Toward biotherapeutic product real-time quality monitoring

Metabolic heat based specific growth rate estimators: Does the choice of estimation model influence the state of bioprocesses?

Accurate and reliable estimation of specific growth rate (μ) in real-time is pivotal for reliable process monitoring of a bioprocess and subsequent implementation of advanced control strategies. Gibbs free energy dissipation is imminent for any biological system, and the metabolic heat flow measurements (calorimetry) formed the basis for estimating μ. However, the rationale behind selecting a suitable μ estimator model based on calorimetric perspective remains unexplored. The present investigation addresses the notion behind the selection of an appropriate estimator for μ and the assessment of the estimator models was illustrated using different types of energy metabolism, namely, high exothermic and low exothermic processes. The results indicated that the μ values from the instantaneous heat flow estimator significantly deviated (10-fold higher) from the offline values for highly exothermic process. Notably, the cumulative heat-based estimator accurately estimated μ values on both types of energy metabolism with performance metrics <0.005 h-1.

In-line fiber optical sensor for detection of IgG aggregates in affinity chromatography

Therapeutic monoclonal antibodies (mAbs) are critical for treatment of a wide range of diseases. Immunoglobulin G (IgG) is the most predominant form of mAb but is prone to aggregation during production. Detection and removal of IgG aggregates are time-consuming and laborious. Chromatography is central for purification of biopharmaceuticals in general and essential in the production of mAbs. Protein purification systems are usually equipped with detectors for monitoring pH, UV absorbance, and conductivity, to facilitate optimization and control of the purification process. However, specific in-line detection of the target products and contaminating species, such as aggregates, is currently not possible using convectional techniques. Here we show a novel fiber optical in-line sensor, based on localized surface plasmon resonance (LSPR), for specific detection of IgG and IgG aggregates during affinity chromatography. A flow cell with a Protein A sensor chip was connected to the outlet of the affinity column connected to three different chromatography systems operating at lab scale to pilot scale. Samples containing various IgG concentrations and aggregate contents were analyzed in-line during purification on a Protein A column using both pH gradient and isocratic elution. Because of avidity effects, IgG aggregates showed slower dissociation kinetics than monomers after binding to the sensor chips. Possibilities to detect aggregate concentrations below 1 % and difference in aggregate content smaller than 0.3 % between samples were demonstrated. In-line detection of aggregates can circumvent time-consuming off-line analysis and facilitate automation and process intensification.

An integrated methodology for quality assessment of therapeutic antibodies with potential long circulation half-life in harvested cell culture fluid using FcRn immobilized hydrophilic magnetic graphene

Designing modified therapeutic antibodies with enhanced FcRn-binding affinity holds promise in the extension of circulation half-lives and potential refinement of pharmacokinetics. During the development of these new-generation therapeutic antibodies, FcRn binding affinity of IgGs is emphasized and monitored as a critical quality attribute (CQA), alongside other critical assessments including titer and aggregation level. However, the traditional workflow for assessing the overall quality of expressed IgGs in harvested cell culture fluid (HCCF) is blamed to be cumbersome and time-consuming. This study presents an integrated methodology for the rapid quality assessment of IgGs in HCCF by selectively extracting IgGs with favorable high FcRn affinity for subsequent analysis using size exclusion chromatography (SEC). The approach utilizes innovative adsorbents known as FcRn immobilized hydrophilic magnetic graphene (MG@PDA@PAMAM-FcRn) in a magnetic solid-phase extraction (MSPE) process. To simulate the in vivo binding dynamics, MSPE binding and dissociation was performed at pH 6.0 and 7.4, respectively. The composite have demonstrated enhanced extraction efficiency and impurity removal ability in comparison to commercially available magnetic beads. The SEC monomer peak area value provides the output of this method, the ranking of which enabled the facile identification of superior HCCF samples with high overall quality of IgG. Optimization of MSPE parameters was performed, and the method was validated for specificity, precision, sensitivity, and accuracy. The proposed method exhibited an analytical time of 0.6 h, which is 7-22 times shortened in comparison to the conventional workflow.

