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.     

Observability analysis of biochemical process models as a valuable tool for the development of mechanistic soft sensors

By enabling the estimation of difficult‐to‐measure target variables using available indirect measurements, mechanistic soft sensors have become important tools for various bioprocess monitoring and control scenarios. Despite promising higher process efficiencies and increased process understanding, widespread application of soft sensors has been stalled by uncertainty about the feasibility and reliability of their estimations given present process analytical constraints. Observability analysis can provide an indication of the possibility and reliability of soft sensor estimations by analyzing the structural properties of first‐principle (mechanistic) models. In addition, it can provide a criteria for selection of suitable measurement methods with respect to their information content; thereby leading to successful implementation of soft sensors in bioprocess development and manufacturing environments. We demonstrate the utility of observability analysis for two classes of upstream bioprocesses: the processes involving growth and ethanol formation by Saccharomyces cerevisiae and the process of penicillin production by Penicillium chrysogenum. Results obtained from laboratory‐scale cultivations in addition to in‐silico experiments enable a comparison of theoretical aspects of observability analysis and the real‐life performance of soft sensors. By taking the expected error of measurements provided to the soft sensor into account, an innovative scaling approach facilitates a higher degree of comparability of observability results among various measurement configurations and process conditions. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1703–1715, 2015     

Generic Raman‐based calibration models enabling real‐time monitoring of cell culture bioreactors

Raman‐based multivariate calibration models have been developed for real‐time in situ monitoring of multiple process parameters within cell culture bioreactors. Developed models are generic, in the sense that they are applicable to various products, media, and cell lines based on Chinese Hamster Ovarian (CHO) host cells, and are scalable to large pilot and manufacturing scales. Several batches using different CHO‐based cell lines and corresponding proprietary media and process conditions have been used to generate calibration datasets, and models have been validated using independent datasets from separate batch runs. All models have been validated to be generic and capable of predicting process parameters with acceptable accuracy. The developed models allow monitoring multiple key bioprocess metabolic variables, and hence can be utilized as an important enabling tool for Quality by Design approaches which are strongly supported by the U.S. Food and Drug Administration. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1004–1013, 2015     

Application of simplex‐based experimental optimization to challenging bioprocess development problems: Case studies in downstream processing

The identification of feasible operating conditions during the early stages of bioprocess development is implemented frequently through High Throughput (HT) studies. These typically employ techniques based on regression analysis, such as Design of Experiments. In this work, an alternative approach, based on a previously developed variant of the Simplex algorithm, is compared to the conventional regression‐based method for three experimental systems involving polishing chromatography and protein refolding. This Simplex algorithm variant was found to be more effective in identifying superior operating conditions, and in fact it reached the global optimum in most cases involving multiple optima. By contrast, the regression‐based method often failed to reach the global optimum, and in many cases reached poor operating conditions. The Simplex‐based method is further shown to be robust in dealing with noisy experimental data, and requires fewer experiments than regression‐based methods to reach favorable operating conditions. The Simplex‐variant also lends itself to the use of HT analytical methods, when they are available, which can assist in avoiding analytical bottlenecks. It is suggested that this Simplex‐variant is ideally suited to rapid optimization in early‐phase process development. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:404–419, 2016     

Rational bioprocess design for human pluripotent stem cell expansion and endoderm differentiation based on cellular dynamics

We present a predictive bioprocess design strategy employing cell- and molecular-level analysis of rate-limiting steps in human pluripotent stem cell (hPSC) expansion and differentiation, and apply it to produce definitive endoderm (DE) progenitors using a scalable directed-differentiation technology. We define a bioprocess optimization parameter (L; targeted cell Loss) and, with quantitative cell division tracking and fate monitoring, identify and overcome key suspension bioprocess bottlenecks. Adapting process operating conditions to pivotal parameters (single cell survival and growth rate) in a cell-line-specific manner enabled adherent-equivalent expansion of hPSCs in feeder- and matrix-free defined-medium suspension culture. Predominantly instructive differentiation mechanisms were found to underlie a subsequent 18-fold expansion, during directed differentiation, to high-purity DE competent for further commitment along pancreatic and hepatic lineages. This study demonstrates that iPSC expansion and differentiation conditions can be prospectively specified to guide the enhanced production of target cells in a scale-free directed differentiation system.     

