Bioprocess monitoring

Development and Application of an Automated Raman Sensor for Bioprocess Monitoring: From the Laboratory to an Algae Production Platform

Microalgae provide valuable bio-components with economic and environmental benefits. The monitoring of microalgal production is mostly performed using different sensors and analytical methods that, although very powerful, are limited to qualified users. This study proposes an automated Raman spectroscopy-based sensor for the online monitoring of microalgal production. For this purpose, an in situ system with a sampling station was made of a light-tight optical chamber connected to a Raman probe. Microalgal cultures were routed to this chamber by pipes connected to pumps and valves controlled and programmed by a computer. The developed approach was evaluated on Parachlorella kessleri under different culture conditions at a laboratory and an industrial algal platform. As a result, more than 4000 Raman spectra were generated and analysed by statistical methods. These spectra reflected the physiological state of the cells and demonstrate the ability of the developed sensor to monitor the physiology of microalgal cells and their intracellular molecules of interest in a complex production environment.

Current and future technologies for monitoring cultured meat: A review

The high population growth rate, massive animal food consumption, fast economic progress, and limited food resources could lead to a food crisis in the future. There is a huge requirement for dietary proteins including cultured meat is being progressed to fulfill the need for meat-derived proteins in the diet. However, production of cultured meat requires monitoring numerous bioprocess parameters. This review presents a comprehensive overview of various widely adopted techniques (optical, spectroscopic, electrochemical, capacitive, FETs, resistive, microscopy, and ultrasound) for monitoring physical, chemical, and biological parameters that can improve the bioprocess control in cultured meat. The methods, operating principle, merits/demerits, and the main open challenges are reviewed with the aim to support the readers in advancing knowledge on novel sensing systems for cultured meat applications.

Investigation and evaluation of a 3D-printed optical modified cultivation vessel for improved scattered light measurement of biotechnologically relevant organisms

In the field of bioprocess development miniaturization, parallelization and flexibility play a key role reducing costs and time. To precisely meet these requirements, additive manufacturing (3D-printing) is an ideal technology. 3D-printing enables rapid prototyping and cost-effective fabrication of individually designed devices with complex geometries on demand. For successful bioprocess development, monitoring of process-relevant parameters, such as pH, dissolved oxygen (DO), and biomass, is crucial. Online monitoring is preferred as offline sampling is time-consuming and leads to loss of information. In this study, 3D-printed cultivation vessels with optical prisms are evaluated for the use in upstream processes of different industrially relevant microorganisms and cell lines. It was shown, that the 3D-printed optically modified well (OMW) is of benefit for a wide range of biotechnologically relevant microorganisms and even for mammalian suspension cells. Evaluation tests with Escherichia coli, Bacillus subtilis, Saccharomyces cerevisiae, and Chinese hamster ovary (CHO) cells were performed, providing highly reproducible results. Growth behavior of OMW cultures was comparable to behavior of shake flask (SF) cultivations and the signal to noise ratio in online biomass measurement was shown to be reduced up to 95.8% by using the OMW. Especially the cultivation phases with low turbidity respective optical densities below 1.0 rel.AU could be monitored accurately for the first time. Furthermore, it was demonstrated that the 3D-printed optics are transferable to different well geometries and sizes, enabling efficient biomass monitoring for individual requirements with tailor-made 3D-printed cultivation vessels in small scale.

Advances in bioreactor control for production of biotherapeutic products

Advanced control strategies are well established in chemical, pharmaceutical, and food processing industries. Over the past decade, the application of these strategies is being explored for control of bioreactors for manufacturing of biotherapeutics. Most of the industrial bioreactor control strategies apply classical control techniques, with the control system designed for the facility at hand. However, with the recent progress in sensors, machinery, and industrial internet of things, and advancements in deeper understanding of the biological processes, coupled with the requirement of flexible production, the need to develop a robust and advanced process control system that can ease process intensification has emerged. This has further fuelled the development of advanced monitoring approaches, modeling techniques, process analytical technologies, and soft sensors. It is seen that proper application of these concepts can significantly improve bioreactor process performance, productivity, and reproducibility. This review is on the recent advancements in bioreactor control and its related aspects along with the associated challenges. This study also offers an insight into the future prospects for development of control strategies that can be designed for industrial-scale production of biotherapeutic products.