Giving the cells what they need when they need it: Biosensor-based feeding control

"Giving the cells exactly what they need, when they need it" is the core idea behind the proposed bioprocess control strategy: operating bioprocess based on the physiological behavior of the microbial population rather than exclusive monitoring of environmental parameters. We are envisioning to achieve this through the use of genetically encoded biosensors combined with online flow cytometry (FCM) to obtain a time-dependent "physiological fingerprint" of the population. We developed a biosensor based on the glnA promoter (glnAp) and applied it for monitoring the nitrogen-related nutritional state of Escherichia coli. The functionality of the biosensor was demonstrated through multiple cultivation runs performed at various scales-from microplate to 20 L bioreactor. We also developed a fully automated bioreactor-FCM interface for on-line monitoring of the microbial population. Finally, we validated the proposed strategy by performing a fed-batch experiment where the biosensor signal is used as the actuator for a nitrogen feeding feedback control. This new generation of process control, -based on the specific needs of the cells, -opens the possibility of improving process development on a short timescale and therewith, the robustness and performance of fermentation processes.

Recent Trends in AI-Based Intelligent Sensing

In recent years, intelligent sensing has gained significant attention because of its autonomous decision-making ability to solve complex problems. Today, smart sensors complement and enhance the capabilities of human beings and have been widely embraced in numerous application areas. Artificial intelligence (AI) has made astounding growth in domains of natural language processing, machine learning (ML), and computer vision. The methods based on AI enable a computer to learn and monitor activities by sensing the source of information in a real-time environment. The combination of these two technologies provides a promising solution in intelligent sensing. This survey provides a comprehensive summary of recent research on AI-based algorithms for intelligent sensing. This work also presents a comparative analysis of algorithms, models, influential parameters, available datasets, applications and projects in the area of intelligent sensing. Furthermore, we present a taxonomy of AI models along with the cutting edge approaches. Finally, we highlight challenges and open issues, followed by the future research directions pertaining to this exciting and fast-moving field.

Capillary and microchip electrophoresis method development for amino acid monitoring during biopharmaceutical cultivation

The increased use of biopharmaceuticals calls for improved means of bioprocess monitoring. In this work, capillary electrophoresis (CE) and microchip electrophoresis (MCE) methods were developed and applied for the analysis of amino acids (AAs) in cell culture supernatant. In samples from different days of a Chinese hamster ovary cell cultivation process, all 19 proteinogenic AAs containing primary amine groups could be detected using CE, and 17 out of 19 AAs using MCE. The relative concentration changes in different samples agreed well with those measured by high-performance liquid chromatography (HPLC). Compared to the more commonly employed HPLC analysis, the CE and MCE methods resulted in faster analysis, while significantly lowering both the sample and reagent consumption, and the cost per analysis. This article is protected by copyright. All rights reserved.

Biopharmaceutical Manufacturing: Historical Perspectives and Future Directions

This review describes key milestones related to the production of biopharmaceuticals-therapies manufactured using recombinant DNA technology. The market for biopharmaceuticals has grown significantly since the first biopharmaceutical approval in 1982, and the scientific maturity of the technologies used in their manufacturing processes has grown concomitantly. Early processes relied on established unit operations, with research focused on process scale-up and improved culture productivity. In the early 2000s, changes in regulatory frameworks and the introduction of Quality by Design emphasized the importance of developing manufacturing processes to deliver a desired product quality profile. As a result, companies adopted platform processes and focused on understanding the dynamic interplay between product quality and processing conditions. The consistent and reproducible manufacturing processes of today's biopharmaceutical industry have set high standards for product efficacy, quality, and safety, and as the industry continues to evolve in the coming decade, intensified processing capabilities for an expanded range of therapeutic modalities will likely become routine. Expected final online publication date for the Annual Review of Chemical and Biomolecular Engineering, Volume 13 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Recent advances and trends in sample preparation and chemical modification for glycan analysis

Growing significance of glycosylation in protein functions has accelerated the development of methodologies for detection, identification, and characterization of protein glycosylation. In the past decade, glycobiology research has been advanced by innovative techniques with further progression in the post-genome era. Although significant technical progress has been made in terms of analytical throughput, comprehensiveness, and sensitivity, most methods for glycosylation analysis still require laborious and time-consuming sample preparation tasks. Additionally, sample preparation methods that are focused on specific glycan(s) require an in-depth understanding of various issues in glycobiology. In this review, modern sample preparation and chemical modification methods for the structural and quantitative glycan analyses together with the challenges and advantages of recent sample preparation methods are summarized. The techniques presented herein can facilitate the exploration of biomarkers, understanding of unknown glycan functions, and development of biopharmaceuticals.