Early‐stage sustainability assessment of biotechnological processes: A case study of citric acid production

Sustainability assessment using a life‐cycle approach is indispensable to contemporary bioprocess development. This assessment is particularly important for early‐stage bioprocess development. As early‐stage investigations of bioprocesses involve the evaluation of their ecological and socioeconomic effects, they can be adjusted more effectively and improved towards sustainability, thereby reducing environmental risk and production costs. Early‐stage sustainability assessment is an important precautionary practice and, despite limited data, a unique opportunity to determine the primary impacts of bioprocess development. To this end, a simple and robust method was applied based on the standardized life‐cycle sustainability assessment methodology and commercially available datasets. In our study, we elaborated on the yeast‐based citric acid production process with Yarrowia lipolytica assessing 11 different substrates in different process modes. The focus of our analysis comprised both cultivation and down‐stream processing. According to our results, the repeated batch raw glycerol based bioprocess alternative showed the best environmental performance. The second‐ and third‐best options were also glycerol‐based. The least sustainable processes were those using molasses, chemically produced ethanol, and soy bean oil. The aggregated results of environmental, economic, and social impacts display waste frying oil as the best‐ranked alternative. The bioprocess with sunflower oil in the batch mode ranked second. The least favorable alternatives were the chemically produced ethanol‐, soy oil‐, refined glycerol‐, and molasses‐based citric acid production processes. The scenario analysis demonstrated that the environmental impact of nutrients and wastewater treatment is negligible, but energy demand of cultivation and down‐stream processing dominated the production process. However, without energy demand the omission of neutralizers almost halves the total impact, and neglecting pasteurization also considerably decreases the environmental impact.     

Micro biochemical engineering to accelerate the design of industrial-scale downstream processes for biopharmaceutical proteins

The article examines how a small set of easily implemented micro biochemical engineering procedures combined with regime analysis and bioprocess models can be used to predict industrial scale performance of biopharmaceutical protein downstream processing. This approach has been worked on in many of our studies of individual operations over the last 10 years and allows preliminary evaluation to be conducted much earlier in the development pathway because of lower costs. It then permits the later large scale trials to be more highly focused. This means that the risk of delays during bioprocess development and of product launch are reduced. Here we draw the outcomes of this research together and illustrate its use in a set of typical operations; cell rupture, centrifugation, filtration, precipitation, expanded bed adsorption, chromatography and for common sources, E. coli, two yeasts and mammalian cells (GS-NSO). The general approach to establishing this method for other operations is summarized and new developments outlined. The technique is placed against the background of the scale-down methods that preceded it and complementary ones that are being examined in parallel. The article concludes with a discussion of the advantages and limitations of the micro biochemical engineering approach versus other methods.     

Fully integrated downstream process to enable next-generation manufacturing

Next-generation manufacturing (NGM) has evolved over the past decade to a point where large biopharmaceutical organizations are making large investments in the technology and considering implementation in clinical and commercial processes. There are many well-considered reasons to implement NGM. For the most part, organizations will not fund NGM unless the implementation benefits the funding organization by providing reduced costs, reduced time, or additional needed capabilities. Productivity improvements gained from continuous purification are shown in this work, which used a new system that fully integrates and automates several downstream unit operations of a biopharmaceutical process to provide flexibility and easy implementation of NGM. The equipment and automation needed to support NGM can be complicated and expensive. Biopharmaceutical Process Development considered two options as follows: (1) design its own NGM system or (2) buy a prebuilt system. PAK BioSolutions offers a turn-key automated and integrated system that can operate up to four continuous purification stages simultaneously, while maintaining a small footprint in the manufacturing plant. The system provides significant cost benefits (~10× lower) compared with the alternative—integration of many different pieces of equipment through a Distributed Control System that would require significant engineering time for design, automation, and integration. Integrated and Continuous Biomanufacturing can lead to significant reductions in facility size, reduced manufacturing costs, and enhanced product quality when compared with the traditional batch mode of operation. The system uses new automation strategies that robustly link unit operations. We present the optimized process fit, sterility and bioburden control strategy, and automation features (such as pH feedback control and in-line detergent addition), which enabled continuous operation of a 14-day end-to-end monoclonal antibody purification process at the clinical manufacturing scale.     

Rapid whole monoclonal antibody analysis by mass spectrometry: An Ultra scale‐down study of the effect of harvesting by centrifugation on the post‐translational modification profile

