production processes

Succinic acid (SA) has been recognized as one of the most important bio-based building block chemicals due to its numerous potential applications. Fermentation SA production from renewable carbohydrate feedstocks can have the economic and sustainability potential to replace petroleum-based production in the future, not only for existing markets, but also for new larger volume markets. Design and operation of bio-reactors play a key role. During the last 20 years, many different fermentation strategies for SA production have been described in literature, including utilization of immobilized biocatalysts, integrated fermentation and separation systems and batch, fed-batch, and continuous operation modes. This review is an overview of different fermentation process design developed over the past decade and provides a perspective on remaining challenges for an economically feasible succinate production processes. The analysis stresses the idea of improving the efficiency of the fermentation stage by improving bioreactor design and by increasing bioreactor performance.     

A Multi-Paradigm Modeling Framework to Simulate Dynamic Reciprocity in a Bioreactor

Despite numerous technology advances, bioreactors are still mostly utilized as functional black-boxes where trial and error eventually leads to the desirable cellular outcome. Investigators have applied various computational approaches to understand the impact the internal dynamics of such devices has on overall cell growth, but such models cannot provide a comprehensive perspective regarding the system dynamics, due to limitations inherent to the underlying approaches. In this study, a novel multi-paradigm modeling platform capable of simulating the dynamic bidirectional relationship between cells and their microenvironment is presented. Designing the modeling platform entailed combining and coupling fully an agent-based modeling platform with a transport phenomena computational modeling framework. To demonstrate capability, the platform was used to study the impact of bioreactor parameters on the overall cell population behavior and vice versa. In order to achieve this, virtual bioreactors were constructed and seeded. The virtual cells, guided by a set of rules involving the simulated mass transport inside the bioreactor, as well as cell-related probabilistic parameters, were capable of displaying an array of behaviors such as proliferation, migration, chemotaxis and apoptosis. In this way the platform was shown to capture not only the impact of bioreactor transport processes on cellular behavior but also the influence that cellular activity wields on that very same local mass transport, thereby influencing overall cell growth. The platform was validated by simulating cellular chemotaxis in a virtual direct visualization chamber and comparing the simulation with its experimental analogue. The results presented in this paper are in agreement with published models of similar flavor. The modeling platform can be used as a concept selection tool to optimize bioreactor design specifications.     

Computational fluid dynamics modeling,a novel,and effective approach for developing scalable cell therapy manufacturing processes

Induced pluripotent stem cells (iPSCs) hold great potential to generate novel, curative cell therapy products. However, current methods to generate these novel therapies lack scalability, are labor-intensive, require a large footprint, and are not suited to meet clinical and commercial demands. Therefore, it is necessary to develop scalable manufacturing processes to accommodate the generation of high-quality iPSC derivatives under controlled conditions. The current scale-up methods used in cell therapy processes are based on empirical, geometry-dependent methods that do not accurately represent the hydrodynamics of 3D bioreactors. These methods require multiple iterations of scale-up studies, resulting in increased development cost and time. Here we show a novel approach using computational fluid dynamics modeling to effectively scale-up cell therapy manufacturing processes in 3D bioreactors. Using a GMP-compatible iPSC line, we translated and scaled-up a small-scale cardiomyocyte differentiation process to a 3-L computer-controlled bioreactor in an efficient manner, showing comparability in both systems.     

Mathematical Modeling in Wound Healing,Bone Regeneration and Tissue Engineering

The processes of wound healing and bone regeneration and problems in tissue engineering have been an active area for mathematical modeling in the last decade. Here we review a selection of recent models which aim at deriving strategies for improved healing. In wound healing, the models have particularly focused on the inflammatory response in order to improve the healing of chronic wound. For bone regeneration, the mathematical models have been applied to design optimal and new treatment strategies for normal and specific cases of impaired fracture healing. For the field of tissue engineering, we focus on mathematical models that analyze the interplay between cells and their biochemical cues within the scaffold to ensure optimal nutrient transport and maximal tissue production. Finally, we briefly comment on numerical issues arising from simulations of these mathematical models.     

Scale-up and design of a pilot-plant photobioreactor for the continuous culture of Spirulina platensis

Scale-up of bioreactors has the intrinsic difficulty of establishing a reliable relationship among physical parameters involved in the design of the new bioreactor and the physiology of the cultured cells. This is more critical in those cases where a more complex operation of the bioreactor is needed, such as in photobioreactors. A key issue in the operation of photobioreactors is establishing a quantification for the interaction between external illumination, internal light distribution and cell growth. In this paper an approach to the scale-up of a photobioreactor for the culture of Spirulina platensis, based on a mathematical model describing this interaction, and the operation of a previous reactor 10 times smaller is presented. The paper describes the approach followed in the scale-up, the analysis of different design constraints, the physical realization of the new bioreactor design, innovative use of plastic material walls to improve reactor safety, and finally the corroboration of its satisfactory operation.     

Mathematical modeling and parameters estimation of anaerobic fermentation processes

In the paper some problems of the mathematical modeling of anaerobic (methane) fermentation of animal waste in stirred tank bioreactors are considered. Laboratory experiments are carried out with highly concentrated organic pollutants and transient step responses of the control output for continuous methane fermentation are obtained. The dynamic behavior of this process is described by sets of deterministic nonlinear differential equations from 2nd order with different structures. Static characteristics are obtained with these models analytically. Investigations by computer simulation of the methane fermentation are performed with the aim to chose appropriate models for automatic control system design of this process.