Showing papers on "Bioprocess published in 2019"
01 Feb 2019
TL;DR: The bioprocess conditions that affects BC production and the main possible applications of BC for food and food packaging purposes are overviewed.
Abstract: Bacterial cellulose (BC) has been produced for a number of applications, mainly focused on the biomedical area. Although there is a variety of interesting applications of BC for food and food packaging, only a few have been explored to the moment, since the high cost of BC production is usually considered as a limiting factor. On the other hand, several cost-effective culture media have been proposed, contributing to reduce BC production costs. This article overviews the bioprocess conditions that affects BC production and the main possible applications of BC for food and food packaging purposes.
257 citations
TL;DR: Recently, advances have been made in the various areas of bioprocessing and are being utilized to develop effective processes for producing recombinant proteins that can be used as therapeutics, vaccines, and diagnostic reagents.
Abstract: Infectious diseases, along with cancers, are among the main causes of death among humans worldwide. The production of therapeutic proteins for treating diseases at large scale for millions of individuals is one of the essential needs of mankind. Recent progress in the area of recombinant DNA technologies has paved the way to producing recombinant proteins that can be used as therapeutics, vaccines, and diagnostic reagents. Recombinant proteins for these applications are mainly produced using prokaryotic and eukaryotic expression host systems such as mammalian cells, bacteria, yeast, insect cells, and transgenic plants at laboratory scale as well as in large-scale settings. The development of efficient bioprocessing strategies is crucial for industrial production of recombinant proteins of therapeutic and prophylactic importance. Recently, advances have been made in the various areas of bioprocessing and are being utilized to develop effective processes for producing recombinant proteins. These include the use of high-throughput devices for effective bioprocess optimization and of disposable systems, continuous upstream processing, continuous chromatography, integrated continuous bioprocessing, Quality by Design, and process analytical technologies to achieve quality product with higher yield. This review summarizes recent developments in the bioprocessing of recombinant proteins, including in various expression systems, bioprocess development, and the upstream and downstream processing of recombinant proteins.
249 citations
TL;DR: The recent developments discussed here would not only give an overview of pertinent parameters for economic biosurfactant production but would also bring to fore multiple strategies that would open up new avenues of research that would go a long way in making biosurfacts a commercially successful compound of the current century.
Abstract: Biosurfactants are economically most sought after biotechnological compounds of the 21st century. However, inefficient bioprocessing has mitigated the economical commercial production of these compounds. Although much work is being done on the use of low-cost substrates for their production, a paucity of literature exists on the upcoming bioprocess optimization strategies and their successes and potential for economical biosurfactant production. This review discusses some of the latest developments and most promising strategies to enhance and economize the biosurfactant production process. Recent market analysis, developments in the field of optimally formulated cost credit substrates for enhanced product formation and subsequent process economization are few of the critical aspects highlighted here. Use of nanoparticles and coproduction of biosurfactant along with other commercially important compounds like enzymes, are other upcoming bioprocess intensification strategies. The recent developments discussed here would not only give an overview of pertinent parameters for economic biosurfactant production but would also bring to fore multiple strategies that would open up new avenues of research on biosurfactant production. This would go a long way in making biosurfactants a commercially successful compound of the current century.
198 citations
TL;DR: The importance of apoptosis in quality-by-design bioprocess development from clone screening to production scale are highlighted and anti-apoptosis strategies including cell engineering and model-based optimization of biop rocesses are highlighted.
91 citations
12 Jun 2019
TL;DR: This review highlights the vital aspects of a cultured meat bioreactor design that are often overlooked when parallels are drawn against fermentation processes such as brewing or recombinant protein production in the pharmaceutical industry.
Abstract: Cultured meat, as a cellular agriculture product, utilizes tissue engineering techniques and consequently faces not only cell culture challenges but also scale-up limitations. To ensure cultured meat is financially viable, efficient bioprocess design for scale-up is required. In this mini-review we focus on the design of the expansion bioreactor, and put it in context of the entire bioprocess by providing an overview of the upstream and downstream process considerations. As a full-scale cultured meat bioprocess is still hypothetical we include a review of the key factors and fundamental cell biology parameters required as input data for the design of a process with a product that is not only viable but price competitive. This review highlights the vital aspects of a cultured meat bioreactor design that are often overlooked when parallels are drawn against fermentation processes such as brewing or recombinant protein production in the pharmaceutical industry. Practical application and awareness of the concepts presented here will enable more accurate estimation of the production expenses and raw material requirements and form a basis for both further academic research and the design of industrial-scale processes in the field of cultured meat and the wider field of tissue engineering-based cellular agriculture.