Paving the way towards continuous biosensing by implementing affinity-based nanoswitches on state-dependent readout platforms

Combining affinity-based nanoswitches with state-dependent readout platforms allows for continuous biosensing and acquisition of real-time information about biochemical processes occurring in the environment of interest.

Taking the pulse of bioprocesses: at-line and in-line monitoring of mammalian cell cultures

Real-time and near real-time monitoring of cell culture processes are critical to the evolving process analytical technology (PAT) paradigm for upstream bioprocessing. The responses measured from these analytical instruments can enable rapid feedback to perturbations that can otherwise lead to batch failures. Historically, real-time monitoring of bioreactor processes has been relegated to parameters such as pH, dissolved oxygen, and temperature. Other analytical results, such as cell growth and metabolites, are provided through manual daily sampling. In order to reduce sample error and increase throughput, real-time and near real-time instruments have been developed. Here we discuss recent advances in these technologies. This article aims to focus on other developing at-line and in-line technologies that enable monitoring of bioreactor processes, including dielectric spectroscopy, NIR, off-gas spectrometry, integrated at-line HPLC, and nanofluidic devices for monitoring cell growth and health, metabolites, titer, and product quality.

Knowing more from less: miniaturization of ligand-binding assays and electrophoresis as new paradigms for at-line monitoring and control of mammalian cell bioprocesses

Monitoring technologies for Process Analytical Technology (PAT) in mammalian cell cultures are often focusing on the same hand full parameters although a deeper knowledge and control of a larger panel of culture components would highly benefit process optimization, control and robustness. This short review highlights key advances in microfluidic affinity assays and microchip capillary electrophoresis (MCE). Aiming at the miniaturization and integration of PAT, these can detect at-line a variety of metabolites, proteins and Critical Quality Attributes (CQA's) in a bioprocess. Furthermore, discrete analytical components, which can potentially support the translation of increasingly mature microfluidic technologies towards this novel application, are also presented as a comprehensive toolbox ranging from sample preparation to signal acquisition.

Two-Dimensional Mass Spectrometry Analysis of IgG1 Antibodies

Two-dimensional mass spectrometry (2DMS) is a new, and theoretically ideal, data-independent analysis tool, which allows the characterization of a complex mixture and was used in the bottom-up analysis of IgG1 for the identification of post-translational modifications. The new peak picking algorithm allows the distinction between chimeric peaks in proteomics. In this application, the processing of 2DMS data correlates fragments to their corresponding precursors, with fragments from precursors which are <0.1 m/z at m/z 840 easily resolved, without the need for quadrupole or chromatographic separation.

Bioprocess Control: Current Progress and Future Perspectives

Typical bioprocess comprises of different unit operations wherein a near optimal environment is required for cells to grow, divide, and synthesize the desired product. However, bioprocess control caters to unique challenges that arise due to non-linearity, variability, and complexity of biotech processes. This article presents a review of modern control strategies employed in bioprocessing. Conventional control strategies (open loop, closed loop) along with modern control schemes such as fuzzy logic, model predictive control, adaptive control and neural network-based control are illustrated, and their effectiveness is highlighted. Furthermore, it is elucidated that bioprocess control is more than just automation, and includes aspects such as system architecture, software applications, hardware, and interfaces, all of which are optimized and compiled as per demand. This needs to be accomplished while keeping process requirement, production cost, market value of product, regulatory constraints, and data acquisition requirements in our purview. This article aims to offer an overview of the current best practices in bioprocess control, monitoring, and automation.