Modern Sensor Tools and Techniques for Monitoring, Controlling, and Improving Cell Culture Processes

The growing biopharmaceutical industry has reached a level of maturity that allows for the monitoring of numerous key variables for both process characterization and outcome predictions. Sensors were historically used in order to maintain an optimal environment within the reactor to optimize process performance. However, technological innovation has pushed towards on-line in situ continuous monitoring of quality attributes that could previously only be estimated off-line. These new sensing technologies when coupled with software models have shown promise for unique fingerprinting, smart process control, outcome improvement, and prediction. All this can be done without requiring invasive sampling or intervention on the system. In this paper, the state-of-the-art sensing technologies and their applications in the context of cell culture monitoring are reviewed with emphasis on the coming push towards industry 4.0 and smart manufacturing within the biopharmaceutical sector. Additionally, perspectives as to how this can be leveraged to improve both understanding and outcomes of cell culture processes are discussed.

Rapid and concise quantification of mycelial growth by microscopic image intensity model and application to mass cultivation of fungi

The microbial food fermentation industry requires real-time monitoring and accurate quantification of cells. However, filamentous fungi are difficult to quantify as they have complex cell types such as pellet, spores, and dispersed hyphae. In this study, numerous data of microscopic image intensity (MII) were used to develop a simple and accurate quantification method of Cordyceps mycelium. The dry cell weight (DCW) of the sample collected during the fermentation was measured. In addition, the intensity values were obtained through the ImageJ program after converting the microscopic images. The prediction model obtained by analyzing the correlation between MII and DCW was evaluated through a simple linear regression method and found to be statistically significant (R2 = 0.941, p < 0.001). In addition, validation with randomly selected samples showed significant accuracy, thus, this model is expected to be used as a valuable tool for predicting and quantifying fungal growth in various industries.

Characterization of cell cycle and apoptosis in Chinese hamster ovary cell culture using flow cytometry for bioprocess monitoring

Chinese hamster ovary (CHO) cells are by far the most important mammalian cell lines used for producing antibodies and other therapeutic proteins. It is critical to fully understand their physiological conditions during a bioprocess in order to achieve the highest productivity and the desired product quality. Flow cytometry technology possesses unique advantages for measuring multiple cellular attributes for a given cell and examining changes in cell culture heterogeneity over time that can be used as metrics for enhanced process understanding and control strategy. Flow cytometry-based assays were utilized to examine the progression of cell cycle and apoptosis in three case studies using different antibody-producing CHO cell lines in both fed-batch and perfusion bioprocesses. In our case studies, we found that G0/G1 phase distribution and early apoptosis accumulation responded to subtle changes in culture conditions, such as pH shifting or momentary glucose depletion. In a perfusion process, flow cytometry provided an insightful understanding of the cell physiological status under a hypothermic condition. More importantly, these changes in cell cycle and apoptosis were not detected by a routine trypan blue exclusion-based cell counting and viability measurement. In summary, integration of flow cytometry into bioprocesses as a process analytical technology tool can be beneficial for establishing optimum process conditions and process control.

