Improving bioprocess efficiency is important to reduce the current costs of biologics on the market, bring them faster to the market, and to improve the environmental footprint. The process ...intensification efforts were historically focused on the main stage, while intensification of pre‐stages has started to gain attention only in the past decade. Performing bioprocess pre‐stages in the perfusion mode is one of the most efficient options to achieve higher viable cell densities over traditional batch methods. While the perfusion‐mode operation allows to reach higher viable cell densities, it also consumes large amount of medium, making it cost‐intensive. The change of perfusion rate during a process (perfusion profile) determines how much medium is consumed, thereby running a process in optimal conditions is key to reduce medium consumption. However, the selection of the perfusion profile is often made empirically, without full understanding of bioprocess dynamics. This fact is hindering potential process improvements and means for cost reduction. In this study, we propose a process modeling approach to identify the optimal perfusion profile during bioprocess pre‐stages. The developed process model was used internally during process development. We could reduce perfused medium volume by 25%–45% (project‐dependent), while keeping the difference in the final cell within 5%–10% compared to the original settings. Additionally, the model helps to reduce the experimental workload by 30%–70% and to predict an optimal perfusion profile when process conditions need to be changed (e.g., higher seeding density, change of operating mode from batch to perfusion, etc.). This study demonstrates the potential of process modeling as a powerful tool for optimizing bioprocess pre‐stages and thereby guiding process development, improving overall bioprocess efficiency, and reducing operational costs, while strongly reducing the need for wet‐lab experiments.
This study developed a modeling approach to identify the optimal perfusion profile for bioprocess pre‐stages. In addition, this method was used to explore different operation modes and to quantify the influence of operational parameters on transfer cell density and viability. Accordingly, the proposed approach represents a powerful tool not only for increasing bioprocess understanding, but also for reducing experimental efforts and operational costs, thereby accelerating development timelines.
Mechanistic models require a significant investment of time and resources, but their application to multiple stages of fermentation process development and operation can make this investment highly ...valuable. This Opinion article discusses how an established fermentation model may be adapted for application to different stages of fermentation process development: planning, process design, monitoring, and control. Although a longer development time is required for such modeling methods in comparison to purely data-based model techniques, the wide range of applications makes them a highly valuable tool for fermentation research and development. In addition, in a research environment, where collaboration is important, developing mechanistic models provides a platform for knowledge sharing and consolidation of existing process understanding.
The Quality by Design (QbD) and process analytical technology (PAT) initiatives have encouraged the development of more advanced monitoring and control methods.
Modeling is one method of ensuring that there is an understanding of how the critical process parameters affect the critical quality attributes, therefore ensuring the quality of the product.
Mechanistic modeling is proposed as a very flexible modeling tool that may be applied at multiple stages of the process development pathway without significant adaptation of the model.
Automated flow cytometry (FC) has been initially considered for bioprocess monitoring and optimization. More recently, new physical and software interfaces have been made available, facilitating the ...access to this technology for labs and industries. It also comes with new capabilities, such as being able to act on the cultivation conditions based on population data. This approach, known as reactive FC, extended the range of applications of automated FC to bioprocess control and the stabilization of cocultures, but also to the broad field of synthetic and systems biology for the characterization of gene circuits. However, several issues must be addressed before automated and reactive FC can be considered standard and modular technologies.
•The accessibility to automated flow cytometry equipment has recently been increased through the open science initiative.•Automated and reactive flow cytometry can be used for controlling gene expression cell populations.•Automated and reactive flow cytometry can be used for controlling cocultures.•Further standardization of automated flow cytometry data is needed.
Extracellular vesicles (EVs) derived from human mesenchymal stromal cells (hMSC-EVs) have been studied in over 200 preclinical applications and dozens of human clinical trials, underscoring the need ...for scalable production processes compatible with GMP environments. Most existing 2D and 3D Bioreactor hMSC-EV production processes require a cell expansion stage utilizing undefined components, followed by a wash and medium exchange to remove expansion medium impurities prior to an EV collection phase in a defined medium. Simplifying this 3D process to include cell expansion and EV collection in one medium requires chemically defined growth conditions, a fed-batch medium design, and an efficient process to maximize cell and EV yield, and final product quality. We have developed a chemically defined, scalable fed-batch bioreactor production medium to enable the streamlined and highly efficient production of hMSC-EVs. This study evaluates hMSC-EV production and EV quality across multiple donors and tissues in microcarrier spinner flask cultures using a traditional cell expansion, wash, collect process vs the single-step production process, including scale-up to a 3L stirred tank bioreactor.
