High‐throughput miniaturized bioreactors for cell culture process development: Reproducibility,scalability, and control

Decreasing the timeframe for cell culture process development has been a key goal toward accelerating biopharmaceutical development. Advanced Microscale Bioreactors (ambr?) is an automated micro‐bioreactor system with miniature single‐use bioreactors with a 10–15 mL working volume controlled by an automated workstation. This system was compared to conventional bioreactor systems in terms of its performance for the production of a monoclonal antibody in a recombinant Chinese Hamster Ovary cell line. The miniaturized bioreactor system was found to produce cell culture profiles that matched across scales to 3 L, 15 L, and 200 L stirred tank bioreactors. The processes used in this article involve complex feed formulations, perturbations, and strict process control within the design space, which are in‐line with processes used for commercial scale manufacturing of biopharmaceuticals. Changes to important process parameters in ambr? resulted in predictable cell growth, viability and titer changes, which were in good agreement to data from the conventional larger scale bioreactors. ambr? was found to successfully reproduce variations in temperature, dissolved oxygen (DO), and pH conditions similar to the larger bioreactor systems. Additionally, the miniature bioreactors were found to react well to perturbations in pH and DO through adjustments to the Proportional and Integral control loop. The data presented here demonstrates the utility of the ambr? system as a high throughput system for cell culture process development. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:718–727, 2014     

Inducible product gene expression technology tailored to bioprocess engineering

Bioprocess engineering has developed as a discipline to design optimal culture conditions and bioreactor operation protocols for production cell lines engineered for constitutive expression of desired protein pharmaceuticals. With the advent of heterologous gene regulation systems it has become possible to fine-tune expression of difficult-to-produce protein pharmaceuticals to optimal levels and to conditionally engineer cell metabolism for the best production performance. However, most of the small-molecules used to trigger expression of product or metabolic engineering product genes are incompatible with downstream processing regulations or process economics. Recent progress in product gene control design has resulted in the development of bioprocess-compatible regulation systems, which are responsive to physical parameters such as temperature or physiologic trigger molecules that are either an inherent part of host cell metabolism or intrinsic components of licensed protein-free cell culture media, such as redox status, vitamin H and gaseous acetaldehyde. While all of these systems have been shown to fine-tune product gene expression independent of the host cell metabolism some of them can be plugged into metabolic networks to capture critical physiologic parameters and convert them into an optimal production response. Assembly of individual product gene control modalities into synthetic networks has recently enabled construction of autonomously regulated time-delay or cell density-sensitive gene circuits, which trigger population-wide induction of product gene expression at a predefined time or culture density. We provide a comprehensive overview on the latest developments in the design of bioprocess-compatible product gene control systems.     

Statistical modeling of single target cell encapsulation

High throughput drop-on-demand systems for separation and encapsulation of individual target cells from heterogeneous mixtures of multiple cell types is an emerging method in biotechnology that has broad applications in tissue engineering and regenerative medicine, genomics, and cryobiology. However, cell encapsulation in droplets is a random process that is hard to control. Statistical models can provide an understanding of the underlying processes and estimation of the relevant parameters, and enable reliable and repeatable control over the encapsulation of cells in droplets during the isolation process with high confidence level. We have modeled and experimentally verified a microdroplet-based cell encapsulation process for various combinations of cell loading and target cell concentrations. Here, we explain theoretically and validate experimentally a model to isolate and pattern single target cells from heterogeneous mixtures without using complex peripheral systems.     

Generic model control of the specific growth rate in recombinant Escherichia coli cultivations

Generic model control is shown to be a powerful tool for keeping a microbial cultivation process close to its predetermined (optimized) control profile. This is demonstrated at the example of the green fluorescent protein expressed in genetically modified Escherichia coli host cells. It is shown that the process can be run very closely to a predefined complex profile of the specific cell growth rate mu(t). Controlling the experiments at many different growth conditions is a straightforward way of effectively collecting the data necessary for optimization of recombinant protein production systems. Although the process dynamics is rather complex, the model for the controller can be kept quite simple. The control technique, used here for specific growth rate control, is quite universal and can be applied for different biotechnological processes as well.     