81 citations
TL;DR: This study proposes an innovative hybrid modeling framework which takes advantages of both physics‐based and data‐driven modeling for bioprocess online monitoring, prediction, and optimization, demonstrating its high predictive and flexible capabilities as well as its potential for industrial application.
Abstract: Model-based online optimization has not been widely applied to bioprocesses due to the challenges of modeling complex biological behaviors, low-quality industrial measurements, and lack of visualization techniques for ongoing processes. This study proposes an innovative hybrid modeling framework which takes advantages of both physics-based and data-driven modeling for bioprocess online monitoring, prediction, and optimization. The framework initially generates high-quality data by correcting raw process measurements via a physics-based noise filter (a generally available simple kinetic model with high fitting but low predictive performance); then constructs a predictive data-driven model to identify optimal control actions and predict discrete future bioprocess behaviors. Continuous future process trajectories are subsequently visualized by re-fitting the simple kinetic model (soft sensor) using the data-driven model predicted discrete future data points, enabling the accurate monitoring of ongoing processes at any operating time. This framework was tested to maximize fed-batch microalgal lutein production by combining with different online optimization schemes and compared against the conventional open-loop optimization technique. The optimal results using the proposed framework were found to be comparable to the theoretically best production, demonstrating its high predictive and flexible capabilities as well as its potential for industrial application.
67 citations
TL;DR: The real trait of microalgae is explored through both thermochemical and biochemical conversion processes for the production of various biofuels such as biodiesel, bioethanol, biomethane, bio-oil, biohydrogen and other products.
66 citations
TL;DR: A two-steps bioprocess approach aimed at biohydrogen production via dark-fermentation, and polyhydroxyalkanoates-PHA production by mixed microbial cultures, was proposed to valorise two dairy-waste streams coming from cheese whey deproteinization.
66 citations
TL;DR: In this article, a two-stage bioprocessing system was developed as part of a power-to-protein approach to fix carbon dioxide in a first stage by anaerobic acetogenic bacteria, and grow yeast or fungi in a second stage under aerobic conditions with acetate as the intermediate metabolite.
Abstract: To prevent an environmental collapse while feeding a future human population of 10 billion people, dilute nitrogen in waste streams as a nitrogen source and carbon dioxide as a carbon source should be recovered and recycled into edible protein as part of the circular economy. For this to work, however, ample renewable electric power would be necessary to provide hydrogen from water electrolysis as an electron donor. We developed a two-stage bioprocessing system as part of a power-to-protein approach to fix carbon dioxide in a first stage by anaerobic acetogenic bacteria, and grow yeasts or fungi in a second stage under aerobic conditions with acetate as the intermediate metabolite. We were able to obtain a carbon yield of 25% as yeast biomass with a protein mass-fraction of ∼40–50% during a proof-of-concept experiment. We developed a technological solution to circumvent conventional agriculture for protein production, while still being able to provide protein for human consumption.
65 citations
TL;DR: A model-assisted Design of Experiments concept is introduced for the knowledge-based reduction of boundary values, where the parameters of a mathematical process model are estimated and the investigated factor combinations are simulated instead of experimentally derived.
Abstract: Design of Experiments methods offer systematic tools for bioprocess development in Quality by Design, but their major drawback is the user-defined choice of factor boundary values. This can lead to several iterative rounds of time-consuming and costly experiments. In this study, a model-assisted Design of Experiments concept is introduced for the knowledge-based reduction of boundary values. First, the parameters of a mathematical process model are estimated. Second, the investigated factor combinations are simulated instead of experimentally derived and a constraint-based evaluation and optimization of the experimental space can be performed. The concept is discussed for the optimization of an antibody-producing Chinese hamster ovary batch and bolus fed-batch process. The same optimal process strategies were found if comparing the model-assisted Design of Experiments (4 experiments each) and traditional Design of Experiments (16 experiments for batch and 29 experiments for fed-batch). This approach significantly reduces the number of experiments needed for knowledge-based bioprocess development.
57 citations
TL;DR: The results are suggestive of alternative methods for management of cheese whey, which may reduce its impact on the environment and result in production of value-added biochemicals.