MSC-EVs were produced from hMSCs (hBM and hUC RoosterVial, 1M) in either RoosterNourish-MSC-XF/RoosterReplenish/RoosterCollect-EV or the new highly productive, chemically defined (HiDef-EV) fed-batch system and collected EVs at set times. HiDef-EV cultures led to increased EV production on days 5, 7, 10 and 12 of culture, while maintaining healthy viable cell profiles. The fed-batch process for hMSC-EV production increased the EV collection window from healthy hMSCs resulting in 2-4x increase in hMSC-EV yield over traditional EV production processes. Elimination of the medium exchange and wash steps resulted in utilization of fewer raw materials, retention rather than disposal of EVs produced during cell growth, and significant reductions in total media used and total cost per billion EVs. Additionally, EV Quality Attributes including size, tetraspanin expression, CD-73 activity, RNA, and lipid content are preserved in the HiDef-EV system. Scale up in 3L Eppendorf bioreactor showed comparable cell growth, EV yields and EV quality between traditional and HiDef-EV process. This highly productive chemically defined EV medium is a simplified, time and cost saving solution for the large-scale production of higher purity hMSC-EVs necessary for extensive clinical investigations.
p‐Coumaric acid (pCA) can be produced via bioprocessing and is a promising chemical precursor to making organic thin film transistors. However, the required tyrosine ammonia lyase (TAL) enzyme ...generally has a low specific activity and suffers from competitive product inhibition. Here we characterized the purified TAL variants from Flavobacterium johnsoniae and Herpetosiphon aurantiacus in terms of their susceptibility to product inhibition and their activity and stability across pH and temperature via initial rate experiments. FjTAL was found to be more active than previously described and to have a relatively weak affinity for pCA, but modeling revealed that product inhibition would still be problematic at industrially relevant product concentrations, due to the low solubility of the substrate tyrosine. The activity of both variants increased with temperature when tested up to 45°C, but HaTAL1 was more stable at elevated temperature. FjTAL is a promising biocatalyst for pCA production, but enzyme or bioprocess engineering are required to stabilize FjTAL and reduce product inhibition.
Graphical and Lay Summary
Hydrogen is regarded as clean future fuel and biological route of hydrogen production is amongst the most sustainable and pollution free alternatives. Biohydrogen production from organic waste via ...fermentation technology is one of the most promising approaches. Though, pilot scale frequent production of this fuel is also on trial stage and its distribution is still odd around the globe due to concern such as unavailability of substrate, incomplete conversion and poor yield. Because of these notable issues, mass scale trials results are different from lab scale trials. Therefore, for applications as an energy source, evaluation of mass-scale H2 production and analysis of different key influential factors of the process technology are mandatory for diverse applications. Thus, the goal of the present review is to explore and evaluate the important and most influential bioprocess parameters for pilot-scale biohydrogen production using organic substrates through dark fermentation. Different process parameters and their influence on pilot scale have been explored with the existing shortcomings and the possible solutions. The future possibilities in reference to pilot-scale biohydrogen production on a global scale have also been discussed, which can be helpful in implementing biohydrogen as a green energy source for a sustainable and clean environment.
The significance of biowaste for pilot-scale biohydrogen production in developing a sustainable environment. Display omitted
•Studies on pilot-scale dark fermentative hydrogen production are reviewed.•Biohydrogen production from organic waste on a pilot-scale is discussed.•Existing pilot-scale bioprocess parameters, impacts, and challenges are analyzed.•Waste-to-energy based technoeconomic and environmental challenges are discussed.•Biohydrogen, from the perspective of green energy for a clean environment, is discussed.