History and Evolution of Modeling in Biotechnology: Modeling & Simulation, Application and Hardware Performance

Biological systems are typically composed of highly interconnected subunits and possess an inherent complexity that make monitoring, control and optimization of a bioprocess a challenging task. Today a toolset of modeling techniques can provide guidance in understanding complexity and in meeting those challenges. Over the last four decades, computational performance increased exponentially. This increase in hardware capacity allowed ever more detailed and computationally intensive models approaching a "one-to-one" representation of the biological reality. Fueled by governmental guidelines like the PAT initiative of the FDA, novel soft sensors and techniques were developed in the past to ensure product quality and provide data in real time. The estimation of current process state and prediction of future process course eventually enabled dynamic process control. In this review, past, present and envisioned future of models in biotechnology are compared and discussed with regard to application in process monitoring, control and optimization. In addition, hardware requirements and availability to fit the needs of increasingly more complex models are summarized. The major techniques and diverse approaches of modeling in industrial biotechnology are compared, and current as well as future trends and perspectives are outlined.

Sustainable Method Using Filtering Techniques for a Fermentation Process State Estimation

Winemaking is concerned about sustainable energy availability that implies new methods for process monitoring and control. The aim of this paper is to realize a comparative analysis of the possibilities offered using estimation techniques, balances, and filtering techniques such as the Kalman filter (KF) and the extended Kalman filter (EKF), to obtain indirect information about the alcoholic fermentation process during winemaking. Thus, an estimation solution of the process variables in the exponential growing phase is proposed, using an extended observer. In addition, two estimation solutions of this process with the EKF and an estimation of the decay phase of the fermentation process are presented. The difference between the two EKF variants consisted of taking into consideration the indicator of the integral of the error norm square for the second EKF, for which the performance criterion was the statistical average of this indicator. Results from the simulation of the estimation programs of the two EKF variants were more than satisfactory. This research provides a basis for using an EKF designed for advanced control of the alcoholic fermentation batch process as a knowledge-based system.

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

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

Biomass soft sensor for a Pichia pastoris fed-batch process based on phase detection and hybrid modeling

A common control strategy for the production of recombinant proteins in Pichia pastoris using the alcohol oxidase 1 (AOX1) promotor is to separate the bioprocess into two main phases: biomass generation on glycerol and protein production via methanol induction. This study reports the establishment of a soft sensor for the prediction of biomass concentration that adapts automatically to these distinct phases. A hybrid approach combining mechanistic (carbon balance) and data-driven modeling (multiple linear regression) is used for this purpose. The model parameters are dynamically adapted according to the current process phase using a multilevel phase detection algorithm. This algorithm is based on the online data of CO₂ in the off-gas (absolute value and first derivative) and cumulative base feed. The evaluation of the model resulted in a mean relative prediction error of 5.52% and R² of .96 for the entire process. The resulting model was implemented as a soft sensor for the online monitoring of the P. pastoris bioprocess. The soft sensor can be used for quality control and as input to process control systems, for example, for methanol control.

Effect of aeration and agitation on yeast inulinase production: a biocalorimetric investigation

Air flow rate and agitation speed for inulinase production by Kluyveromyces marxianus were optimized based on metabolic heat release profiles. Shear stress and oxygen transfer (k_La) values were compared to assess the effects of aeration and agitation. At agitation rates of ≤ 100 rpm, the oxygen mass transfer rates were small and eventually led to less inulinase production, but at agitation rates > 150 rpm, loss of biomass resulted in less inulinase activity. Bio-reaction calorimeter (BioRc1e) experiment with aeration rates ≤ 0.5 lpm showed low k_La while at 1.5 lpm frothing of reactor contents caused loss of biomass and inulinase activity. The optimum conditions for aeration and agitation rate for K. marxianus in BioRc1e were 1 lpm and 150 rpm. Heat yield values obtained for the substrate, product and biomass reinstated the ongoing metabolic process. The heat release pattern could be a promising tool for optimization of bioprocess and in situ monitoring, with a possibility of interventions during the biotransformation process. At optimized aeration and agitation conditions, a two-fold increase in inulinase activity could be noticed.