With the trend towards the generation and production of increasing numbers of complex biopharmaceutical (protein based) products, there is an increased need and requirement to characterize both the product and production process in terms of robustness and reproducibility. This is of particular importance for products from mammalian cell culture which have large molecular structures and more often than not complex post‐translational modifications (PTMs) that can impact the efficacy, stability and ultimately the safety of the final product. It is therefore vital to understand how the operating conditions of a bioprocess affect the distribution and make up of these PTMs to ensure a consistent quality and activity in the final product. Here we have characterized a typical bioprocess and determined (a) how the time of harvest from a mammalian cell culture and, (b) through the use of an ultra scale‐down mimic how the nature of the primary recovery stages, affect the distribution and make up of the PTMs observed on a recombinant IgG₄ monoclonal antibody. In particular we describe the use of rapid whole antibody analysis by mass spectrometry to analyze simultaneously the changes that occur to the cleavage of heavy chain C‐terminal lysine residues and the glycosylation pattern, as well as the presence of HL dimers. The time of harvest was found to have a large impact upon the range of glycosylation patterns observed, but not upon C‐terminal lysine cleavage. The culture age had a profound impact on the ratio of different glycan moieties found on antibody molecules. The proportion of short glycans increased (e.g., (G0F)₂ 20–35%), with an associated decrease in the proportion of long glycans with culture age (e.g., (G2F)₂ 7–4%, and G1F/G2F from 15.2% to 7.8%). Ultra scale‐down mimics showed that subsequent processing of these cultures did not change the post‐translational modifications investigated, but did increase the proportion of half antibodies present in the process stream. The combination of ultra scale‐down methodology and whole antibody analysis by mass spectrometry has demonstrated that the effects of processing on the detailed molecular structure of a monoclonal antibody can be rapidly determined early in the development process. In this study we have demonstrated this analysis to be applicable to critical process design decisions (e.g., time of harvest) in terms of achieving a desired molecular structure, but this approach could also be applied as a selection criterion as to the suitability of a platform process for the preparation of a new drug candidate. Also the methodology provides means for bioprocess engineers to predict at the discovery phase how a bioprocess will impact upon the quality of the final product. Biotechnol. Bioeng. 2010;107: 85–95. © 2010 Wiley Periodicals, Inc.     

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.     

Scale‐down of the inactivated polio vaccine production process

The anticipated increase in the demand for inactivated polio vaccines resulting from the success in the polio eradication program requires an increase in production capacity and cost price reduction of the current inactivated polio vaccine production processes. Improvement of existing production processes is necessary as the initial process development has been done decades ago. An up‐to‐date lab‐scale version encompassing the legacy inactivated polio vaccine production process was set‐up. This lab‐scale version should be representative of the large scale, meaning a scale‐down model, to allow experiments for process optimization that can be readily applied. Initially the separate unit operations were scaled‐down at setpoint. Subsequently, the unit operations were applied successively in a comparative manner to large‐scale manufacturing. This allows the assessment of the effects of changes in one unit operation to the consecutive units at small‐scale. Challenges in translating large‐scale operations to lab‐scale are discussed, and the concessions that needed to be made are described. The current scale‐down model for cell and virus culture (2.3‐L) presents a feasible model with its production scale counterpart (750‐L) when operated at setpoint. Also, the current scale‐down models for the DSP unit operations clarification, concentration, size exclusion chromatography, ion exchange chromatography, and inactivation are in agreement with the manufacturing scale. The small‐scale units can be used separately, as well as sequentially, to study variations and critical product quality attributes in the production process. Finally, it is shown that the scale‐down unit operations can be used consecutively to prepare trivalent vaccine at lab‐scale with comparable characteristics to the product produced at manufacturing scale. Biotechnol. Bioeng. 2013; 110: 1354–1365. © 2012 Wiley Periodicals, Inc.     

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%.     

工业生物过程智能控制原理和方法进展

工业生物过程是一个复杂的系统过程,对活体细胞代谢过程的认识是实现高效工业生物制造的基础。文中首先综述了工业发酵过程多尺度优化控制原理和实践,包括多尺度理论与装备、细胞宏观代谢在线检测传感技术以及生理代谢参数相关分析。在此基础上,对工业生物过程智能控制——感知细胞内生理代谢特性新型传感技术、大数据库建立和数据深度计算以及生物过程智能决策进行了综述和展望。     

Allogeneic cell therapy bioprocess economics and optimization: Single‐use cell expansion technologies

For allogeneic cell therapies to reach their therapeutic potential, challenges related to achieving scalable and robust manufacturing processes will need to be addressed. A particular challenge is producing lot‐sizes capable of meeting commercial demands of up to 10⁹ cells/dose for large patient numbers due to the current limitations of expansion technologies. This article describes the application of a decisional tool to identify the most cost‐effective expansion technologies for different scales of production as well as current gaps in the technology capabilities for allogeneic cell therapy manufacture. The tool integrates bioprocess economics with optimization to assess the economic competitiveness of planar and microcarrier‐based cell expansion technologies. Visualization methods were used to identify the production scales where planar technologies will cease to be cost‐effective and where microcarrier‐based bioreactors become the only option. The tool outputs also predict that for the industry to be sustainable for high demand scenarios, significant increases will likely be needed in the performance capabilities of microcarrier‐based systems. These data are presented using a technology S‐curve as well as windows of operation to identify the combination of cell productivities and scale of single‐use bioreactors required to meet future lot sizes. The modeling insights can be used to identify where future R&D investment should be focused to improve the performance of the most promising technologies so that they become a robust and scalable option that enables the cell therapy industry reach commercially relevant lot sizes. The tool outputs can facilitate decision‐making very early on in development and be used to predict, and better manage, the risk of process changes needed as products proceed through the development pathway. Biotechnol. Bioeng. 2014;111: 69–83. © 2013 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.     

