Development of monitoring and control systems for biotechnological processes

The field of biotechnology represents an important research area that has gained increasing success in recent times. Characterized by the involvement of biological organisms in manufacturing processes, its areas of application are broad and include the pharmaceuticals, agri-food, energy, and even waste treatment. The implication of living microorganisms represents the common element in all bioprocesses. Cell cultivations is undoubtedly the key step that requires maintaining environmental conditions in precise and defined ranges, having a significant impact on the process yield and thus on the desired product quality. The apparatus in which this process occurs is the bioreactor. Unfortunately, monitoring and controlling these processes can be a challenging task because of the complexity of the cell growth phenomenon and the limited number of variables can be monitored in real-time. The thesis presented here focuses on the monitoring and control of biotechnological processes, more specifically in the production of bioethanol by fermentation of sugars using yeasts. The study conducted addresses several issues related to the monitoring and control of the bioreactor, in which the fermentation takes place. First, the topic concerning the lack of proper sensors capable of providing online measurements of key variables (biomass, substrate, product) is investigated. For this purpose, nonlinear estimation techniques are analyzed to reconstruct unmeasurable states. In particular, the geometric observer approach is applied to select the best estimation structure and then a comparison with the extended Kalman filter is reported. Both estimators proposed demonstrate good estimation capabilities as input model parameters vary. Guaranteeing the achievement of the desired ethanol composition is the main goal of bioreactor control. To this end, different control strategies, evaluated for three different scenarios, are analzyed. The results show that the MIMO system, together with an estimator for ethanol composition, ensure the compliance with product quality. After analyzing these difficulties through numeric simulations, this research work shifts to testing a specific biotechnological process such as manufacturing bioethanol from brewery’s spent grain (BSG) as renewable waste biomass. Both acid pre-treatment, which is necessary to release sugars, and fermentation are optimized. Results show that a glucose yield of 18.12 per 100 g of dried biomass is obtained when the pre-treatment step is performed under optimized conditions (0.37 M H2SO4, 10% S-L ratio). Regarding the fermentation, T=25°C, pH=4.5, and inoculum volume equal to 12.25% v/v are selected as the best condition, at which an ethanol yield of 82.67% evaluated with respect to theoretical one is obtained. As a final step, the use of Raman spectroscopy combined with chemometric techniques such as Partial Least Square (PLS) analysis is evaluated to develop an online sensor for fermentation process monitoring. The results show that the biomass type involved significantly affects the acquired spectra, making them noisy and difficult to interpret. This represents a nontrivial limitation of the applied methodology, for which more experimental data and more robust statistical techniques could be helpful

Sensors and Techniques for On-Line Determination of Cell Viability in Bioprocess Monitoring

In recent years, the bioprocessing industry has experienced significant growth and is increasingly emerging as an important economic sector. Here, efficient process management and constant control of cellular growth are essential. Good product quality and yield can only be guaranteed with high cell density and high viability. Whereas the on-line measurement of physical and chemical process parameters has been common practice for many years, the on-line determination of viability remains a challenge and few commercial on-line measurement methods have been developed to date for determining viability in industrial bioprocesses. Thus, numerous studies have recently been conducted to develop sensors for on-line viability estimation, especially in the field of optical spectroscopic sensors, which will be the focus of this review. Spectroscopic sensors are versatile, on-line and mostly non-invasive. Especially in combination with bioinformatic data analysis, they offer great potential for industrial application. Known as soft sensors, they usually enable simultaneous estimation of multiple biological variables besides viability to be obtained from the same set of measurement data. However, the majority of the presented sensors are still in the research stage, and only a few are already commercially available