High-throughput N-glycan screening method for therapeutic antibodies using a microchip-based DNA analyzer: a promising methodology for monitoring monoclonal antibody N-glycosylation

N-Glycosylation of therapeutic antibodies is a critical quality attribute (CQA), and the micro-heterogeneity affects the biological and physicochemical properties of antibodies. Therefore, the profiling of N-glycans on antibodies is essential for controlling the manufacturing process and ensuring the efficacy and safety of the therapeutic antibodies. To monitor N-glycosylation in recombinant proteins, a high-throughput (HTP) methodology for glycan analysis is required to handle bulk samples in various stages of the manufacturing process. In this study, we focused on the HTP methodology for N-glycan analysis using a commercial microchip electrophoresis-based DNA analyzer and demonstrated the feasibility of the workflow consisting of sample preparation and electrophoretic separation. Even if there is a demand to analyze up to 96 samples, the present workflow can be completed in a day without expensive instruments and reagent kits for sample preparation, and it will be a promising methodology for cost-effective and facile HTP N-glycosylation analysis while optimizing the manufacturing process and development for therapeutic antibodies.

Protein L—More Than Just an Affinity Ligand

In the past 30 years, highly specific drugs, known as antibodies, have conquered the biopharmaceutical market. In addition to monoclonal antibodies (mAbs), antibody fragments are successfully applied. However, recombinant production faces challenges. Process analytical tools for monitoring and controlling production processes are scarce and time-intensive. In the downstream process (DSP), affinity ligands are established as the primary and most important step, while the application of other methods is challenging. The use of these affinity ligands as monitoring tools would enable a platform technology to monitor process steps in the USP and DSP. In this review, we highlight the current applications of affinity ligands (proteins A, G, and L) and discuss further applications as process analytical tools.

Calibration for quantitative Fc-glycosylation analysis of therapeutic IgG1-type monoclonal antibodies by using glycopeptide standards

Fc-glycosylation has crucial impact on the efficacy and safety of IgG-type therapeutic monoclonal antibodies (mAbs). In order to enhance the performance of MS-based bottom-up quantitation strategy, a library of glycopeptide standards containing 26 common IgG1-type Fc-glycoforms has been constructed via modified two-dimensional hydrophilic interaction liquid chromatography (HILIC) purification. Taking advantage of the acquired glycopeptide standards, calibrated quantitation strategy for Fc-glycosylation analysis of mAbs was established and evaluated on the basis of three LC-MS-based methods, including HILIC-MRM (multiple reaction monitoring), HILIC-SIM (selected ion monitor) and RPLC-SIM. Molar concentrations of eleven individual Fc-glycoforms (0.03 ± 0.001-13.77 ± 0.64 nmol mg^-1) as well as degree of fucosylation (75.44-97.04%), galactosylation (3.39-49.47%) and mannosylation (1.12-21.22%) in six IgG1-type mAbs were achieved. In addition, Fc-glycosylation site occupancy was also determined from 98.05% to 99.83%. Compared with traditional MS-based quantitation via peak area normalization, the quantitation accuracy and precision of the calibrated strategy had been remarkably improved, especially when combining with HILIC separation. In addition, the transferability of calibrated quantitation as assessed by using MRM-based method had also been significantly enhanced on different instruments from different laboratories. This calibrated quantitation strategy using glycopeptide standards as calibrators will be useful for Fc-glycosylation analysis of IgG1-type mAbs with multiple glycosylation sites.

Dielectric Spectroscopy to Improve the Production of rAAV Used in Gene Therapy

The insect cell-baculovirus expression vector system is an established method for large scale recombinant adeno-associated virus (rAAV) production, largely due to its scalability and high volumetric productivities. During rAAV production it is critical to monitor process parameters such as Spodoptera frugiperda (Sf9) cell concentration, infection timing, and cell harvest viabilities since they can have a significant influence on rAAV productivity and product quality. Herein we developed the use of dielectric spectroscopy as a process analytical technology (PAT) tool used to continuously monitor the production of rAAV in 2 L stirred tank bioreactors, achieving enhanced control over the production process. This study resulted in improved manufacturing robustness through continuous monitoring of cell culture parameters, eliminating sampling needs, increasing the accuracy of infection timing, and reliably estimating the time of harvest. To increase the accuracy of baculovirus infection timing, the cell growth/permittivity model was coupled to a feedback loop with real-time monitoring. This system was able to predict baculovirus infection timing up to 24 h in advance for greatly improved accuracy of infection and ensuring consistent high rAAV productivities. Furthermore, predictive models were developed based on the dielectric measurements of the culture. These multiple linear regression-based models resulted in correlation coefficients (Q2) of 0.89 for viable cell concentration, 0.97 for viability, and 0.92 for cell diameter. Finally, models were developed to predict rAAV titer providing the capability to distinguish in real time between high and low titer production batches.