A novel LED‐based 2D‐fluorescence spectroscopy system for in‐line bioprocess monitoring of Chinese hamster ovary cell cultivations—Part II

This study was performed in order to evaluate a new LED‐based 2D‐fluorescence spectrometer for in‐line bioprocess monitoring of Chinese hamster ovary (CHO) cell culture processes. The new spectrometer used selected excitation wavelengths of 280, 365, and 455 nm to collect spectral data from six 10‐L fed‐batch processes. The technique provides data on various fluorescent compounds from the cultivation medium as well as from cell metabolism. In addition, scattered light offers information about the cultivation status. Multivariate data analysis tools were applied to analyze the large data sets of the collected fluorescence spectra. First, principal component analysis was used to accomplish an overview of all spectral data from all six CHO cultivations. Partial least square regression models were developed to correlate 2D‐fluorescence spectral data with selected critical process variables as offline reference values. A separate independent fed‐batch process was used for model validation and prediction. An almost continuous in‐line bioprocess monitoring was realized because 2D‐fluorescence spectra were collected every 10 min during the whole cultivation. The new 2D‐fluorescence device demonstrates the significant potential for accurate prediction of the total cell count, viable cell count, and the cell viability. The results strongly indicated that the technique is particularly capable to distinguish between different cell statuses inside the bioreactor. In addition, spectral data provided information about the lactate metabolism shift and cellular respiration during the cultivation process. Overall, the 2D‐fluorescence device is a highly sensitive tool for process analytical technology applications in mammalian cell cultures.     

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.     

Physiological description of multivariate interdependencies between process parameters,morphology and physiology during fed‐batch penicillin production

Optimization of productivity and economics of industrial bioprocesses requires characterization of interdependencies between process parameters and process performance. In the case of penicillin production, as in other processes, process performance is often closely interlinked with the physiology and morphology of the organism used for production. This study presents a systematic approach to efficiently characterize the physiological effects of multivariate interdependencies between bioprocess design parameters (spore inoculum concentration, pO₂ control level and substrate feed rate), morphology, and physiology. Method development and application was performed using the industrial model process of penicillin production. Applying traditional, statistical bioprocess analysis, multivariate correlations of raw bioprocess design parameters (high spore inoculum concentration, low pO₂ control as well as reduced glucose feeding) and pellet morphology were identified. A major drawback of raw design parameter correlation models; however, is the lack of transferability across different process scales and regimes. In this context, morphological and physiological bioprocess modeling based on scalable physiological parameters is introduced. In this study, raw parameter effects on pellet morphology were efficiently summarized by the physiological parameter of the biomass yield per substrate. Finally, for the first time to our knowledge, the specific growth rate per spore was described as time‐independent determinant for switching from pellet to disperse growth during penicillin production and thus introduced as a novel, scalable key process parameter for pellet morphology and process performance. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:689–699, 2014     

High throughput chromatography and analytics can inform viral clearance capabilities during downstream process development for biologics

High throughput process development (HTPD) using liquid handling robotics and RoboColumns is an established methodology in downstream process development to screen chromatography resins and optimize process designs to meet target product profiles. However, HTPD is not yet widely available for use in viral clearance capability of the resin due to a variety of constraints. In the present study, a BSL-1-compatible, non-infectious MVM model, MVM-VLP, was tested for viral clearance assessment with various resin and membrane chromatography operations in a HTPD mode. To detect the MVM-VLP in the high throughput experiments, an electrochemiluminescence immunoassay (ECLIA) assay was developed with up to 5 logs of dynamic range. Storage time suitability of MVM-VLP solutions in various buffer matrices, in the presence or absence of a glycoprotein vaccine candidate, were assessed. Then, MVM-VLP and a test article monoclonal antibody (mAb) were used in a HTPD design that included commercially available ion exchange media chemistries, elucidating a wide variety of viral clearance ability at different operating conditions. The methodologies described herein have the potential to be a part of the process design stage in biologics manufacturing process development, which in turn can reduce risk associated with viral clearance validation studies.