Improvement of bioprocess monitoring: development of novel concepts

The advancement of bioprocess monitoring will play a crucial role to meet the future requirements of bioprocess technology. Major issues are the acceleration of process development to reduce the time to the market and to ensure optimal exploitation of the cell factory and further to cope with the requirements of the Process Analytical Technology initiative. Due to the enormous complexity of cellular systems and lack of appropriate sensor systems microbial production processes are still poorly understood. This holds generally true for the most microbial production processes, in particular for the recombinant protein production due to strong interaction between recombinant gene expression and host cell metabolism. Therefore, it is necessary to scrutinise the role of the different cellular compartments in the biosynthesis process in order to develop comprehensive process monitoring concepts by involving the most significant process variables and their interconnections. Although research for the development of novel sensor systems is progressing their applicability in bioprocessing is very limited with respect to on-line and in-situ measurement due to specific requirements of aseptic conditions, high number of analytes, drift, and often rather low physiological relevance. A comprehensive survey of the state of the art of bioprocess monitoring reveals that only a limited number of metabolic variables show a close correlation to the currently explored chemical/physical principles. In order to circumvent this unsatisfying situation mathematical methods are applied to uncover "hidden" information contained in the on-line data and thereby creating correlations to the multitude of highly specific biochemical off-line data. Modelling enables the continuous prediction of otherwise discrete off-line data whereby critical process states can be more easily detected. The challenging issue of this concept is to establish significant on-line and off-line data sets. In this context, online sensor systems are reviewed with respect to commercial availability in combination with the suitability of offline analytical measurement methods. In a case study, the aptitude of the concept to exploit easily available online data for prediction of complex process variables in a recombinant E. coli fed-batch cultivation aiming at the improvement of monitoring capabilities is demonstrated. In addition, the perspectives for model-based process supervision and process control are outlined

Benchmarking real-time monitoring strategies for ethanol production from lignocellulosic biomass

The goal of this paper is to review and critically assess different methods to monitor key process variables for ethanol production from lignocellulosic biomass. Because cellulose-based biofuels cannot yet compete with noncellulosic biofuels, process control and optimization are of importance to lower the production costs. This study reviews different monitoring schemes, to indicate what the added value of real-time monitoring is for process control. Furthermore, a comparison is made on different monitoring techniques to measure the off-gas, the concentrations of dissolved components in the inlet to the process, the concentrations of dissolved components in the reactor, and the biomass concentration. Finally, soft sensor techniques and available models are discussed, to give an overview of modeling techniques that analyze data, with the aim of coupling the soft sensor predictions to the control and optimization of cellulose to ethanol fermentation. The paper ends with a discussion of future needs and developmentsThis work was partially financed by the European Regional Development Fund (ERDF) and Region Zealand (Denmark) through the BIOPRO-SMV project. Furthermore, the work received funding from Innovation Fund Denmark (BIOPRO2 strategic research center, project number 4105-00020B). This project has also been supported partially by the EUDP project ‘Demonstration of 2G ethanol in full scale, MEC’ (Jr. no. 64015–0642). Finally, we wish to acknowledge the support obtained from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement number 713683 (COFUNDfellowsDTU) and from the Danish Council for Independent Research in the frame of the DFF FTP research project GREENLOGIC (grant agreement number 7017-00175A). Miguel Mauricio-Iglesias belongs to the Galician Competitive Research Group GRC2013-032 and the CRETUS strategic partnership (AGRUP2015/02), co-funded by FEDER (EU)S

