A quantitative approach for understanding small-scale human mesenchymal stem cell culture – implications for large-scale bioprocess development

Human mesenchymal stem cell (hMSC) therapies have the potential to revolutionise the healthcare industry and replicate the success of the therapeutic protein industry; however, for this to be achieved there is a need to apply key bioprocessing engineering principles and adopt a quantitative approach for large-scale reproducible hMSC bioprocess development. Here we provide a quantitative analysis of the changes in concentration of glucose, lactate and ammonium with time during hMSC monolayer culture over 4 passages, under 100% and 20% dissolved oxgen (dO₂), where either a 100%, 50% or 0% growth medium exchange was performed after 72h in culture. Yield coefficients, specific growth rates (h^-1) and doubling times (h) were calculated for all cases. The 100% dO₂ flasks outperformed the 20% dO₂ flasks with respect to cumulative cell number, with the latter consuming more glucose and producing more lactate and ammonium. Furthermore, the 100% and 50% medium exchange conditions resulted in similar cumulative cell numbers, whilst the 0% conditions were significantly lower. Cell immunophenotype and multipotency were not affected by the experimental culture conditions. This study demonstrates the importance of determining optimal culture conditions for hMSC expansion and highlights a potential cost savings from only making a 50% medium exchange, which may prove significant for large-scale bioprocessing.     

Universal label‐free in‐process quantification of influenza virus‐like particles

Virus‐like particles (VLPs) are becoming established as vaccines, in particular for influenza pandemics, increasing the interest in the development of VLPs manufacturing bioprocess. However, for complex VLPs, the analytical tools used for quantification are not yet able to keep up with the bioprocess progress. Currently, quantification for Influenza relies on traditional methods: hemagglutination assay or Single Radial Immunodiffusion. These analytical technologies are time‐consuming, cumbersome, and not supportive of efficient downstream process development and monitoring. Hereby we report a label‐free tool that uses Biolayer interferometry (BLI) technology applied on an Octet platform to quantify Influenza VLPs at all stages of bioprocess. Human (α2,6‐linked sialic acid) and avian (α2,3‐linked sialic acid) biotinylated receptors associated with streptavidin biosensors were used, to quantify hemagglutinin content in several mono‐ and multivalent Influenza VLPs. The applied method was able to quantify hemagglutinin from crude samples up to final bioprocessing VLP product. BLI technology confirmed its value as a high throughput analytical tool with high sensitivity and improved detection limits compared to traditional methods. This simple and fast method allowed for real‐time results, which are crucial for in‐line monitoring of downstream processing, improving process development, control and optimization.     

Bioprocessing automation in cell therapy manufacturing: Outcomes of special interest group automation workshop

Phacilitate held a Special Interest Group workshop event in Edinburgh, UK, in May 2017. The event brought together leading stakeholders in the cell therapy bioprocessing field to identify present and future challenges and propose potential solutions to automation in cell therapy bioprocessing. Here, we review and summarize discussions from the event. Deep biological understanding of a product, its mechanism of action and indication pathogenesis underpin many factors relating to bioprocessing and automation. To fully exploit the opportunities of bioprocess automation, therapeutics developers must closely consider whether an automation strategy is applicable, how to design an ‘automatable’ bioprocess and how to implement process modifications with minimal disruption. Major decisions around bioprocess automation strategy should involve all relevant stakeholders; communication between technical and business strategy decision-makers is of particular importance. Developers should leverage automation to implement in-process testing, in turn applicable to process optimization, quality assurance (QA)/ quality control (QC), batch failure control, adaptive manufacturing and regulatory demands, but a lack of precedent and technical opportunities can complicate such efforts. Sparse standardization across product characterization, hardware components and software platforms is perceived to complicate efforts to implement automation. The use of advanced algorithmic approaches such as machine learning may have application to bioprocess and supply chain optimization. Automation can substantially de-risk the wider supply chain, including tracking and traceability, cryopreservation and thawing and logistics. The regulatory implications of automation are currently unclear because few hardware options exist and novel solutions require case-by-case validation, but automation can present attractive regulatory incentives.     