TL;DR: An overview of the latest advances in oleaginous Yeasts and de novo lipid accumulation due to their high lipid accumulating ability, robustness and versatility across a range of substrates is provided.
TL;DR: An apparent revival of interest in complex fermentation is occurring, as well in the use of mixed strains in the production of food and beverages with more diverse and peculiar flavors impressed by a more complex micro-organisms interaction and the associated health functionalities.
Abstract: The fermentation of carbon sources by fungi leading to the production of foods and beverages represents one of the oldest and most economically significant of all biotechnologies. Also, some traditional fermented foods require a ripening period to develop their best sensorial characteristics. On ancient times, fermentation was carried out spontaneously. With scientific development, single strains were selected and adapted for use as starters in some large-scale food producing. Currently an apparent revival of interest in complex fermentation is occurring, as well in the use of mixed strains wondering production of food and beverages with more diverse and peculiar flavors impressed by a more complex micro-organisms interaction and the associated health functionalities.
TL;DR: These findings showed that recombinant plasmid-free E. coli strains are promising candidates for the production of vanillin at industrial scale and that a reduction of the cost of the bioconversion process requires approaches that minimize the toxicity of both ferulic acid and vanillin.
Abstract: The rising demand of bio-vanillin and the possibility to use microbial biotransformation to produce this compound from agroindustrial byproducts are economically attractive. However, there are still several bottlenecks, including substrate and product toxicity, formation of undesired products and genetic stability of the recombinant strains, that impede an efficient use of recombinant Escherichia coli strains to make the whole process cost effective. To overcome these problems, we developed a new E. coli strain, named FR13, carrying the Pseudomonas genes encoding feruloyl-CoA synthetase and feruloyl-CoA hydratase/aldolase integrated into the chromosome and, using resting cells, we demonstrated that the vanillin yield and selectivity were strongly affected by the physiological state of the cells, the temperature used for the growth and the recovery of the biomass and the composition and pH of the bioconversion buffer. The substrate consumption rate and the vanillin yield increased using a sodium/potassium phosphate buffer at pH 9.0 as bioconversion medium. Optimization of the bioprocess variables, using response surface methodology, together with the use of a two-phase (solid-liquid) system for the controlled release of ferulic acid allowed us to increase the vanillin yield up to 28.10 ± 0.05 mM. These findings showed that recombinant plasmid-free E. coli strains are promising candidates for the production of vanillin at industrial scale and that a reduction of the cost of the bioconversion process requires approaches that minimize the toxicity of both ferulic acid and vanillin.
TL;DR: The domestication and engineering of a scCO2-tolerant strain of Bacillus megaterium is reported, previously isolated from formation waters from the McElmo Dome CO2 field, to produce branched alcohols that have potential use as biofuels.
Abstract: Culture contamination, end-product toxicity, and energy efficient product recovery are long-standing bioprocess challenges. To solve these problems, we propose a high-pressure fermentation strategy, coupled with in situ extraction using the abundant and renewable solvent supercritical carbon dioxide (scCO2), which is also known for its broad microbial lethality. Towards this goal, we report the domestication and engineering of a scCO2-tolerant strain of Bacillus megaterium, previously isolated from formation waters from the McElmo Dome CO2 field, to produce branched alcohols that have potential use as biofuels. After establishing induced-expression under scCO2, isobutanol production from 2-ketoisovalerate is observed with greater than 40% yield with co-produced isopentanol. Finally, we present a process model to compare the energy required for our process to other in situ extraction methods, such as gas stripping, finding scCO2 extraction to be potentially competitive, if not superior. End-product toxicity, culture contamination, and energy efficient product recovery are long-standing issues in bioprocessing. Here, the authors address these problems using a fermentation strategy that combines microbial production of branched alcohols with supercritical carbon dioxide extraction.
TL;DR: The research avenues for bioprocess intensification connected to enhance selective sugar recovery and effective detoxification constitute the critical steps to develop future red macroalgae-derived galactose-based robust biohydrogen production system.
TL;DR: An approach to integrate data-driven methods with genome scale metabolic model for assessment of microbial bio-production (yield, titer and rate) and demonstrates a reasonably high cross-validation accuracy for prediction of E.coli factory performance metrics under presumed bioprocess and pathway conditions.