Bioreactor Operating Strategies for Improved Polyhydroxyalkanoate (PHA) Productivity

Microbial polyhydroxyalkanoates (PHAs) are promising biodegradable polymers that may alleviate some of the environmental burden of petroleum-derived polymers. The requirements for carbon substrates and energy for bioreactor operations are major factors contributing to the high production costs and environmental impact of PHAs. Improving the process productivity is an important aspect of cost reduction, which has been attempted using a variety of fed-batch, continuous, and semi-continuous bioreactor systems, with variable results. The purpose of this review is to summarize the bioreactor operations targeting high PHA productivity using pure cultures. The highest volumetric PHA productivity was reported more than 20 years ago for poly(3-hydroxybutryate) (PHB) production from sucrose (5.1 g L⁻¹ h⁻¹). In the time since, similar results have not been achieved on a scale of more than 100 L. More recently, a number fed-batch and semi-continuous (cyclic) bioreactor operation strategies have reported reasonably high productivities (1 g L⁻¹ h⁻¹ to 2 g L⁻¹ h⁻¹) under more realistic conditions for pilot or industrial-scale production, including the utilization of lower-cost waste carbon substrates and atmospheric air as the aeration medium, as well as cultivation under non-sterile conditions. Little development has occurred in the area of fully continuously fed bioreactor systems over the last eight years.

In-situ electrochemical analysis of microbial activity

Microbes have a wide range of metabolic capabilities available that makes them industrially useful organisms. Monitoring these metabolic processes is a crucial component in efficient industrial application. Unfortunately, monitoring these metabolic processes can often be invasive and time consuming and expensive, especially within an anaerobic environment. Electrochemical techniques, such as cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) offer a non-invasive approach to monitor microbial activity and growth. EIS and CV were used to monitor Clostridium phytofermentans, an anaerobic and endospore-forming bacterium. C. phytofermentans ferments a wide range of sugars into hydrogen, acetate, and ethanol as fermentation by-products. For this study, both traditional microbiological and electrochemical techniques were used to monitor the growth of C. phytofermentans and the formation of fermentation products. An irreversible reduction peak was observed using CV beginning at mid-logarithmic phase of growth. This peak was associated with C. phytofermentans and not the spent medium and was indicative of a decrease in carbon and energy sources to the cells. Additionally, EIS analysis during growth provided information related to increased charge transfer resistance of the culture also as a function of carbon and energy source depletion. Results demonstrate that CV and EIS are useful tools in the monitoring the physiological status of bioprocesses.

Sensors for disposable bioreactors

Modern bioprocess monitoring demands sensors that provide on-line information about the process state. In particular, sensors for monitoring bioprocesses carried out in single-use bioreactors are needed because disposable systems are becoming increasingly important for biotechnological applications. Requirements for the sensors used in these single-use bioreactors are different than those used in classical reusable bioreactors. For example, long lifetime or resistance to steam and cleaning procedures are less crucial factors, while a requirement of sensors for disposable bioreactors is a cost that is reasonable on a per-use basis. Here, we present an overview of current and emerging sensors for single-use bioreactors, organized by the type of interface of the sensor systems to the bioreactor. A major focus is on non-invasive, in-situ sensors that are based on electromagnetic, semiconducting, optical, or ultrasonic measurements. In addition, new technologies like radio-frequency identification sensors or free-floating sensor spheres are presented. Notably, at this time there is no standard interface between single-use bioreactors and the sensors discussed here. In the future, manufacturers should address this shortcoming to promote single-use bioprocess monitoring and control.

On-line identification of fermentation processes for ethanol production

A strategy for monitoring fermentation processes, specifically, simultaneous saccharification and fermentation (SSF) of corn mash, was developed. The strategy covered the development and use of first principles, semimechanistic and unstructured process model based on major kinetic phenomena, along with mass and energy balances. The model was then used as a reference model within an identification procedure capable of running on-line. The on-line identification procedure consists on updating the reference model through the estimation of corrective parameters for certain reaction rates using the most recent process measurements. The strategy makes use of standard laboratory measurements for sugars quantification and in situ temperature and liquid level data. The model, along with the on-line identification procedure, has been tested against real industrial data and have been able to accurately predict the main variables of operational interest, i.e., state variables and its dynamics, and key process indicators. The results demonstrate that the strategy is capable of monitoring, in real time, this complex industrial biomass fermentation. This new tool provides a great support for decision-making and opens a new range of opportunities for industrial optimization.