Real-Time Nanoplasmonic Sensor for IgG Monitoring in Bioproduction

Real-time monitoring of product titers during process development and production of biotherapeutics facilitate implementation of quality-by-design principles and enable rapid bioprocess decision and optimization of the production process. Conventional analytical methods are generally performed offline/at-line and, therefore, are not capable of generating real-time data. In this study, a novel fiber optical nanoplasmonic sensor technology was explored for rapid IgG titer measurements. The sensor combines localized surface plasmon resonance transduction and robust single use Protein A-modified sensor chips, housed in a flexible flow cell, for specific IgG detection. The sensor requires small sample volumes (1–150 µL) and shows a reproducibility and sensitivity comparable to Protein G high performance liquid chromatography-ultraviolet (HPLC-UV). The dynamic range of the sensor system can be tuned by varying the sample volume, which enables quantification of IgG samples ranging from 0.0015 to 10 mg/mL, without need for sample dilution. The sensor shows limited interference from the sample matrix and negligible unspecific protein binding. IgG titers can be rapidly determined in samples from filtered unpurified Chinese hamster ovary (CHO) cell cultures and show good correlation with enzyme-linked immunosorbent assay (ELISA).

Process Analytical Technologies and Data Analytics for the Manufacture of Monoclonal Antibodies

Process analytical technology (PAT) for the manufacture of monoclonal antibodies (mAbs) is defined by an integrated set of advanced and automated methods that analyze the compositions and biophysical properties of cell culture fluids, cell-free product streams, and biotherapeutic molecules that are ultimately formulated into concentrated products. In-line or near-line probes and systems are remarkably well developed, although challenges remain in the determination of the absence of viral loads, detecting microbial or mycoplasma contamination, and applying data-driven deep learning to process monitoring and soft sensors. In this review, we address the current status of PAT for both batch and continuous processing steps and discuss its potential impact on facilitating the continuous manufacture of biotherapeutics.

Digital Twins in Pharmaceutical and Biopharmaceutical Manufacturing: A Literature Review

The development and application of emerging technologies of Industry 4.0 enable the realization of digital twins (DT), which facilitates the transformation of the manufacturing sector to a more agile and intelligent one. DTs are virtual constructs of physical systems that mirror the behavior and dynamics of such physical systems. A fully developed DT consists of physical components, virtual components, and information communications between the two. Integrated DTs are being applied in various processes and product industries. Although the pharmaceutical industry has evolved recently to adopt Quality-by-Design (QbD) initiatives and is undergoing a paradigm shift of digitalization to embrace Industry 4.0, there has not been a full DT application in pharmaceutical manufacturing. Therefore, there is a critical need to examine the progress of the pharmaceutical industry towards implementing DT solutions. The aim of this narrative literature review is to give an overview of the current status of DT development and its application in pharmaceutical and biopharmaceutical manufacturing. State-of-the-art Process Analytical Technology (PAT) developments, process modeling approaches, and data integration studies are reviewed. Challenges and opportunities for future research in this field are also discussed.

Towards a widespread adoption of metabolic modeling tools in biopharmaceutical industry: a process systems biology engineering perspective

In biotechnology, the emergence of high-throughput technologies challenges the interpretation of large datasets. One way to identify meaningful outcomes impacting process and product attributes from large datasets is using systems biology tools such as metabolic models. However, these tools are still not fully exploited for this purpose in industrial context due to gaps in our knowledge and technical limitations. In this paper, key aspects restraining the routine implementation of these tools are highlighted in three research fields: monitoring, network science and hybrid modeling. Advances in these fields could expand the current state of systems biology applications in biopharmaceutical industry to address existing challenges in bioprocess development and improvement.

