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.     

Estimating environmental impacts of early-stage bioprocesses

The use of bioprocesses in industrial production promises resource- and energy-efficient processes starting from renewable, nonfossil feedstocks. Thus, the environmental benefits must be demonstrated, ideally in the early development phase with standardized methods such as life cycle assessment (LCA). Herein we discuss selected LCA studies of early-stage bioprocesses, highlighting their potential and contribution to estimating environmental impacts and decision support in bioprocess development. However, LCAs are rarely performed among bioprocess engineers due to challenges such as data availability and process uncertainties. To address this issue, recommendations are provided for conducting LCAs of early-stage bioprocesses. Opportunities are identified to facilitate future applicability, for example, by establishing dedicated bioprocess databases that could enable the use of LCAs as standard tools for bioprocess engineers.     

Mass flux balance-based model and metabolic pathway engineering analysis for serine alkaline protease synthesis by Bacillus licheniformis

A mass flux balance-based stoichiometric model of Bacillus licheniformis for the serine alkaline protease (SAP) fermentation process has been established. The model considers 147 reaction fluxes, and there are 105 metabolites that are assumed to be in pseudo-steady state. Metabolic flux distributions were obtained from the solution of the model based on the minimum SAP accumulation rate assumption in B. licheniformis in combination with the off-line extracellular analyses of the metabolites that were the sole carbon source citrate, dry cell, organic acids, amino acids, and SAP; variations in the intracellular fluxes were demonstrated for the three periods of the batch bioprocess. The flux distribution maps showed that the cells completed the TCA cycle and utilized the gluconeogenesis pathway, pentose phosphate pathway, and anaplerotic reactions throughout the fermentation; however, the glycolysis pathway was inactive in all the periods of the fermentation. The flux values toward SAP increased throughout the bioprocess and slightly decreased in the last period; however, SAP selectivity values were almost the same in Periods II and III and higher than Period I. The diversions in the pathways and certain metabolic reactions depending on the bioprocess periods are also presented and the results indicated that the intracellular amino acid fluxes played an important role in the SAP fermentation process.     

我国工业生物过程工程研究进展

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

A new microfluidic concept for parallel operated milliliter-scale stirred tank bioreactors

Parallel miniaturized stirred tank bioreactors are an efficient tool for "high-throughput bioprocess design." As most industrial bioprocesses are pH-controlled and/or are operated in a fed-batch mode, an exact scale-down of these reactions with continuous dosing of fluids into the miniaturized bioreactors is highly desirable. Here, we present the development, characterization, and application of a novel concept for a highly integrated microfluidic device for a bioreaction block with 48 parallel milliliter-scale stirred tank reactors (V = 12 mL). The device consists of an autoclavable fluidic section to dispense up to three liquids individually per reactor. The fluidic section contains 144 membrane pumps, which are magnetically driven by a clamped-on actuator section. The micropumps are designed to dose 1.6 μL per pump lift. Each micropump enables a continuous addition of liquid with a flow rate of up to 3 mL h(-1) . Viscous liquids up to a viscosity of 8.2 mPa s (corresponds to a 60% v/v glycerine solution) can be pumped without changes in the flow rates. Thus, nearly all feeding solutions can be delivered, which are commonly used in bioprocesses. The functionality of the first prototype of this microfluidic device was demonstrated by double-sided pH-controlled cultivations of Saccharomyces cerevisiae based on signals of fluorimetric sensors embedded at the bottom of the bioreactors. Furthermore, fed-batch cultivations with constant and exponential feeding profiles were successfully performed. Thus, the presented novel microfluidic device will be a useful tool for parallel and, thus, efficient optimization of controlled fed-batch bioprocesses in small-scale stirred tank bioreactors. This can help to reduce bioprocess development times drastically.     

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.     

Temporally segmented modelling: a route to improved bioprocess monitoring using near infrared spectroscopy?

Near infrared spectroscopy (NIRS) was used to monitor an industrial bioprocess for the production of the antibiotic, tylosin, using a segmented modelling approach. Models were built over the entire time course of the fermentation from 0 to 150 h, and also in two distinct phases or segments of the bioprocess from 50 to 100 h (synthetic phase) and from 100 to 150 h (stationary phase). All models were validated externally and the performance of the full range and segmented models compared. The standard error of prediction (SEP) of the segmented models was less in both 50–100 h and 100–150 h and the correlation highest in the 50–100 h range. This would suggest that data segmentation is potentially a useful method of accommodating the impact of the pronounced matrix changes which occur in some bioprocesses in NIRS models for key analytes. While there are many reports on bioprocess monitoring using NIRS, there have been no previous studies on the use of segmented NIR models within a bioprocess as a means of accommodating matrix change.     

Protein engineering of Acidovorax facilis 72W nitrilase for bioprocess development

Hydroxycarboxylic acid monomers can be used to prepare industrially important polymers. Enzymatic production of such hydroxycarboxylic acids is often preferred to chemical production since the reactions are run at ambient temperature, do not require strongly acidic or basic reaction conditions, and produce the desired product with high selectivity at high conversion. However, native enzymes often do not perform desired reactions with the efficiency required for commercial applications. Protein engineering was used to significantly increase the specific activity of nitrilase from Acidovorax facilis 72W for the conversion of 3-hydroxyvaleronitrile to 3-hydroxyvaleric acid. Overexpression of engineered nitrilase enzymes in Escherichia coli, combined with immobilization of whole cells in alginate beads that can be recycled many times has facilitated the development of a commercially viable bioprocess for production of 3-hydroxyvaleric acid.     