Microbioreactors for Bioprocess Development

As a step toward high-throughput bioprocess development, we present design, fabrication, and characterization of polymer based microbioreactors integrated with automated sensors and actuators. The devices are realized, in increasing levels of complexity, in poly(dimethylsiloxane) and poly(methyl methacrylate) by micromachining and multilayer thermal compression bonding procedures. Online optical measurements for optical density, pH, and dissolved oxygen are integrated. Active mixing is made possible by a miniature magnetic stir bar. Plug-in-and-flow microfluidic connectors and fabricated polymer micro-optical lenses/connectors are integrated in the microbioreactors for fast set up and easy operation. Application examples demonstrate the feasibility of culturing microbial cells, specifically Escherichia coli, in 150 μL-volume bioreactors in batch, continuous, and fed-batch operations. (JALA 2007;12:143–51)

Response of biodegradation characteristics of unacclimated activated sludge to moderate pressure in a batch reactor

This study was aimed to investigate the effect of moderate pressure on unacclimated activated sludge. Process of organic degradation, variation of carbon dioxide (CO2) concentration of off-gas and characteristics of extracellular polymeric substances (EPS) of activated sludge were analyzed using pressure-atmospheric comparative experiments in bench-scale batch reactors. It was found that moderate pressure increased the degradation rate more dramatically when the biological process ran under a higher organic load with much more oxygen demand, which illuminated that applications of the pressurized method to high concentration organic wastewaters would be more reasonable and practicable. High oxygen transfer impetus increased utilization of oxygen which not only promoted the biodegradation of organics in wastewater, but also led to more EPS consumption in activated sludge. CO2 concentration of off-gas was lower in the earlier stage due to CO2 being pressed into the liquid phase and converted into inorganic carbon (IC). More CO2 emission was observed during the pressurized aerobic process 160 min later. EPS in pressurized reactor was much lower, which may be an important way of sludge reduction by pressurized technology.

Versatile common instrumentation for optical detection of pH and dissolved oxygen

The recent trend toward use of disposable and miniature bioreactors requires the use of appropriate sensors. pH and dissolved oxygen (DO) are often measured using optical chemical sensors due to their small form factor and convenience in use. These sensors are often interrogated using a specialized opto-electronic transducer that is designed around the optical sensor. In this contribution, we are presenting a new class of opto-electronic transducers that are usable with several different chemical sensors without the need to switch the optics or hardware when changing the type of the chemical sensor. This allows flexibility closer to the lab-grade devices while the size is closer to a dedicated sensor. This versatile instrumentation is capable of seamlessly switching between the pH and DO measurement modes and is capable of auto recognition of the sensor type. The principle of ratiometric fluorescence is used for pH measurements, and that of fluorescence lifetime for DO measurements. An approach to obtain identical calibrations between several devices is also presented. The described hardware constitutes common instrumentation for measuring either pH or DO and has been tested in actual bioprocesses. It has been found adequate for continuous bioprocess monitoring.