Raman spectroscopy is widely used in monitoring and controlling cell cultivations for biopharmaceutical drug manufacturing. However, its implementation for culture monitoring in the cell line ...development stage has received little attention. Therefore, the impact of clonal differences, such as productivity and growth, on the prediction accuracy and transferability of Raman calibration models is not yet well described. Raman OPLS models were developed for predicting titer, glucose and lactate using eleven CHO clones from a single cell line. These clones exhibited diverse productivity and growth rates. The calibration models were evaluated for clone‐related biases using clone‐wise linear regression analysis on cross validated predictions. The results revealed that clonal differences did not affect the prediction of glucose and lactate, but titer models showed a significant clone‐related bias, which remained even after applying variable selection methods. The bias was associated with clonal productivity and lead to increased prediction errors when titer models were transferred to cultivations with productivity levels outside the range of their training data. The findings demonstrate the feasibility of Raman‐based monitoring of glucose and lactate in cell line development with high accuracy. However, accurate titer prediction requires careful consideration of clonal characteristics during model development.
Graphical and Lay Summary
Raman spectroscopy is a widely used technology for monitoring and controlling cell cultivations for biopharmaceutical drug manufacturing. Multiple CHO clones were cultivated with varying clonal characteristics. The corresponding Raman calibration models were developed and finally evaluated for any clone‐related biases. This work serves as a potential basis for Raman‐based cell culture monitoring in cell line development.
•Online and offline data combined leads to informative representation of the bioprocess design space.•Method proposed to condense online data is superior to averaging.•Proposed method maintains ...identity of each individual parameter post-condensation.•Proposed method captures the behaviour of the time series better.•Impact-of-error analysis highlights the importance of continuous monitoring.
Efficient control of a bioprocess relies on the ability to systematically capture and represent the process dynamics of critical process parameters. Multivariate monitoring techniques in biopharmaceuticals has resulted in the generation of large amounts of data comprising real-time measurements of critical quality and performance attributes. If exploited efficiently, these can provide an opportunity for developing better control action. For this, it is important to have a comprehensive view of the critical process parameter landscape, which can only be achieved by integrating both online and offline data into a single data matrix that can then be subjected to standard data analysis protocols. However, owing to the difference in the number of readings available for variables recorded online and offline, there is a need for new methods to achieve condensation capability. This paper introduces a novel methodology for condensing online data into an offline data matrix, which performed better when compared to traditionally employed averaging and helped increase the number of variables available for representing the design space of the process. The method was also used to understand how error propagates through online data, so as to identify an interval of tolerance in online monitoring of bioprocesses.
Bioprocesses are scaled up for the production of large product quantities. With larger fermenter volumes, mixing becomes increasingly inefficient and environmental gradients get more prominent than ...in smaller scales. Environmental gradients have an impact on the microorganism's metabolism, which makes the prediction of large-scale performance difficult and can lead to scale-up failure. A promising approach for improved understanding and estimation of dynamics of microbial populations in large-scale bioprocesses is the analysis of microbial lifelines. The lifeline of a microbe in a bioprocess is the experience of environmental gradients from a cell's perspective, which can be described as a time series of position, environment and intracellular condition. Currently, lifelines are predominantly determined using models with computational fluid dynamics, but new technical developments in flow-following sensor particles and microfluidic single-cell cultivation open the door to a more interdisciplinary concept. We critically review the current concepts and challenges in lifeline determination and application of lifeline analysis, as well as strategies for the integration of these techniques into bioprocess development. Lifelines can contribute to a successful scale-up by guiding scale-down experiments and identifying strain engineering targets or bioreactor optimisations.
•A microbe's view on large-scale reactors gives insights for bioprocess development.•Computational fluid dynamics allow to predict the lifelines of cells.•Environmental lifelines can be mimicked for microbes in microfluidic devices.•Flow-following particles have the potential to measure lifelines in bioreactor.•Microbial lifelines lay the foundation for new strategies in bioprocess development.
In this work, a bioprocess for the fermentation of A. succinogenes for the production of succinic acid from glycerol was developed, employing a continuous bioreactor with recycle. Moreover, a new ...bioprocess model was constructed, based on an existing double substrate limitation model, which was validated with experimental results for a range of operating parameters. The model was used to successfully predict the dynamics of the continuous fermentation process and was subsequently employed in optimisation studies to compute the optimal conditions, dilution rate, reflux rate and feed glycerol concentration, that maximise the productivity of bio-succinic acid. In addition, a Pareto front for optimal volumetric productivity and glycerol conversion combinations was computed. Maximum volumetric productivity of 0.518 g/L/h, was achieved at the optimal computed conditions, which were experimentally validated. This is the highest bio-succinic acid productivity reported so far, for such a continuous bioprocess.