Abstract: Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks struggle to predict cell performance (including product titer or rate) under suboptimal metabolism and complex bioprocess conditions. On the other hand, machine learning, complementary to metabolic modeling necessitates large amounts of data. Building such a database for metabolic engineering designs requires significant manpower and is prone to human errors and bias. We propose an approach to integrate data-driven methods with genome scale metabolic model for assessment of microbial bio-production (yield, titer and rate). Using engineered E. coli as an example, we manually extracted and curated a data set comprising about 1200 experimentally realized cell factories from ~100 papers. We furthermore augmented the key design features (e.g., genetic modifications and bioprocess variables) extracted from literature with additional features derived from running the genome-scale metabolic model iML1515 simulations with constraints that match the experimental data. Then, data augmentation and ensemble learning (e.g., support vector machines, gradient boosted trees, and neural networks in a stacked regressor model) are employed to alleviate the challenges of sparse, non-standardized, and incomplete data sets, while multiple correspondence analysis/principal component analysis are used to rank influential factors on bio-production. The hybrid framework demonstrates a reasonably high cross-validation accuracy for prediction of E.coli factory performance metrics under presumed bioprocess and pathway conditions (Pearson correlation coefficients between 0.8 and 0.93 on new data not seen by the model).
TL;DR: The results of a study to identify the optimal settings to digest fish manure through a microbial-assisted aerobic bioprocess, using endogenous heterotrophic and nitrifying bacteria are presented.
TL;DR: The current research compares the performance of advanced physical and data‐driven models for dynamic bioprocess simulations subject to incomplete and scarce datasets, which to the best of the knowledge has never been addressed before and paves the way to facilitate future biop rocess modeling.
Abstract: Microorganism production and remediation processes are of critical importance to the next generation of sustainable industries. Undertaking mathematical treatment of dynamic biosystems operating at any spatial or temporal scale is essential to guarantee their performance and safety. However, constructing physical models remains a challenge due to the extreme complexity of process biological mechanisms. Data-driven models also encounter severe limitations because datasets from large-scale bioprocesses are often scarce without complete information and on a restricted operational space. To fill this gap, the current research compares the performance of advanced physical and data-driven models for dynamic bioprocess simulations subject to incomplete and scarce datasets, which to the best of our knowledge has never been addressed before. In specific, kinetic models were constructed by integrating different classic models, and state-of-the-art hyperparameter selection frameworks were developed to design artificial neural networks and Gaussian process regression models. An algae-bacteria consortium wastewater treatment process was selected to test the accuracy of these modeling strategies, as it is one of the most sophisticated biosystems due to the intricate mutualistic and competitive interactions. Based on the current results and available data, a heuristic model selection procedure is provided. This study paves the way to facilitate future bioprocess modeling.
TL;DR: It is desirable to investigate the response of strains to such heterogeneities to reduce the risk of failure during process scale‐up, as these effects have significant effects on process efficiency.
Abstract: Concentration gradients that occur in large industrial-scale bioreactors due to mass transfer limitations have significant effects on process efficiency. Hence, it is desirable to investigate the response of strains to such heterogeneities to reduce the risk of failure during process scale-up. Although there are various scale-down techniques to study these effects, scale-down strategies are rarely applied in the early developmental phases of a bioprocess, as they have not yet been implemented on small-scale parallel cultivation devices. In this study, we combine mechanistic growth models with a parallel mini-bioreactor system to create a high-throughput platform for studying the response of Escherichia coli strains to concentration gradients. As a scaled-down approach, a model-based glucose pulse feeding scheme is applied and compared with a continuous feed profile to study the influence of glucose and dissolved oxygen gradients on both cell physiology and incorporation of noncanonical amino acids into recombinant proinsulin. The results show a significant increase in the incorporation of the noncanonical amino acid norvaline in the soluble intracellular extract and in the recombinant product in cultures with glucose/oxygen oscillations. Interestingly, the amount of norvaline depends on the pulse frequency and is negligible with continuous feeding, confirming observations from large-scale cultivations. Most importantly, the results also show that a larger number of the model parameters are significantly affected by the scale-down scheme, compared with the reference cultivations. In this example, it was possible to describe the effects of oscillations in a single parallel experiment. The platform offers the opportunity to combine strain screening with scale-down studies to select the most robust strains for bioprocess scale-up.
TL;DR: The latest developments in the unit operation for downstream processing applications are discussed and a perspective on exploring precipitation for bioprocess intensification is provided.