Non-Invasive Optical Sensor Based Approaches for Monitoring Virus Culture to Minimize BSL3 Laboratory Entry

High titers of infectious viruses for vaccine and diagnostic reference panel development are made by infecting susceptible mammalian cells. Laboratory procedures are strictly performed in a Bio-Safety Level-3 (BSL3) laboratory and each entry and exit involves the use of  disposable Personnel Protective Equipment (PPE) to observe cell culture conditions. Routine PPE use involves significant recurring costs. Alternative non-invasive optical sensor based approaches to remotely monitor cell culture may provide a promising and cost effective approach to monitor infectious virus cultures resulting in lower disruption and costs. We report here the monitoring of high titer cultures of Human Immunodeficiency Virus-1 (HIV-1) and Herpes Simplex Virus-2 (HSV-2) remotely with the use of optical oxygen sensors aseptically placed inside the cell culture vessel. The replacement of culture media for cell and virus propagation and virus load monitoring was effectively performed using this fluorescent sensor and resulted in half the number of visits to the BSL3 lab (five versus ten).

In situ near-infrared (NIR) versus high-throughput mid-infrared (MIR) spectroscopy to monitor biopharmaceutical production

The development of biopharmaceutical manufacturing processes presents critical constraints, with the major constraint being that living cells synthesize these molecules, presenting inherent behavior variability due to their high sensitivity to small fluctuations in the cultivation environment. To speed up the development process and to control this critical manufacturing step, it is relevant to develop high-throughput and in situ monitoring techniques, respectively. Here, high-throughput mid-infrared (MIR) spectral analysis of dehydrated cell pellets and in situ near-infrared (NIR) spectral analysis of the whole culture broth were compared to monitor plasmid production in recombinant Escherichia coli cultures. Good partial least squares (PLS) regression models were built, either based on MIR or NIR spectral data, yielding high coefficients of determination (R(2)) and low predictive errors (root mean square error, or RMSE) to estimate host cell growth, plasmid production, carbon source consumption (glucose and glycerol), and by-product acetate production and consumption. The predictive errors for biomass, plasmid, glucose, glycerol, and acetate based on MIR data were 0.7 g/L, 9 mg/L, 0.3 g/L, 0.4 g/L, and 0.4 g/L, respectively, whereas for NIR data the predictive errors obtained were 0.4 g/L, 8 mg/L, 0.3 g/L, 0.2 g/L, and 0.4 g/L, respectively. The models obtained are robust as they are valid for cultivations conducted with different media compositions and with different cultivation strategies (batch and fed-batch). Besides being conducted in situ with a sterilized fiber optic probe, NIR spectroscopy allows building PLS models for estimating plasmid, glucose, and acetate that are as accurate as those obtained from the high-throughput MIR setup, and better models for estimating biomass and glycerol, yielding a decrease in 57 and 50% of the RMSE, respectively, compared to the MIR setup. However, MIR spectroscopy could be a valid alternative in the case of optimization protocols, due to possible space constraints or high costs associated with the use of multi-fiber optic probes for multi-bioreactors. In this case, MIR could be conducted in a high-throughput manner, analyzing hundreds of culture samples in a rapid and automatic mode.

Evaluation of fluorimetric pH sensors for bioprocess monitoring at low pH

Optical chemical sensors are the standard for pH monitoring in small-scale bioreactors such as microtiter plates, shaking flasks or other single-use bioreactors. The dynamic pH range of the so far commercially available fluorescent pH sensors applied in small-scale bioreactors is restricted to pH monitoring around neutral pH, although many fermentation processes are performed at pH < 6 on industrial scale. Thus, two new prototype acidic fluorescence pH sensors immobilized in single-use stirred-tank bioreactors, one with excitation at 470 nm and emission at 550 nm (sensor 470/550) and the other with excitation at 505 nm and emission at 600 nm (sensor 505/600), were characterized with respect to dynamic ranges and operational stability in representative fermentation media. Best resolution and dynamic range was observed with pH sensor 505/600 in mineral medium (dynamic range of 3.9 < pH < 7.2). Applying the same pH sensors to complex medium results in a drastic reduction of resolution and dynamic ranges. Yeast extract in complex medium was found to cause background fluorescence at the sensors' operating wavelength combinations. Optical isolation of the sensor by adding a black colored polymer layer above the sensor spot and fixing an aperture made of adhesive photoresistant foil between the fluorescence reader and the transparent bottom of the polystyrene reactors enabled full re-establishment of the sensor's characteristics. Reliability and operational stability of sensor 505/600 was shown by online pH monitoring (4.5 < pH < 5.8) of parallel anaerobic batch fermentations of Clostridium acetobutylicum for the production of acetone, butanol and ethanol (ABE) with offline pH measurements with a standard glass electrode as reference.

