Expert systems in the control of animal cell culture processes: Potentials,functions, and perspectives

In recent years, the development of advanced systems for bioprocess monitoring and control has become an area of intensive research. Along with traditional techniques, there are several new approaches which are increasingly being applied to bioprocess operations. Among these, of special note is expert system technology, which provides possibilities for the design of efficient bioprocess control systems with new functional capabilities. This technology has been successfully applied to variety of microbial processes at laboratory and industrial scale. The present paper analyzes the possibility for application of expert systems to animal cell cultures processes whose high complexity is well suited to expert control. The discussion focuses on the organization and the functionality of the intelligent control systems, and covers some practical aspects of their design.     

Bioprocess monitoring by marker gene analysis

The optimization and the scale up of industrial fermentation processes require an efficient and possibly comprehensive analysis of the physiology of the production system throughout the process development. Furthermore, to ensure a good quality control of established bioprocesses, on-line analysis techniques for the determination of marker gene expression are of interest to monitor the productivity and the safety of bioprocesses. A prerequisite for such analyses is the knowledge of genes, the expression of which is critical either for the productivity or for the performance of the bioprocess. This work reviews marker genes that are specific indicators for stress- and nutrient-limitation conditions or for the physiological status of the bacterial production hosts Bacillus subtilis, Bacillus licheniformis and Escherichia coli. The suitability of existing gene expression analysis techniques for bioprocess monitoring is discussed. Analytical approaches that enable a robust and sensitive determination of selected marker mRNAs or proteins are presented.     

Microtiter plate‐based cultivation to investigate the growth of filamentous fungi

Microscale bioprocessing techniques are rapidly emerging as a means to increase the speed of bioprocess design and to reduce material consumption. However, there is still a lack of suitable parallelized techniques to investigate the industrially important group of filamentous bacteria and fungi. Cultivation of filamentous organisms in shake flasks is still the favored technique for comparing and optimizing cultivation conditions of production strains at mL‐scale. In this paper, the application of a microtiter plate‐based cultivation system in combination with the filamentous fungus Aspergillus niger was investigated. A protocol for reproducible cultivation was developed and evaluated. Productivity of A. niger concerning the rose‐like aroma compound 2‐phenylethanol showed low standard deviations while regular and consistent morphologies appeared in the parallelized system. Furthermore, the effect of addition of microparticles on the morphology was investigated. The results can be used to accelerate the process development with A. niger and other filamentous organisms.     

我国工业生物过程工程研究进展

工业生物技术的进步离不开工业生物过程工程研究的不断深入及发展,我国作为工业发酵大国在工业生物技术由实验室向产业化转化过程中面对诸多挑战,由此而逐渐发展起来的我国工业生物过程工程发展先后经历了多个阶段,伴随着不同阶段的发展,我国的工业生物技术水平得到不断的提升。本文重点回顾了近三、四十年来我国工业生物过程工程发展的历程,包括早期由化工过程研究引入的动力学模型化研究、基于过程控制的优化理论与方法的应用、基于过程在线监测技术发展起来的参数相关性分析方法、过程多尺度理论的建立、基于现代固态发酵的新型固态发酵罐的设计及优化技术发展等。通过对生物过程工程发展历程的回顾对先进工业生物过程发展面临的技术难题及由此引出的未来发展重点方向进行了探讨。     

Bioprocess development for endospore production by Bacillus coagulans using an optimized chemically defined medium

Bacillus coagulans is a promising probiotic, because it combines probiotic properties of Lactobacillus and the ability of Bacillus to form endospores. Due to this hybrid relationship, cultivation of this organism is challenging. As the probiotics market continues to grow, there is a new focus on the production of these microorganisms. In this work, a strain-specific bioprocess for B. coagulans was developed to support growth on one hand and ensure sporulation on the other hand. This circumstance is not trivial, since these two metabolic states are contrary. The developed bioprocess uses a modified chemically defined medium which was further investigated in a one-factor-at-a-time assay after adaptation. A transfer from the shake flask to the bioreactor was successfully demonstrated in the scope of this work. The investigated process parameters included temperature, agitation and pH-control. Especially the pH-control improved the sporulation in the bioreactor when compared to shake flasks. The bioprocess resulted in a sporulation efficiency of 80%–90%. This corresponds to a sevenfold increase in sporulation efficiency due to a transfer to the bioreactor with pH-control. Additionally, a design of experiment (DoE) was conducted to test the robustness of the bioprocess. This experiment validated the beforementioned sporulation efficiency for the developed bioprocess. Afterwards the bioprocess was then scaled up from a 1 L scale to a 10 L bioreactor scale. A comparable sporulation efficiency of 80% as in the small scale was achieved. The developed bioprocess facilitates the upscaling and application to an industrial scale, and can thus help meet the increasing market for probiotics.     