The use of infrared spectroscopy to monitor bio-catalytic processes

This thesis was previously held under moratorium from 11th June 2013 until 11th June 2017.Industrial biotransformation processes are becoming increasingly important for the production of single enantiomers of both low value commodity and high value fine chemicals. Despite this demand and the regulatory authorities encouragement of a quality by design approach, the application of process analytical technology to these systems has, to date, been relatively limited. A more traditional off-line approach involving chromatographic methods is still commonly employed for the quantification of key analytes during the process. In-situ measurements tend to be limited to physical parameters of the system such as pH and dO₂, which give little information about the actual process progression. This study investigates the potential of applying infrared spectroscopic techniques to monitor and quantify the key components of de-racemisation and transaminase biotransformation processes. Multivariate models based on the near and mid infrared spectroscopic regions have been constructed for a variety of these processes. Each constructed model was subjected to an external validation procedure to ensure rigorous testing. Stoichiometric linkages were known to exist within these systems. Whilst steps were taken to ensure these linkages were broken, the contributors to each model were also carefully examined to ensure that co-linearity within the constructed models had been adequately addressed. Having constructed robust process models, mechanisms of ensuring the long-term suitability of the models were also investigated. This aimed to ensure the continued predictive ability of the constructed models following instrument maintenance, repair or replacement. Quantitative models resulted that were able to predict the key analyte concentrations of the external validation datasets over the course of the biotransformation processes. Predicted values from the constructed models were in good agreement with both the errors of calibration and cross validation associated with the models, and the actual concentrations predicted by the off-line chromatographic reference methods.Industrial biotransformation processes are becoming increasingly important for the production of single enantiomers of both low value commodity and high value fine chemicals. Despite this demand and the regulatory authorities encouragement of a quality by design approach, the application of process analytical technology to these systems has, to date, been relatively limited. A more traditional off-line approach involving chromatographic methods is still commonly employed for the quantification of key analytes during the process. In-situ measurements tend to be limited to physical parameters of the system such as pH and dO₂, which give little information about the actual process progression. This study investigates the potential of applying infrared spectroscopic techniques to monitor and quantify the key components of de-racemisation and transaminase biotransformation processes. Multivariate models based on the near and mid infrared spectroscopic regions have been constructed for a variety of these processes. Each constructed model was subjected to an external validation procedure to ensure rigorous testing. Stoichiometric linkages were known to exist within these systems. Whilst steps were taken to ensure these linkages were broken, the contributors to each model were also carefully examined to ensure that co-linearity within the constructed models had been adequately addressed. Having constructed robust process models, mechanisms of ensuring the long-term suitability of the models were also investigated. This aimed to ensure the continued predictive ability of the constructed models following instrument maintenance, repair or replacement. Quantitative models resulted that were able to predict the key analyte concentrations of the external validation datasets over the course of the biotransformation processes. Predicted values from the constructed models were in good agreement with both the errors of calibration and cross validation associated with the models, and the actual concentrations predicted by the off-line chromatographic reference methods

Optimization of insect cell based protein production processes - online monitoring, expression systems, scale-up

Due to the increasing use of insect cell based expression systems in research and industrial recombinant protein production, the development of efficient and reproducible production processes remains a challenging task. In this context, the application of online monitoring techniques is intended to ensure high and reproducible product qualities already during the early phases of process development. In the following chapter, the most common transient and stable insect cell based expression systems are briefly introduced. Novel applications of insect cell based expression systems for the production of insect derived antimicrobial peptides/proteins (AMPs) are discussed using the example of G. mellonella derived gloverin. Suitable in situ sensor techniques for insect cell culture monitoring in disposable and common bioreactor systems are outlined with respect to optical and capacitive sensor concepts. Since scale-up of production processes is one of the most critical steps in process development, a conclusive overview is given about scale up aspects for industrial insect cell culture processes

ECUT (Energy Conversion and Utilization Technologies) program: Biocatalysis Project

Fiscal year 1987 research activities and accomplishments for the Biocatalysis Project of the U.S. Department of Energy, Energy Conversion and Utilization Technologies (ECUT) Division are presented. The project's technical activities were organized into three work elements. The Molecular Modeling and Applied Genetics work element includes modeling and simulation studies to verify a dynamic model of the enzyme carboxypeptidase; plasmid stabilization by chromosomal integration; growth and stability characteristics of plasmid-containing cells; and determination of optional production parameters for hyper-production of polyphenol oxidase. The Bioprocess Engineering work element supports efforts in novel bioreactor concepts that are likely to lead to substantially higher levels of reactor productivity, product yields, and lower separation energetics. The Bioprocess Design and Assessment work element attempts to develop procedures (via user-friendly computer software) for assessing the economics and energetics of a given biocatalyst process

Fourier transform infrared spectroscopy, a powerful tool to monitor biopharmaceuticals production