TL;DR: A sustainable bioprocess was developed for the valorization of a no/low value substrate, i.e. waste frying oils with high content of free fatty acids, otherwise unsuitable for biodiesel production, together with an efficient conversion of the treated WFO into biodiesel.
Abstract: A sustainable bioprocess was developed for the valorization of a no/low value substrate, i.e. waste frying oils (WFOs) with high content of free fatty acids (FFAs), otherwise unsuitable for biodiesel production. The bioprocess was verified using both recombinant (Escherichia coli) and native (Pseudomonas resinovorans) polyhydroxyalkanoates (PHAs) producing cell factories. Microbial fermentation of WFOs provided a 2-fold advantage: i) the reduction of FFAs content resulting into an upgrading of the “exhausted waste oils” and ii) the production of a bio-based microbial polymer. Proper strain designing and process optimization allowed to achieve up to 1.5 g L−1 of medium chain length, mcl-PHAs, together with an efficient conversion (80% yield) of the treated WFO into biodiesel.
TL;DR: This paper provides a useful reference for researchers on the merits, drawbacks, achievements, and application of halophiles for bioproduction.
TL;DR: This review focuses on understanding the key factors that can enhance recombinant protein production in Pichia pastoris; they are the basis for a further discussion on future industrial applications with the aim of developing scalable alternative strategies that maximize yields and productivity.
TL;DR: In this study, a 15 L mammalian cell culture bioreactor was characterized with respect to kLa under varying process conditions, leading to an easy-to-apply model that allows real-time calculation of the oxygen uptake rate (THE AUTHORS') throughout the bioprocess without off-gas analyzers.
Abstract: In aerobic cell cultivation processes, dissolved oxygen is a key process parameter, and an optimal oxygen supply has to be ensured for proper process performance. To achieve optimal growth and/or product formation, the rate of oxygen transfer has to be in right balance with the consumption by cells. In this study, a 15 L mammalian cell culture bioreactor was characterized with respect to kLa under varying process conditions. The resulting dynamic kLa description combined with functions for the calculation of oxygen concentrations under prevailing process conditions led to an easy-to-apply model, that allows real-time calculation of the oxygen uptake rate (OUR) throughout the bioprocess without off-gas analyzers. Subsequently, the established OUR soft-sensor was applied in a series of 13 CHO fed-batch cultivations. The OUR was found to be directly associated with the amount of viable biomass in the system, and deploying of cell volumes instead of cell counts led to higher correlations. A two-segment linear model predicted the viable biomass in the system sufficiently. The segmented model was necessary due to a metabolic transition in which the specific consumption of oxygen changed. The aspartate to glutamate ratio was identified as an indicator of this metabolic shift. The detection of such transitions is enabled by a combination of the presented dynamic OUR method with another state-of-the-art viable biomass soft-sensor. In conclusion, this hyphenated technique is a robust and powerful tool for advanced bioprocess monitoring and control based exclusively on bioreactor characteristics.
TL;DR: Results indicate that the combination of a pulse‐based scale‐down approach with mechanistic models is a very suitable method to test strain robustness and physiological constraints at the early stages of bioprocess development.
Abstract: BACKGROUND: The impact of concentration gradients in large industrial‐scale bioreactors on microbial physiology can be studied in scale‐down bioreactors. However, scale‐down systems pose several challenges in construction, operation and footprint. Therefore, it is challenging to implement them in emerging technologies for bioprocess development, such as in high throughput cultivation platforms. In this study, a mechanistic model of a two‐compartment scale‐down bioreactor is developed. Simulations from this model are then used as bases for a pulse‐based scale‐down bioreactor suitable for application in parallel cultivation systems. RESULTS: As an application, the pulse‐based system model was used to study the misincorporation of non‐canonical branched‐chain amino acids into recombinant pre‐proinsulin expressed in Escherichia coli, as a response to oscillations in glucose and dissolved oxygen concentrations. The results show significant accumulation of overflow metabolites, up to 18.3% loss in product yield and up to 10‐fold accumulation of the non‐canonical amino acids norvaline and norleucine in the product in the pulse‐based cultivation, compared with a reference cultivation. CONCLUSIONS: Results indicate that the combination of a pulse‐based scale‐down approach with mechanistic models is a very suitable method to test strain robustness and physiological constraints at the early stages of bioprocess development. © 2018 Society of Chemical Industry
TL;DR: Key metabolic enzymes and metabolites are identified that can be potentially monitored as the process progresses and/or increased in the cell either by nutrient feeding or genetic engineering and reinforces the centrality of redox balance to cellular health and success of the bioprocess.