Accelerated design of bioconversion processes using automated microscale processing techniques

Microscale processing techniques are rapidly emerging as a means to increase the speed of bioprocess design and reduce material requirements. Automation of these techniques can reduce labour intensity and enable a wider range of process variables to be examined. This article examines recent research on various individual microscale unit operations including microbial fermentation, bioconversion and product recovery techniques. It also explores the potential of automated whole process sequences operated in microwell formats. The power of the whole process approach is illustrated by reference to a particular bioconversion, namely the Baeyer-Villiger oxidation of bicyclo[3.2.0]hept-2-en-6-one for the production of optically pure lactones.     

Scale-up of a new bacterial mannitol production process

D-Mannitol is a sugar alcohol with applications in chemistry, food and pharmaceutical industries, and medicine. Commercially, mannitol is produced by catalytic hydrogenation. Although this process is widely used, it is not optimal for mannitol production. New processes, including chemical, enzymatic, and microbial processes, are frequently developed and evaluated against the existing hydrogenation processes. In earlier papers, we have described the identification of a food-grade lactic acid bacterium strain, Leuconostoc mesenteroides ATCC-9135, with efficient mannitol production capabilities and the development and optimization of a new bioprocess in which the strain was applied. The new bioprocess is simple. It requires a reduced bioreactor with the following features: sterilization, pH and T control (at mild conditions), and slow mixing. The contamination risk of the new bioprocess is low, and the downstream processing protocol comprises simple, widely used unit operations: evaporation, crystallization, crystal separation, and drying. On a 2-L laboratory scale, high mannitol yields from fructose (93-97%) and volumetric mannitol productivities (>20 g L(-1) h(-1)) were achieved. In this paper, the scalability of the new bioprocess was tested on a small pilot scale (100 L). In the pilot plant, production levels were achieved similar to those in the laboratory. Also, high-purity mannitol crystals were obtained at similar yield levels. The results presented in this paper indicate that the new bioprocess can easily be scaled-up to an industrial scale and that the production levels achieved with it are comparable to the catalytic hydrogenation processes.     

Affinity Chromatography: An Enabling Technology for Large‐Scale Bioprocessing

Affinity chromatography (AC) has been used in large‐scale bioprocessing for almost 40 years and is considered the preferred method for primary capture in downstream processing of various types of biopharmaceuticals. The objective of this mini‐review is to provide an overview of a) the history of bioprocess AC, b) the current state of platform processes based on affinity capture steps, c) the maturing field of custom developed bioprocess affinity resins, d) the advantages of affinity capture‐based downstream processing in comparison to other forms of chromatography, and e) the future direction for bioprocess scale AC. The use of AC can result in economic advantages by enabling the standardization of process development and the manufacturing processes and the use of continuous operations in flexible multiproduct production suites. These concepts are discussed from a growing field of custom affinity bioprocess resin perspective. The custom affinity resins not only address the need for a capture resin for non‐platformable processes, but also can be employed in polishing applications, where they are used to define and control drug substance composition by separating specific product variants from the desired product form.     

Advanced near‐infrared monitor for stable real‐time measurement and control of Pichia pastoris bioprocesses

Near‐infrared spectroscopy is considered to be one of the most promising spectroscopic techniques for upstream bioprocess monitoring and control. Traditionally the nature of near‐infrared spectroscopy has demanded multivariate calibration models to relate spectral variance to analyte concentrations. The resulting analytical measurements have proven unreliable for the measurement of metabolic substrates for bioprocess batches performed outside the calibration process. This paper presents results of an innovative near‐infrared spectroscopic monitor designed to follow the concentrations of glycerol and methanol, as well as biomass, in real time and continuously during the production of a monoclonal antibody by a Pichia pastoris high cell density process. A solid state instrumental design overcomes the ruggedness limitations of conventional interferometer‐based spectrometers. Accurate monitoring of glycerol, methanol, and biomass is demonstrated over 274 days postcalibration. In addition, the first example of feedback control to maintain constant methanol concentrations, as low as 1 g/L, is presented. Postcalibration measurements over a 9‐month period illustrate a level of reliability and robustness that promises its adoption for online bioprocess monitoring throughout product development, from early laboratory research and development to pilot and manufacturing scale operation. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:749–759, 2014     

On-line infrared spectroscopy for bioprocess monitoring

One of the major aims of bioprocess engineering is the real-time monitoring of important process variables. This is the basis of precise process control and is essential for high productivity as well as the exact documentation of the overall production process. Infrared spectroscopy is a powerful analytical technique to analyze a wide variety of organic compounds. Thus, infrared sensors are ideal instruments for bioprocess monitoring. The sensors are non-invasive, have no time delay due to sensor response times, and have no influence on the bioprocess itself. No sampling is necessary, and several components can be analyzed simultaneously. In general, the direct monitoring of substrates, products, metabolites, as well as the biomass itself is possible. In this review article, insights are provided into the different applications of infrared spectroscopy for bioprocess monitoring and the complex data interpretation. Different analytical techniques are presented as well as example applications in different areas.     