Evaluating metabolic stress and plasmid stability in plasmid DNA production by Escherichia coli

In the context of recombinant DNA technology, the development of feasible and high-yielding plasmid DNA production processes has regained attention as more evidence for its efficacy as vectors for gene therapy and DNA vaccination arise. When producing plasmid DNA in Escherichia coli, a number of biological restraints, triggered by plasmid maintenance and replication as well as culture conditions are responsible for limiting final biomass and product yields. This termed "metabolic burden" can also cause detrimental effects on plasmid stability and quality, since the cell machinery is no longer capable of maintaining an active metabolism towards plasmid synthesis and the stress responses elicited by plasmid maintenance can also cause increased plasmid instability. The optimization of plasmid DNA production bioprocesses is still hindered by the lack of information on the host metabolic responses as well as information on plasmid instability. Therefore, systematic and on-line approaches are required not only to characterise this "metabolic burden" and plasmid stability but also for the design of appropriate metabolic engineering and culture strategies. The monitoring tools described to date rapidly evolve from laborious, off-line and at-line monitoring to online monitoring, at a time-scale that enables researchers to solve these bioprocessing problems as they occur. This review highlights major E. coli biological alterations caused by plasmid maintenance and replication, possible causes for plasmid instability and discusses the ability of currently employed bioprocess monitoring techniques to provide information in order to circumvent metabolic burden and plasmid instability, pointing out the possible evolution of these methods towards online bioprocess monitoring.     

Cellulosome-based, Clostridium-derived multi-functional enzyme complexes for advanced biotechnology tool development: Advances and applications

The cellulosome is one of nature's most elegant and elaborate nanomachines and a key biological and biotechnological macromolecule that can be used as a multi-functional protein complex tool. Each protein module in the cellulosome system is potentially useful in an advanced biotechnology application. The high-affinity interactions between the cohesin and dockerin domains can be used in protein-based biosensors to improve both sensitivity and selectivity. The scaffolding protein includes a carbohydrate-binding module (CBM) that attaches strongly to cellulose substrates and facilitates the purification of proteins fused with the dockerin module through a one-step CBM purification method. Although the surface layer homology (SLH) domain of CbpA is not present in other strains, replacement of the cell surface anchoring domain allows a foreign protein to be displayed on the surface of other strains. The development of a hydrolysis enzyme complex is a useful strategy for consolidated bioprocessing (CBP), enabling microorganisms with biomass hydrolysis activity. Thus, the development of various configurations of multi-functional protein complexes for use as tools in whole-cell biocatalyst systems has drawn considerable attention as an attractive strategy for bioprocess applications. This review provides a detailed summary of the current achievements in Clostridium-derived multi-functional complex development and the impact of these complexes in various areas of biotechnology.     

Prospective inference of bioprocess cell viability through chemometric modeling of fluorescence multiway data

In this investigation, the fermentation step of a standard mammalian cell-based industrial bioprocess for the production of a therapeutic protein was studied, with particular emphasis on the evolution of cell viability. This parameter constitutes one of the critical variables for bioprocess monitoring since it can affect downstream operations and the quality of the final product. In addition, when the cells experiment an unpredictable drop in viability, the assessment of this variable through classic off-line methods may not provide information sufficiently in advance to take corrective actions. In this context, Process Analytical Technology (PAT) framework aims to develop novel strategies for more efficient monitoring of critical variables, in order to improve the bioprocess performance. Thus, in this work, a set of chemometric tools were integrated to establish a PAT strategy to monitor cell viability, based on fluorescence multiway data obtained from fermentation samples of a particular bioprocess, in two different scales of operation. The spectral information, together with data regarding process variables, was integrated through chemometric exploratory tools to characterize the bioprocess and stablish novel criteria for the monitoring of cell viability. These findings motivated the development of a multivariate classification model, aiming to obtain predictive tools for the monitoring of future lots of the same bioprocess. The model could be satisfactorily fitted, showing the non-error rate of prediction of 100%.     

Reproducible culture and differentiation of mouse embryonic stem cells using an automated microwell platform

The use of embryonic stem cells (ESCs) and their progeny in high throughput drug discovery and regenerative medicine will require production at scale of well characterized cells at an appropriate level of purity. The adoption of automated bioprocessing techniques offers the possibility to overcome the lack of consistency and high failure rates seen with current manual protocols. To build the case for increased use of automation this work addresses the key question: “can an automated system match the quality of a highly skilled and experienced person working manually?” To answer this we first describe an integrated automation platform designed for the ‘hands-free’ culture and differentiation of ESCs in microwell formats. Next we outline a framework for the systematic investigation and optimization of key bioprocess variables for the rapid establishment of validatable Standard Operating Procedures (SOPs). Finally the experimental comparison between manual and automated bioprocessing is exemplified by expansion of the murine Oct-4-GiP ESC line over eight sequential passages with their subsequent directed differentiation into neural precursors. Our results show that ESCs can be effectively maintained and differentiated in a highly reproducible manner by the automated system described. Statistical analysis of the results for cell growth over single and multiple passages shows up to a 3-fold improvement in the consistency of cell growth kinetics with automated passaging. The quality of the cells produced was evaluated using a panel of biological markers including cell growth rate and viability, nutrient and metabolite profiles, changes in gene expression and immunocytochemistry. Automated processing of the ESCs had no measurable negative effect on either their pluripotency or their ability to differentiate into the three embryonic germ layers. Equally important is that over a 6-month period of culture without antibiotics in the medium, we have not had any cases of culture contamination. This study thus confirms the benefits of adopting automated bioprocess routes to produce cells for therapy and for use in basic discovery research.     