A Escherichia coli é o microorganismo mais usado como hospedeiro para a produção de produtos recombinantes, tais como plasmídeos usados para terapia génica e vacinação de ADN. Desta forma, torna-se importante compreender as relações metabólicas complexas e a bioprodução de plasmídeo, que ocorre em ambientes de cultura dinâmicos, a fim de controlar e optimizar o desempenho do sistema de expressão recombinante. O objectivo principal deste trabalho consiste em avaliar a potencialidade da espectroscopia FT-IR para monitorizar e caracterizar a produção do plasmídeo pVAX-LacZ em culturas recombinantes de E. coli, nomeadamente para extrair informação relacionada com as variáveis críticas (biomassa, plasmídeo, fontes de carbono e acetato) e informação metabólica da célula hospedeira E. coli. Para tal, culturas de E. coli com diferentes concentrações de glucose e glicerol e diferentes estratégias de cultivo (batch e fed-batch) foram monitorizadas por espectroscopia de infravermelho perto (NIR) e de infravermelho médio (MIR). Tanto a espectroscopia NIR com a MIR permitiram extrair informação sobre as variáveis críticas do bioprocesso, através da construção de modelos de regressão por mínimos quadrados parciais, que resultaram em elevados coeficientes de regressão e baixos erros de previsão. A abordagem NIR apresenta a vantagem de aquisição em tempo real das variáveis do bioprocesso, já a abordagem MIR permite a leitura simultânea de centenas de amostras de várias culturas ao mesmo tempo através do uso multi-microplacas, sendo muito vantajosa nos casos de micro-bioreactores usados para optimização. Para além disso, como os espectros MIR apresentam mais informação do que os espectros NIR, uma vez que representam os modos de vibração fundamentais das biomoléculas, enquanto que os espectros NIR representam sobreposições e combinações de vibrações, os dados espectrais MIR também permitiram a aquisição de informação bioquímica ao longo das culturas de E. coli a partir da análise das componentes principais (PCA) bem como do estudo das características bioquímicas, tais como as reservas de glicogénio e os níveis de transcrição aparente. Portanto, a espectroscopia FT-IR apresenta assim características relevantes para a compreensão e monitorização do processo de produção de culturas recombinantes, sendo, de acordo com Quality-by-Design e Process Analytical Technology, muito importante para fins de controlo e optimização.Escherichia coli is the most used microorganism as host for the production of recombinant products, such as plasmids used for gene therapy and DNA vaccination. Therefore, it is important to understand the complex metabolic relationships and the plasmid bioproduction process occurring in dynamic culture environments, in order to control and optimize the performance of the recombinant expression system. The main goal of this work is to evaluate the potential of Fourier Transform Infrared (FT-IR) spectroscopy to monitor and characterize recombinant E. coli cultures producing the plasmid model pVAX-LacZ, namely to extract information concerning the critical variables (biomass, plasmid, carbon sources and the by-product acetate) and metabolic information regarding the host E. coli. To achieve that cultures of E. coli conducted with different mixture of glucose and glycerol and different cultivation strategies (batch and fed-batch) were monitored in-situ by a fiber optic probe in near- infrared (NIR) and of the cell pellets in at-line in high-throughput mode by mid-infrared (MIR) spectroscopy. Both NIR and MIR spectroscopy setup enabled to extract information regarding the critical variables of the bioprocess by the implementation of partial least square regression models that result in high regression coefficients and low prediction errors. The NIR setup presents the advantage of acquiring in real time the knowledge of the bioprocess variables, where the at-line measurements with the MIR setup presents more advantageous in cases of micro-bioreactors used in optimization protocols, enabling the simultaneously information acquisition of hundreds samples by using multi-microplates. Furthermore, as the MIR spectra presents more information than the NIR spectra, since it represents the fundamental vibration modes of biomolecules while the NIR spectra represents overtones and combinations of vibrations, the MIR data also enabled to acquire biochemical information along the E. coli cultures as pointed out in an principal component analysis and by the estimation of biochemical features as glycogen reserves and apparent transcriptional levels. Therefore, FT-IR spectroscopy presents relevant features towards the understanding and monitoring of the production process of recombinant cultures for control and optimization purposes, in according to the Quality-by-Design and the Process Analytical Technology