Application of a multiphase microreactor chemostat for the determination of reaction kinetics of Staphylococcus carnosus

Bioprocess and Biosystems Engineering - Bioreactors at the microliter scale offer a promising approach to accelerate bioprocess development. Advantages of such microbioreactors include a reduction...     

Machine learning in bioprocess development: from promise to practice

Fostered by novel analytical techniques, digitalization, and automation, modern bioprocess development provides large amounts of heterogeneous experimental data, containing valuable process information. In this context, data-driven methods like machine learning (ML) approaches have great potential to rationally explore large design spaces while exploiting experimental facilities most efficiently. Herein we demonstrate how ML methods have been applied so far in bioprocess development, especially in strain engineering and selection, bioprocess optimization, scale-up, monitoring, and control of bioprocesses. For each topic, we will highlight successful application cases, current challenges, and point out domains that can potentially benefit from technology transfer and further progress in the field of ML.     

Assessment of near-infrared spectral information for rapid monitoring of bioprocess quality.

Access to real-time process information is desirable for consistent and efficient operation of bioprocesses. Near-infrared spectroscopy (NIRS) is known to have potential for providing real-time information on the quantitative levels of important bioprocess variables. However, given the fact that a typical NIR spectrum encompasses information regarding almost all the constituents of the sample matrix, there are few case studies that have investigated the spectral details for applications in bioprocess quality assessment or qualitative bioprocess monitoring. Such information would be invaluable in providing operator-level assistance on the progress of a bioprocess in industrial-scale productions. We investigated this aspect and report the results of our investigation. Near-infrared spectral information derived from scanning unprocessed culture fluid (broth) samples from a complex antibiotic production process was assessed for a data set that incorporated bioprocess variations. Principal component analysis was applied to the spectral data and the loadings and scores of the principal components studied. Changes in the spectral information that corresponded to variations in the bioprocess could be deciphered. Despite the complexity of the matrix, near-infrared spectra of the culture broth are shown to have valuable information that can be deconvoluted with the help of factor analysis techniques such as principal component analysis (PCA). Although complex to interpret, the loadings and score plots are shown to offer potential in process diagnosis that could be of value in the rapid assessment of process quality, and in data assessment prior to quantitative model development.     

Metabolomic profiling of CHO fed-batch growth phases at 10, 100, and 1,000 L

Established bioprocess monitoring is based on quick and reliable methods, including cell count and viability measurement, extracellular metabolite measurement, and the measurement of physicochemical qualities of the cultivation medium. These methods are sufficient for monitoring of process performance, but rarely give insight into the actual physiological states of the cell culture. However, understanding of the latter is essential for optimization of bioprocess development. Our study used LC-MS metabolomics as a tool for additional resolution of bioprocess monitoring and was designed at three bioreactors scales (10 L, 100 L, and 1,000 L) to gain insight into the basal metabolic states of the Chinese hamster ovary (CHO) cell culture during fed-batch. Metabolites characteristics of the four growth stages (early and late exponential phase, stationary phase, and the phase of decline) were identified by multivariate analysis. Enriched metabolic pathways were then established for each growth phase using the CHO metabolic network model. Biomass generation and nucleotide synthesis were enriched in early exponential phase, followed by increased protein production and imbalanced glutathione metabolism in late exponential phase. Glycolysis became downregulated in stationary phase and amino-acid metabolism increased. Phase of culture decline resulted in rise of oxidized glutathione and fatty acid concentrations. Intracellular metabolic profiles of the CHO fed-batch culture were also shown to be consistent with scale and thus demonstrate metabolomic profiling as an informative method to gain physiological insight into the cell culture states during bioprocess regardless of scale.     

Apoptosis: A mammalian cell bioprocessing perspective

Apoptosis is a form of programmed and controlled cell death that accounts for the majority of cellular death in bioprocesses. Cell death affects culture longevity and product quality; it is instigated by several stresses experienced by the cells within a bioreactor. Understanding the factors that cause apoptosis as well as developing strategies that can protect cells is crucial for robust bioprocess development. This review aims to a) address apoptosis from a bioprocess perspective; b) describe the significant apoptotic mechanisms linking them to the most relevant stresses encountered in bioreactors; c) discuss the design of operating conditions in order to avoid cell death; d) focus on industrially relevant cell lines; and e) present anti-apoptosis strategies including cell engineering and model-based optimization of bioprocesses. In addition, the importance of apoptosis in quality-by-design bioprocess development from clone screening to production scale are highlighted.     