A distributed knowledge-based approach to flexible automation: The contract net framework

This article applied distributed artificial intelligence to the real-time planning and control of flexible manufacturing systems (FMS) consisting of asynchronous manufacturing cells. A knowledge-based approach is used to determine the course of action, resource sharing, and processor assignments. Within each cell there is an embedded automatic planning system that executes dynamic scheduling and supervises manufacturing operations. Because of the decentralized control, real-time task assignments are carried out by a negotiation process among cell hosts. The negotiation process is modeled by augmented Petri nets —the combination of production rules and Petri nets—and is excuted by a distributed, rule-based algorithm.     

Automated flow cytometry for monitoring CHO cell cultures

Flow cytometry has been used to accurately monitor cell events that indicate the spatio-temporal state of a bioreactor culture. The introduction of process analytical technology (PAT) has led to process improvements using real-time or semi real-time monitoring systems. Integration of flow cytometry into an automated scheme for improved process monitoring can benefit PAT in bioreactor-based biopharmaceutical productions by establishing optimum process conditions and better quality protocols. Herein, we provide detailed protocols for establishing an automated flow cytometry system that can be used to investigate and monitor cell growth, viability, cell size, and cell cycle data. A method is described for the use of such a system primarily focused on CHO cell culture, although it is foreseen the information gathered from automated flow cytometry can be applied to a variety of cell lines to address both PAT requirements and gain further understanding of complex biological systems.     

Heterologous recombinant expression of non-originator NISTmAb

The successful development and regulatory approval of originator and biosimilar therapeutic proteins requires a systems approach to upstream and downstream processing as well as product characterization and quality control. Innovation in process design and control, product characterization strategies, and data integration represent an ecosystem whose concerted advancement may reduce time-to-market and further improve comparability and biosimilarity programs. The biopharmaceutical community has made great strides to this end, yet there currently exists no pre-competitive monoclonal antibody (mAb) expression platform for open innovation. Here, we describe the development and initial expression of an intended copy of the NISTmAb using three non-originator murine cell lines. It was found that, without optimization and in culture flasks, all three cell lines produce approximately 100 mg mAb per liter of culture. Sodium dodecyl sulfate polyacrylamide gel electrophoresis, size-exclusion chromatography, nuclear magnetic resonance spectroscopy, intact mass spectrometry, and surface plasmon resonance were used to demonstrate that the products of all three cell lines embody quality attributes with a sufficient degree of sameness to the NISTmAb Reference Material 8671 to warrant further bioreactor studies, process improvements and optimization. The implications of the work with regard to pre-competitive innovation to support process design and feedback control, comparability and biosimilarity assessments, and process analytical technologies are discussed.     

Evaluation of criteria for bioreactor comparison and operation standardization for mammalian cell culture

Development of bioprocesses with mammalian cell culture deals with different bioreactor types and scales. The bioreactors might be intended for generation of cell inoculum and production, research, process development, validation, or transfer purposes. During these activities, not only the difficulty of up and downscaling might lead to failure of consistency in cell growth, but also the use of different bioreactor geometries and operation conditions. In such cases, criteria for bioreactor design and process transfer should be carefully evaluated in order to select appropriate cultivation parameters. In this work, power input, mixing time, impeller tip speed, and Reynolds number have been compared systematically for the cultivation of the human cell line AGE1.HN within three partner laboratories using five different bioreactor systems. Proper operation ranges for the bioreactors were identified using the maximal cell‐specific growth rate (μ_max) as indicator. Common optimum values for process transfer criteria were found in these geometrically different bioreactors, in which deviations of μ_max between cultivation systems can be importantly reduced. The data obtained in this work are used for process standardization and comparability of results obtained in different bioreactor systems, i.e. to guarantee lab‐to‐lab consistency for systems biology approaches using mammalian cells.     