Essential prerequisites for successful bioprocess development of biological CH4 production from CO2 and H2

The production and storage of energy from renewable resources steadily increases in importance. One opportunity is to utilize carbon dioxide (CO₂)-type hydrogenotrophic methanogens, which are an intriguing group of microorganisms from the domain Archaea, for conversion of hydrogen and CO₂ to methane (CH₄). This review summarizes the current state of the art of bioprocess development for biological CH₄ production (BMP) from pure cultures with pure gasses. The prerequisites for successful quantification of BMP by using closed batch, as well as fed-batch and chemostat culture cultivation, are presented. This review shows that BMP is currently a much underexplored field of bioprocess development, which mainly focuses on the application of continuously stirred tank reactors. However, some promising alternatives, such as membrane reactors have already been adapted for BMP. Moreover, industrial-based scale-up of BMP to pilot scale and larger has not been conducted. Most crucial parameters have been found to be those, which influence gas-limitation fundamentals, or parameters that contribute to the complex effects that arise during medium development for scale-up of BMP bioprocesses, highly stressing the importance of holistic BMP quantification by the application of well-defined physiological parameters. The much underexplored number of different genera, which is mainly limited to Methanothermobacter spp., offers the possibility of additional scientific and bioprocess development endeavors for the investigation of BMP. This indicates the large potential for future bioprocess development considering the possible application of bioprocessing technological aspects for renewable energy storage and power generation.     

Ranking bioprocess variables using global sensitivity analysis: a case study in centrifugation

The selection of appropriate operating conditions for bioprocessing is complex due to the large number of interacting stages and variables. Bioprocesses also operate under tight regulation and therefore tools to assist bioprocess design are of significant utility. Conventional approaches for the analysis of variable sensitivities are inadequate. We propose the use of global sensitivity analysis to determine the level of importance of each variable and their interactions. Once key variables have been determined, the designer may focus on the most significant subset. Two case studies are used to demonstrate the applicability of the approach. Each is based on centrifugation and determines the impact of flow-rate, feed viscosity, density difference and particle size, while performance is assessed by supernatant clarification. Significant differences in sensitivities were found between the two studies due to the different feed material properties. Variable sensitivities were found to be system-specific and provide insight for potential operating strategies.     

Hybrid semi-parametric mathematical systems: bridging the gap between systems biology and process engineering

Systems biology is an integrative science that aims at the global characterization of biological systems. Huge amounts of data regarding gene expression, proteins activity and metabolite concentrations are collected by designing systematic genetic or environmental perturbations. Then the challenge is to integrate such data in a global model in order to provide a global picture of the cell. The analysis of these data is largely dominated by nonparametric modelling tools. In contrast, classical bioprocess engineering has been primarily founded on first principles models, but it has systematically overlooked the details of the embedded biological system. The full complexity of biological systems is currently assumed by systems biology and this knowledge can now be taken by engineers to decide how to optimally design and operate their processes. This paper discusses possible methodologies for the integration of systems biology and bioprocess engineering with emphasis on applications involving animal cell cultures. At the mathematical systems level, the discussion is focused on hybrid semi-parametric systems as a way to bridge systems biology and bioprocess engineering.     

Current challenges and recent advances on the path towards continuous biomanufacturing

Continuous biopharmaceutical manufacturing is currently a field of intense research due to its potential to make the entire production process more optimal for the modern, ever-evolving biopharmaceutical market. Compared to traditional batch manufacturing, continuous bioprocessing is more efficient, adjustable, and sustainable and has reduced capital costs. However, despite its clear advantages, continuous bioprocessing is yet to be widely adopted in commercial manufacturing. This article provides an overview of the technological roadblocks for extensive adoptions and points out the recent advances that could help overcome them. In total, three key areas for improvement are identified: Quality by Design (QbD) implementation, integration of upstream and downstream technologies, and data and knowledge management. First, the challenges to QbD implementation are explored. Specifically, process control, process analytical technology (PAT), critical process parameter (CPP) identification, and mathematical models for bioprocess control and design are recognized as crucial for successful QbD realizations. Next, the difficulties of end-to-end process integration are examined, with a particular emphasis on downstream processing. Finally, the problem of data and knowledge management and its potential solutions are outlined where ontologies and data standards are pointed out as key drivers of progress.     

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.     

Continuous bioprocessing: The real thing this time?