Hybrid intelligent control of substrate feeding for industrial fed-batch chlortetracycline fermentation process

The lack of accurate process models and reliable online sensors for substrate measurements poses significant challenges for controlling substrate feeding accurately, automatically and optimally in fed-batch fermentation industries. It is still a common practice to regulate the feeding rate based upon manual operations. To address this issue, a hybrid intelligent control method is proposed to enable automatic substrate feeding. The resulting control system consists of three modules: a presetting module for providing initial set-points; a predictive module for estimating substrate concentration online based on a new time interval-varying soft sensing algorithm; and a feedback compensator using expert rules. The effectiveness of the proposed approach is demonstrated through its successful applications to the industrial fed-batch chlortetracycline fermentation process.

Shine a light on immobilized enzymes: real-time sensing in solid supported biocatalysts

Enzyme immobilization on solid supports has been key to biotransformation development. Although technologies for immobilization have largely reached maturity, the resulting biocatalysts are not well understood mechanistically. One limitation is that their internal environment is usually inferred from external data. Therefore, biological consequences of the immobilization remain masked by physical effects of mass transfer, obstructing further development. Work reviewed herein shows that opto-chemical sensing performed directly within the solid support enables the biocatalyst's internal environment to be uncovered quantitatively and in real time. Non-invasive methods of intraparticle pH and O2 determination are presented, and their use as process analytical tools for development of heterogeneous biocatalysts is described. Method diversification to other analytes remains a challenging task for the future.

Model-based analysis on the extractability of information from data in dynamic fed-batch experiments

Dynamic changes of physiological bioprocess parameters, e.g. a change in the specific growth rate μ, are frequently observed during industrial manufacturing as well as bioprocess development. A quantitative description of these variations is of great interest, since it can bring elucidation to the physiological state of the culture. The goal of this contribution was to show limitations and issues for the calculation of rates with regard to temporal resolution for dynamic fed-batch experiments. The impact of measurement errors, temporal resolution and the physiological activity on the signal to noise ratio (SNR) of the calculated rates was evaluated using an in-silico approach. To make use of that in practice, a generally applicable rule of thumb equation for the estimation of the SNR of specific rates was presented. The SNR calculated by this rule of thumb equation helps with definition of sampling intervals and making a decision whether an observed change is statistically significant or should be attributed to random error. Furthermore, a generic reconciliation approach to remove random as well as systematic error from data was presented. This reconciliation technique requires only little prior knowledge. The validity of the proposed tools was checked with real data from a fed-batch culture of E. coli with dynamic variations due to feed profile. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 2013

Oxygen transfer characteristics of miniaturized bioreactor systems

Since their introduction in 2001 miniaturized bioreactor systems have made great advances in function and performance. In this article the dissolved oxygen (DO) transfer performance of submilliliter microbioreactors, and 1–10 mL minibioreactors was examined. Microbioreactors have reached k_La values of 460 h^-1, and are offering instrumentation and some functionality comparable to production systems, but at high throughput screening volumes. Minibioreactors, aside from one 1,440 h^-1k_La system, have not offered as high rates of DO transfer, but have demonstrated superior integration with automated fluid handling systems. Microbioreactors have been typically limited to studies with E. coli, while minibioreactors have offered greater versatility in this regard. Further, mathematical relationships confirming the applicability of k_La measurements across all scales have been derived, and alternatives to fluorescence lifetime DO sensors have been evaluated. Finally, the influence on reactor performance of oxygen uptake rate (OUR), and the possibility of its real-time measurement have been explored. Biotechnol. Bioeng. 2013; 110: 1005–1019. © 2012 Wiley Periodicals, Inc.