Real‐time monitoring and control of soluble signaling factors enables enhanced progenitor cell outputs from human cord blood stem cell cultures

Monitoring and control of primary cell cultures is challenging as they are heterogenous and dynamically complex systems. Feedback signaling proteins produced from off‐target cell populations can accumulate, inhibiting the production of the desired cell populations. Although culture strategies have been developed to reduce feedback inhibition, they are typically optimized for a narrow range of process parameters and do not allow for a dynamically regulated response. Here we describe the development of a microbead‐based process control system for the monitoring and control of endogenously produced signaling factors. This system uses quantum dot barcoded microbeads to assay endogenously produced signaling proteins in the culture media, allowing for the dynamic manipulation of protein concentrations. This monitoring system was incorporated into a fed‐batch bioreactor to regulate the accumulation of TGF‐β1 in an umbilical cord blood cell expansion system. By maintaining the concentration of TGF‐β1 below an upper threshold throughout the culture, we demonstrate enhanced ex vivo expansion of hematopoietic progenitor cells at higher input cell densities and over longer culture periods. This study demonstrates the potential of a fully automated and integrated real‐time control strategy in stem cell culture systems, and provides a powerful strategy to achieve highly regulated and intensified in vitro cell manufacturing systems. Biotechnol. Bioeng. 2014;111: 1258–1264. © 2013 The Authors Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.     

Online- and offline- monitoring of stem cell expansion on microcarrier

In the biopharmaceutical industry, adherent growing stem cell cultures gain worldwide importance as cell products. The cultivation process of these cells, such as in stirred tank reactors or in fixed bed reactors, is highly sophisticated. Cultivations need to be monitored and controlled to guarantee product quality and to satisfy GMP requirements. With the process analytical technology (PAT) initiative, requirements regarding process monitoring and control have changed and real-time on-line monitoring tools are recommended. A tool meeting the new requirements may be the dielectric spectroscopy for online viable cell mass determination by measurement of the permittivity. To establish these tools, proper offline methods for data correlation are required. The cell number determination of adherent cells on microcarrier is difficult, as it requires cell detachment from the carrier, which highly increases the statistical error. As an offline method, a fluorescence assay based on SYBR^®GreenI was developed allowing fast and easy total cell concentration determination without the need to detach the cells from the carrier. The assay is suitable for glass carriers used in stirred tank reactor systems or in fixed bed systems, may be suitable for different cell lines and can be applied to high sample numbers easily. The linear dependency of permittivity to cell concentration of suspended stem cells with the dielectric spectroscopy is shown for even very small cell concentrations. With this offline-method, a correlation of the cell concentration grown on carrier to the permittivity data measured by the dielectric spectroscopy was done successfully.     

Development and strategies of cell-culture technology for influenza vaccine

Influenza is a pandemic contagious disease and causes human deaths and huge economic destruction of poultry in the world. In order to control and prevent influenza, mainly type A, influenza vaccine for human and poultry were available since the 1940s and 1920s, respectively. In the development of vaccine production, influenza viruses were cultured originally from chicken embryos to anchorage-dependent cell lines, such as MDCK and Vero. The anchorage-independent lines have also been used to produce influenza virus, such as PER.C6 and engineering modified MDCK and Vero. During the process of influenza vaccine production, the common problem faced by all producers is how to improve the titer of influenza virus. This paper focuses on the developments of cell culture for influenza virus vaccine production, limitations of cell culture, and relative strategies for improvement virus yields in cell-culture systems.     