The Annual bioProcessUK Conference has acted as the key networking event for bioprocess scientists and engineers in the UK for the past 10 years. The following article is a report from the sessions that focused on continuous bioprocessing during the 10^th Annual bioProcessUK Conference (London, December 2013). These sessions were organized by the ‘EPSRC Centre for Innovative Manufacturing in Emergent Macromolecular Therapies’ hosted at University College London. A plenary lecture and workshop provided a forum for participants to debate topical issues in roundtable discussions with industry and academic experts from institutions such as Genzyme, Janssen, Novo Nordisk, Pfizer, Merck, GE Healthcare and University College London. The aim of these particular sessions was to understand better the challenges and opportunities for continuous bioprocessing in the bioprocessing sector.     

Plasmid DNA fermentation strategies: influence on plasmid stability and cell physiology

In order to provide sufficient pharmaceutical-grade plasmid DNA material, it is essential to gain a comprehensive knowledge of the bioprocesses involved; so, the development of protocols and techniques that allow a fast monitoring of process performance is a valuable tool for bioprocess design. Regarding plasmid DNA production, the metabolic stress of the host strain as well as plasmid stability have been identified as two of the key parameters that greatly influence plasmid DNA yields. The present work describes the impact of batch and fed-batch fermentations using different C/N ratios and different feeding profiles on cell physiology and plasmid stability, investigating the potential of these two monitoring techniques as valuable tools for bioprocess development and design. The results obtained in batch fermentations showed that plasmid copy number values suffered a pronounced increase at the end of almost all fermentation conditions tested. Regarding fed-batch fermentations, the strategies with exponential feeding profiles, in contrast with those with constant feeding, showed higher biomass and plasmid yields, the maximum values obtained for these two parameters being 95.64 OD₆₀₀ and 344.3 mg plasmid DNA (pDNA)/L, respectively, when using an exponential feed rate of 0.2 h⁻¹. Despite the results obtained, cell physiology and plasmid stability monitoring revealed that, although higher pDNA overall yields were obtained, this fermentation exhibited lower plasmid stability and percentage of viable cells. In conclusion, this study allowed clarifying the bioprocess performance based on cell physiology and plasmid stability assessment, allowing improvement of the overall process and not only plasmid DNA yield and cell growth.     

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.     

Continuous bioprocessing: The real thing this time?: 10th Annual bioProcessUK Conference,December 3–4, 2013, London,UK

The Annual bioProcessUK Conference has acted as the key networking event for bioprocess scientists and engineers in the UK for the past 10 years. The following article is a report from the sessions that focused on continuous bioprocessing during the 10^th Annual bioProcessUK Conference (London, December 2013). These sessions were organized by the ‘EPSRC Centre for Innovative Manufacturing in Emergent Macromolecular Therapies’ hosted at University College London. A plenary lecture and workshop provided a forum for participants to debate topical issues in roundtable discussions with industry and academic experts from institutions such as Genzyme, Janssen, Novo Nordisk, Pfizer, Merck, GE Healthcare and University College London. The aim of these particular sessions was to understand better the challenges and opportunities for continuous bioprocessing in the bioprocessing sector.     

Biochemical control of xylan biosynthesis - which end is up?

Xylans are major components of land plant secondary cell walls and are required for normal plant growth and development. Secondary walls also account for the bulk of lignocellulosic biomass, a potential feedstock for large-scale production of biofuels. Glucuronoxylan and arabinoxylan affect the conversion of lignocellulosic biomass to fermentable sugar, a crucial and expensive step in biofuel production. Thus, knowledge of xylan biosynthesis may provide tools to modify secondary cell wall structure and thereby improve the bioprocessing characteristics of biomass. Recent studies have shown that glucuronoxylan structure and biosynthesis are far more complex than previously appreciated and the number of glycosyltransferases implicated in this process continues to increase. New hypotheses regarding the mechanisms of glucuronoxylan biosynthesis challenge some widely held views.     

Precipitation of filamentous bacteriophages for their selective recovery in primary purification

Filamentous bacteriophages and their derivatives are showing great promise as a whole new class of industrial agents, such as biologically based nano-materials and viral vectors. This raises challenges for their large-scale manufacture, principally due to the lack of bioprocessing knowledge. This article addresses what will be a potentially important option in the primary purification of the bacteriophages. Polyethylene glycol (PEG)-salt dual precipitants, calcium ions, spermidine, and isoelectric precipitation were first examined for their potential suitability for bacteriophage concentration under both pure and broth conditions. Successful precipitants were further studied on the basis of their selective purification ability from DNA and protein contaminants in a clarified broth system. Both PEG-based and isoelectric precipitations resulted in bacteriophage purity improvements, and PEG-based precipitations offered the highest selectivities. This work shows that precipitation of bacteriophages can be an effective primary purification step in a large-scale bioprocess.