Dynamic process conditions in bioprocess development

In this review, we summarise recent studies that purposefully employed dynamic conditions, such as shifts, pulses, ramps and oscillations, for fast physiological strain characterisation and bioprocess development. We show the broad applicability of dynamic conditions and the various objectives that can thereby be investigated in a short time. Dynamic processes reveal information about the analysed system faster than traditional strategies, like continuous cultivations, as process parameters can directly be linked to platform and product parameters. Furthermore, we demonstrate that dynamic operations can result in increased productivity and high product quality, making this strategy a valuable tool for bioprocess development. With this review, we would like to encourage bioprocess engineers to an increased use of dynamic conditions in bioprocess development.     

Designing a blueprint for next-generation stem cell bioprocessing development

The creation of a blueprint for stem cell bioprocess development that it is easily readable and shareable among those involved in the construction of the bioprocess is a necessary step toward full-fledged bioprocess integration. The blueprint provides the culturing tools and methodologies, designed to highlight knowledge gaps within biological sciences and bioengineering. This review highlights a blueprint for stem cell bioprocessing development using a landscape architecture approach that can aid the development of culture technologies and tools that satisfy the demands for stem cell-derived products for use in clinical and industrial applications. This work is intended to provide insights to cell biologists, geneticists, bioengineers, and clinicians seeking knowledge outside of their field of expertise and fosters a leap from a reductionist approach to one, that is, globally integrated in stem cell bioprocessing.     

A logic-reasoning based system to harness bioprocess experimental data and knowledge for design

Bioprocess design requires substantial resources during the experimental investigation of the options for each bioprocess step. This is both time-consuming and expensive. The amount of data available has increased exponentially since the expansion of new biological drug development. Data are heterogeneous, sometimes inconsistent and incomplete, making them difficult to be systematically utilised for analysis for any new bioprocess design. In this paper, we report a novel computational method that harnesses the bioprocess experimental data to assist design decision making, and perhaps identify further needed experiments. First, we develop a new data representation structure to capture the experimental data systematically. Then the ontology for modelling the relationship of data properties is created. A computational system has been developed to search relevant data, or to predict required process conditions, or to suggest a new set of experiments for process development. A prototype for harnessing centrifugation experimental data has been built, and is then used to illustrate the method and demonstrate the type of results that can be obtained. Evaluations show that such a system has significant potential to mine the relevant experimental data to assist new drug bioprocess development, which should reduce process development time and cost.     

Flow injection analysis and in-line biosensors for bioprocess control: a comparison.

Miniaturization will unify the different approaches chosen for the application of biosensors in bioprocess control. The most versatile system, which in our opinion is flow injection analysis will be the method of choice for the introduction of biosensors in bioprocess control. A lot of experience will be gained for the future development of miniaturized total chemical analysis systems.     

Apoptosis: A mammalian cell bioprocessing perspective

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

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

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

Bio-based production of the platform chemical 1,5-diaminopentane

In the rising era of bio-economy, the five carbon compound 1,5-diaminopentane receives increasing interest as platform chemical, especially as innovative building block for bio-based polymers. The vital interest in bio-based supply of 1,5-diaminopentane has strongly stimulated research on the development of engineered producer strains. Based on the state-of-art knowledge on the pathways and reactions linked to microbial 1,5-diaminopentane metabolism, the review covers novel systems metabolic engineering approaches towards hyper-producing cell factories of Corynebacterium glutamicum or Escherichia coli. This is integrated into the whole value chain from renewable feedstocks via 1,5-diaminopentane to innovative biopolymers involving bioprocess engineering considerations for economic supply.     

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%.     

Machine learning in bioprocess development: from promise to practice

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

Accelerating patient access to novel biologics using stable pool‐derived product for non‐clinical studies and single clone‐derived product for clinical studies

Cell cloning and subsequent process development activities are on the critical path directly impacting the timeline for advancement of next generation therapies to patients with unmet medical needs. The use of stable cell pools for early stage material generation and process development activities is an enabling technology to reduce timelines. To successfully use stable pools during development, it is important that bioprocess performance and requisite product quality attributes be comparable to those observed from clonally derived cell lines. To better understand the relationship between pool and clone derived cell lines, we compared data across recent first in human (FIH) programs at Amgen including both mAb and Fc‐fusion modalities. We compared expression and phenotypic stability, bioprocess performance, and product quality attributes between material derived from stable pools and clonally derived cells. Overall, our results indicated the feasibility of matching bioprocess performance and product quality attributes between stable pools and subsequently derived clones. These findings support the use of stable pools to accelerate the advancement of novel biologics to the clinic. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 33:1476–1482, 2017     

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.     

Hybrid modeling in bioprocess dynamics: Structural variabilities,implementation strategies,and practical challenges

Hybrid modeling, with an appropriate blend of the mechanistic and data-driven framework, is increasingly being adopted in bioprocess modeling, model-based experimental design (digital-twin), identification of critical process parameters, and optimization. However, the development of a hybrid model from experimental data is an inherently complex workflow, involving designed experiments, selection of the data-driven process, identification of model parameters, assessment fitness, and generalization capability. Depending on the complexity of the process system and purpose, each piece of these modules can flexibly be incorporated into the puzzle. However, this extra flexibility can be a cause of concern to trace an “optimal” model structure. In this paper, the development of hybrid models in a common bioprocess system, selection of data-driven components and their mapping to states, choice of parameter identification techniques, and model quality assurance are revisited. The challenges associated with hybrid-model development, and corrective actions have also been reviewed. The review also suggests the lack of data, and code sharing in communal repositories can be a hurdle in the exploration, and expansion of those tools in a bioprocess system.