Strategies for selecting Recombinant CHO cell lines for cGMP manufacturing: Realizing the potential in bioreactors

Manufacture of recombinant proteins from mammalian cell lines requires the use of bioreactor systems at scales of up to 20,000 L. The cost and complexity of such systems can prohibit their extensive use during the process to construct and select the manufacturing cell line. It is therefore common practice to develop a model of the production process in a small scale vessel, such as a shake‐flask, where lower costs, ease of handling, and higher throughput are possible. This model can then be used to select a small number of cell lines for further evaluation in bioreactor culture. Here, we extend our previous work investigating cell line construction strategies to assess how well the behavior of cell lines in such a shake‐flask assessment predicts behavior in the associated bioreactor production process. A panel of 29 GS‐CHO cell lines, all producing the same antibody, were selected to include a mixture of high and low producers from a pool of 175 transfectants. Assessment of this panel in 10 L bioreactor culture revealed wide variation in parameters including growth, productivity, and metabolite utilization. In general, those cell lines which were high producing in the bioreactor cultures had also been higher producing in an earlier shake‐flask assessment. However, some changes in rank position of the evaluated cell lines were seen between the two systems. A potential explanation of these observations is discussed and approaches to improve the predictability of assessments used for cell line selection are considered. © 2010 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

Process control in cell culture technology using dielectric spectroscopy

In the biopharmaceutical industry, mammalian and insect cells as well as plant cell cultures are gaining worldwide importance to produce biopharmaceuticals and as products themselves, for example in stem cell therapy. These highly sophisticated cell-based production processes need to be monitored and controlled to guarantee product quality and to satisfy GMP requirements. With the process analytical technology (PAT) initiative, requirements regarding process monitoring and control have changed and real-time in-line monitoring tools are now recommended. Dielectric spectroscopy (DS) can serve as a tool to satisfy some PAT requirements. DS has been used in the medical field for quite some time and it may allow real-time process monitoring of biological cell culture parameters. DS has the potential to enable process optimization, automation, cost reduction, and a more consistent product quality. Dielectric spectroscopy is reviewed here as a tool to monitor biochemical processes. Commercially available dielectric sensing systems are discussed. The potential of this technology is demonstrated through examples of current and potential future applications in research and industry for mammalian and insect cell culture.     

The effect of the oligomerization of pBR322 on the level of transformation in Escherichia coli

The ability of the known Escherichia coli strain JC3881 recB recC recF sbc15 to produce oligomeric and multimeric forms of pBR322 underlies the study presented. The individual oligomeric forms of pBR322 were isolated from the agarose gel. The plasmid forms were used for electron microscopic control and also introduced into the system of E. coli competent cells. The E. coli transformation level of different forms of plasmid DNA rose from monomers to pentamers. CCC forms of the plasmid possessed high efficiency of the E. coli cell transformation. The systems of the host recombination are to be significant in the process of plasmid oligomerization.     

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.     

Determination of cell membrane permeability in concentrated cell ensembles

The method of volume averaging is used to analyze the process of diffusion in concentrated cell ensembles in which significant resistance to mass transfer is caused by the cellular membrane. A general closure scheme is given that allows for direct theoretical prediction of effective diffusivities for any cellular geometry. Numerical results are presented for the classical parallelepiped arrangement used to model cellular systems, and these results are used in conjunction with experimental studies of concentrated cell ensembles to determine membrane permeabilities for solute diffusion in several cellular systems. Membrane permeabilities are compared with predictions from other models of diffusion in cellular systems.     

Visualizing medium and biodistribution in complex cell culture bioreactors using in vivo imaging

There is a dearth of technology and methods to aid process characterization, control and scale‐up of complex culture platforms that provide niche micro‐environments for some stem cell‐based products. We have demonstrated a novel use of 3d in vivo imaging systems to visualize medium flow and cell distribution within a complex culture platform (hollow fiber bioreactor) to aid characterization of potential spatial heterogeneity and identify potential routes of bioreactor failure or sources of variability. This can then aid process characterization and control of such systems with a view to scale‐up. Two potential sources of variation were observed with multiple bioreactors repeatedly imaged using two different imaging systems: shortcutting of medium between adjacent inlet and outlet ports with the potential to create medium gradients within the bioreactor, and localization of bioluminescent murine 4T1‐luc2 cells upon inoculation with the potential to create variable seeding densities at different points within the cell growth chamber. The ability of the imaging technique to identify these key operational bioreactor characteristics demonstrates an emerging technique in troubleshooting and engineering optimization of bioreactor performance. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 30:256–260, 2014     