Acoustofluidics 21: ultrasound-enhanced immunoassays and particle sensors

In part 21 of the tutorial series "Acoustofluidics--exploiting ultrasonic standing wave forces and acoustic streaming in microfluidic systems for cell and particle manipulation", we review applications of ultrasonic standing waves used for enhancing immunoassays and particle sensors. The paper covers ultrasonic enhancement of bead-based immuno-agglutination assays, bead-based immuno-fluorescence assays, vibrational spectroscopy sensors and cell deposition on a sensor surface.

An advanced monitoring platform for rational design of recombinant processes

Bioprocess engineering is an application-oriented science in an interdisciplinary environment, and a meaningful combination of different scientific disciplines is the only way to meet the challenges of bioprocess complexity. Setting up a reasoned process monitoring platform is the first step in an iterative procedure aiming at process and systems understanding, being the key to rational and innovative bioprocess design. This chapter describes a comprehensive process monitoring platform and how the resulting knowledge is translated into new strategies in process and/or host cell design.

Real-time estimation of biomass and specific growth rate in physiologically variable recombinant fed-batch processes

The real-time measurement of biomass has been addressed since many years. The quantification of biomass in the induction phase of a recombinant bioprocess is not straight forward, since biological burden, caused by protein expression, can have a significant impact on the cell morphology and physiology. This variability potentially leads to poor generalization of the biomass estimation, hence is a very important issue in the dynamic field of process development with frequently changing processes and producer lines. We want to present a method to quantify “biomass” in real-time which avoids off-line sampling and the need for representative training data sets. This generally applicable soft-sensor, based on first principles, was used for the quantification of biomass in induced recombinant fed-batch processes. Results were compared with “state of the art” methods to estimate the biomass concentration and the specific growth rate µ. Gross errors such as wrong stoichiometric assumptions or sensor failure were detected automatically. This method allows for variable model coefficients such as yields in contrast to other process models, hence does not require prior experiments. It can be easily adapted to a different growth stoichiometry; hence the method provides good generalization, also for induced culture mode. This approach estimates the biomass (or anabolic bioconversion) in induced fed-batch cultures in real-time and provides this key variable for process development for control purposes.

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.

Automated measurement and monitoring of bioprocesses: key elements of the M(3)C strategy

The state-of-routine monitoring items established in the bioprocess industry as well as some important state-of-the-art methods are briefly described and the potential pitfalls discussed. Among those are physical and chemical variables such as temperature, pressure, weight, volume, mass and volumetric flow rates, pH, redox potential, gas partial pressures in the liquid and molar fractions in the gas phase, infrared spectral analysis of the liquid phase, and calorimetry over an entire reactor. Classical as well as new optical versions are addressed. Biomass and bio-activity monitoring (as opposed to "measurement") via turbidity, permittivity, in situ microscopy, and fluorescence are critically analyzed. Some new(er) instrumental analytical tools, interfaced to bioprocesses, are explained. Among those are chromatographic methods, mass spectrometry, flow and sequential injection analyses, field flow fractionation, capillary electrophoresis, and flow cytometry. This chapter surveys the principles of monitoring rather than compiling instruments.

Online analysis and process control in recombinant protein production (review)

Online analysis and control is essential for efficient and reproducible bioprocesses. A key factor in real-time control is the ability to measure critical variables rapidly. Online in situ measurements are the preferred option and minimize the potential loss of sterility. The challenge is to provide sensors with a good lifespan that withstand harsh bioprocess conditions, remain stable for the duration of a process without the need for recalibration, and offer a suitable working range. In recent decades, many new techniques that promise to extend the possibilities of analysis and control, not only by providing new parameters for analysis, but also through the improvement of accepted, well practiced, measurements have arisen.