Data-based modeling and analysis of bioprocesses: some real experiences

Data-generated models find numerous applications in areas where the speed of collection and logging of data surpasses the ability to analyze it. This work is meant to addresses some of the challenges and difficulties encountered in the practical application of these methods in an industrial setting and, more specifically, in the bioprocess industry. Neural network and principal component models are the two topics that are covered in detail in this paper. A review of these modeling technologies as applied to bioprocessing is provided, and four original case studies using industrial fermentation data are presented that utilize these models in the context of prediction and monitoring of bioprocess performance.     

Bioprocess engineering: now and beyond 2000

Abstract: Bioprocess engineering may be defined as the translation of life-science discoveries into practical products, processes, or systems capable of serving the needs of society. It is a critical link from discovery to commercialization. Current bioprocess engineering is primarily focused on biopharmaceutical products of high dollar value per gram such as erythropoietin or growth hormones. However, other products of current interest include ethanol, amino acids, organic acids, antibiotics, and specialty chemicals. Current challenges for increased use of bioprocesses for producing bulk and semi-bulk chemicals include both technical and infrastructural barriers. Technical barriers are easy to identify and at times can be overcome by engineering improvements or changes brought about radical developments in science (e.g. recombinant DNA). Infrastructural barriers, such as raw-material substitutions or educational limitations are more difficult to define and change. Recently the National Academy of Sciences examined barriers to bioprocess engineering and issued a report entitled: "Putting Biotechnology to Work: Bioprocess Engineering". A key recommendation was the establishment of a coordinated long-range plan of research, development, training and education in bioprocess engineering involving participation by industry, academe and the federal government. The report was the first national analysis devoted entirely to bioprocess engineering and covered new topics such as space bioprocess engineering. Other topics covered by the author include the current state of the US chemical industry and future directions in three promising areas of bioprocess engineering environmental bioprocess engineering, marine bioprocess engineering and microsystem bioprocess engineering.     

A reinforcement learning-based hybrid modeling framework for bioprocess kinetics identification

Constructing predictive models to simulate complex bioprocess dynamics, particularly time-varying (i.e., parameters varying over time) and history-dependent (i.e., current kinetics dependent on historical culture conditions) behavior, has been a longstanding research challenge. Current advances in hybrid modeling offer a solution to this by integrating kinetic models with data-driven techniques. This article proposes a novel two-step framework: first (i) speculate and combine several possible kinetic model structures sourced from process and phenomenological knowledge, then (ii) identify the most likely kinetic model structure and its parameter values using model-free Reinforcement Learning (RL). Specifically, Step 1 collates feasible history-dependent model structures, then Step 2 uses RL to simultaneously identify the correct model structure and the time-varying parameter trajectories. To demonstrate the performance of this framework, a range of in-silico case studies were carried out. The results show that the proposed framework can efficiently construct high-fidelity models to quantify both time-varying and history-dependent kinetic behaviors while minimizing the risks of over-parametrization and over-fitting. Finally, the primary advantages of the proposed framework and its limitation were thoroughly discussed in comparison to other existing hybrid modeling and model structure identification techniques, highlighting the potential of this framework for general bioprocess modeling.     

Economic analysis of pilot‐scale production of B‐phycoerythrin

β‐Phycoerythrin is a color protein with several applications, from food coloring to molecular labeling. Depending on the application, different purity is required, affecting production cost and price. Different production and purification strategies for B‐phycoerythrin have been developed, the most studied are based on the production using Porphyridium cruentum and purified using chromatographic techniques or aqueous two‐phase systems. The use of the latter can result in a less expensive and intensive recovery of the protein, but there is lack of a proper economic analysis to study the effect of using aqueous two‐phase systems in a scaled‐up process. This study analyzed the production of B‐Phycoerythrin using real data obtained during the scale‐up of a bioprocess using specialized software (BioSolve, Biopharm Services, UK). First, a sensitivity analysis was performed to identify critical parameters for the production cost, then a Monte Carlo analysis to emulate real processes by adding uncertainty to the identified parameters. Next, the bioprocess was analyzed to determine its financial attractiveness and possible optimization strategies were tested and discussed. Results show that aqueous two‐phase systems retain their advantages of low cost and intensive recovery (54.56%); the costs of production per gram calculated (before titer optimization: US$15,709 and after optimization: US$2,374) allowed to obtain profit (in the range of US$millions in a 10‐year period) for a potential company taking this production method by comparing the production cost against commercial prices. The bioprocess analyzed is a promising and profitable method for the generation of a highly purified B‐phycoerythrin. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1472–1479, 2016