Sustainable ecosystem management using optimal control theory: part 2 (stochastic systems)

Sustainable development of ecosystems through external ecosystem management is assuming importance for the environmentalists. To that effect, previous work by the authors looked at the option of manipulating population dynamics of the species in an ecosystem to achieve sustainability. Fisher information is used as the quantifying measure of sustainability and optimal control theory is used to derive the control profiles. However, that work considered only deterministic systems. Uncertainty being prevalent in all systems, particularly in natural systems, this paper extends that work to analyse uncertain systems. Predator-prey models are used to model the species populations and different control philosophies are compared. Ito mean reverting process is used to model the stochastic process, and stochastic maximum principle is used to derive the control profiles. The results for the objective of FI variance minimization qualitatively agree with those for the deterministic system, while the results for the FI maximization objective differ. It is observed that the instability associated with the FI maximization objective for deterministic systems is absorbed by the noise introduced by the uncertainty. Quantitatively, it is observed that the degree of uncertainty, along with its presence, is also important to identify the most appropriate management strategy.     

Modeling the control of a flexible manufacturing cell for automatic verification and control program generation

Shortened product life-cycles decrease the output rate of manufacturing systems. Offline verification of the control systems promises to increase the output. However, to make offline verification possible some major improvements of the current development process of manufacturing systems are needed. Information handling and development of control programs based on information reuse are two of the most important improvement areas. This paper presents the results of the modeling of a real manufacturing cell according to a previously presented method for offline verification and program generation based on information reuse.     

Monitoring and control of the physiological state of cell cultures

Advances in bioprocess engineering depends ultimately on the level of understanding and control of the physiological state of the cell population. Process efficiency is strongly influenced by changes in the cellular state which should be monitored, interpreted, and, if possible, properly manipulated. In most control systems this function is not explicitly considered, which hampers process development and optimization. Conventional control logic is based on direct mapping of the growth environment into process efficiency, thereby bypassing the cell state as an intermediate control objective. Today, this limitation is well realized, and explicit monitoring and control of cellular physiology are considered to be among the most challenging tasks of modern bioprocess engineering. We present here a generic methodology for the design of systems capable of performing these advanced monitoring and control functions.The term "physiological state" is quantified by a vector composed of several process variables that convey significant information about cellular state. These variables can be selected among different classes, including specific metabolic rates, metabolic rate ratios, degees of limitation, and others. The real-time monitoring of many of these is possible using commercial sensors. The definition and calculation of representative sets of physiological state variables is demonstrated with examples from several fermentor cultures: recombinant Escherichia coli for phenylalanine production, bioluminescent E. coli (harboring lux genes driven by a heat shock protein promoter) for detection of environmental pollutants, plant cell culture of Perilla frutescensfor anthocyanin production, and perfusion cultures of recombinant mammalian cells (NS0 and CHO) for therapeutic protein production.If the physiological state vector is on-line calculated, the fermentation process can be described by its trajectory in a space defined by the vector components. Then, the goal of the control system is to maintain the physiological state of the cell as close as possible to the trajectory, providing maximum efficiency. A control structure meant to perform this function is proposed, along with the mechanism for its design. In contrast to conventional systems which work in a closed loop in respect to the cell environment, this scheme operates in a closed loop in respect to the cell state. The discussed control concept has been successfully applied to the recombinant phenylalanine production, resulting in physiologically consistent operation, total computer control, and high process efficiency. Initial results from the application of the method to perfusion mammalian cell cultures are also presented. (c) 1996 John Wiley & Sons, Inc.