Abstract: There is continual demand to maximize CHO cell culture productivity of a biotherapeutic while maintaining product quality. In this study, a comprehensive multi-omics analysis is performed to investigate the cellular response to the level of dosing of the amino acid cysteine (Cys) in the production of a monoclonal antibody (mAb). When Cys feed levels are insufficient, there is a significant decrease in protein titer. Multi-omics (metabolomics and proteomics, with support from RNAseq) is performed over the time course of the CHO bioprocess producing an IgG1 mAb in 5 L bioreactors. Pathway analysis reveals that insufficient levels of Cys in the feed lead to Cys depletion in the cell. This depletion negatively impacts antioxidant molecules, such as glutathione (GSH) and taurine, leading to oxidative stress with multiple deleterious cellular effects. In this paper, the resultant ER stress and subsequent apoptosis that affects cell viability and viable cell density has been considered. Key metabolic enzymes and metabolites are identified that can be potentially monitored as the process progresses and/or increased in the cell either by nutrient feeding or genetic engineering. This work reinforces the centrality of redox balance to cellular health and success of the bioprocess as well as the power of multi-omics to provide an in-depth understanding of the CHO cell biology during biopharmaceutical production.
31 Jul 2019
TL;DR: This review focuses primarily, but not exclusively, on Yarrowia lipolytica as a yeast cell factory, owing to its broad range of naturally metabolizable carbon sources, together with its popularity as a non-conventional yeast.
Abstract: Non-conventional yeasts are efficient cell factories for the synthesis of value-added compounds such as recombinant proteins, intracellular metabolites, and/or metabolic by-products. Most bioprocess, however, are still designed to use pure, ideal sugars, especially glucose. In the quest for the development of more sustainable processes amid concerns over the future availability of resources for the ever-growing global population, the utilization of organic wastes or industrial by-products as feedstocks to support cell growth is a crucial approach. Indeed, vast amounts of industrial and commercial waste simultaneously represent an environmental burden and an important reservoir for recyclable or reusable material. These alternative feedstocks can provide microbial cell factories with the required metabolic building blocks and energy to synthesize value-added compounds, further representing a potential means of reduction of process costs as well. This review highlights recent strategies in this regard, encompassing knowledge on catabolic pathways and metabolic engineering solutions developed to endow cells with the required metabolic capabilities, and the connection of these to the synthesis of value-added compounds. This review focuses primarily, but not exclusively, on Yarrowia lipolytica as a yeast cell factory, owing to its broad range of naturally metabolizable carbon sources, together with its popularity as a non-conventional yeast.
TL;DR: In this paper, the authors combine a commercially available microbioreactor system and a laboratory robot to develop a fully automated milliliter-scale microbial fed-batch cultivation, sample handling, and data storage.
Abstract: Advances in molecular biotechnology have resulted in the generation of numerous potential production strains. Because every strain can be screened under various process conditions, the number of potential cultivations is multiplied. Exploiting this potential without increasing the associated timelines requires a cultivation platform that offers increased throughput and flexibility to perform various bioprocess screening protocols. Currently, there is no commercially available fully automated cultivation platform that can operate multiple microbial fed-batch processes, including at-line sampling, deep freezer off-line sample storage, and complete data handling. To enable scalable high-throughput early-stage microbial bioprocess development, a commercially available microbioreactor system and a laboratory robot are combined to develop a fully automated cultivation platform. By making numerous modifications, as well as supplementation with custom-built hardware and software, fully automated milliliter-scale microbial fed-batch cultivation, sample handling, and data storage are realized. The initial results of cultivations with two different expression systems and three different process conditions are compared using 5 L scale benchmark cultivations, which provide identical rankings of expression systems and process conditions. Thus, fully automated high-throughput cultivation, including automated centralized data storage to significantly accelerate the identification of the optimal expression systems and process conditions, offers the potential for automated early-stage bioprocess development.
TL;DR: Improvements act to improve the biotechnological engineering cycle with tools for building, testing and evaluating cell factories and bioprocesses by increasing throughput, parallelization and automation.