Single-Use Printed Biosensor for L-Lactate and Its Application in Bioprocess Monitoring

There is a profound need in bioprocess manufacturing for low-cost single-use sensors that allow timely monitoring of critical product and production attributes. One such opportunity is screen-printed enzyme-based electrochemical sensors, which have the potential to enable low-cost online and/or off-line monitoring of specific parameters in bioprocesses. In this study, such a single-use electrochemical biosensor for lactate monitoring is designed and evaluated. Several aspects of its fabrication and use are addressed, including enzyme immobilization, stability, shelf-life and reproducibility. Applicability of the biosensor to off-line monitoring of bioprocesses was shown by testing in two common industrial bioprocesses in which lactate is a critical quality attribute (Corynebacterium fermentation and mammalian Chinese hamster ovary (CHO) cell cultivation). The specific response to lactate of the screen-printed biosensor was characterized by amperometric measurements. The usability of the sensor at typical industrial culture conditions was favorably evaluated and benchmarked with commonly used standard methods (HPLC and enzymatic kits). The single-use biosensor allowed fast and accurate detection of lactate in prediluted culture media used in industrial practice. The design and fabrication of the biosensor could most likely be adapted to several other critical bioprocess analytes using other specific enzymes. This makes this single-use screen-printed biosensor concept a potentially interesting and versatile tool for further applications in bioprocess monitoring.

Mass spectrometry-based methods in characterization of the higher order structure of protein therapeutics

Higher order structure of protein therapeutics is an important quality attribute, which dictates both potency and safety. While modern experimental biophysics offers an impressive arsenal of state-of-the-art tools that can be used for the characterization of higher order structure, many of them are poorly suited for the characterization of biopharmaceutical products. As a result, these analyses were traditionally carried out using classical techniques that provide relatively low information content. Over the past decade, mass spectrometry made a dramatic debut in this field, enabling the characterization of higher order structure of biopharmaceuticals as complex as monoclonal antibodies at a level of detail that was previously unattainable. At present, mass spectrometry is an integral part of the analytical toolbox across the industry, which is critical not only for quality control efforts, but also for discovery and development.

When Is an In Silico Representation a Digital Twin? A Biopharmaceutical Industry Approach to the Digital Twin Concept

Digital twins (DTs) are expected to render process development and life-cycle management much more cost-effective and time-efficient. A DT definition, a brief retrospect on their history and expectations for their deployment in today's business environment, and a detailed financial assessment of their attractive economic benefits are provided in this chapter. The argument that restrictive guidelines set forth by regulatory agencies would hinder the adoption of DTs in the (bio)pharmaceutical industry is revisited, concluding that those companies who collaborate with the agencies to further their technical capabilities will gain significant competitive advantage. The analyzed process development examples show high methodological readiness levels but low systematic adoption of technology. Given the technical feasibilities, financial opportunities, and regulatory encouragement, concerns regarding intellectual property and data sharing, though required to be taken into account, will at best delay an industry-wide adoption of DTs. In conclusion, it is expected that a strategic investment in DTs now will gain an advantage over competition that will be difficult to overcome by late adopters.

Advancements in SPR biosensing technology: An overview of recent trends in smart layers design, multiplexing concepts, continuous monitoring and in vivo sensing

Inspired by the rapid progress and existing limitations in surface plasmon resonance (SPR) biosensing technology, we have summarized the recent trends in the fields of both chip-SPR and fiber optic (FO)-SPR biosensors during the past five years, primarily regarding smart layers design, multiplexing, continuous monitoring and in vivo sensing. Versatile surface chemistries, biomaterials and nanomaterials have been utilized thus far to generate smart layers on SPR platforms and as such achieve oriented immobilization of bioreceptors, improved fouling resistance and sensitivity enhancement, collectively aiming to improve the biosensing performance. Furthermore, often driven by the desires for time- and cost-effective quantification of multiple targets in a single measurement, efforts have been made to implement multiplex bioassays on SPR platforms. While this aspect largely remains difficult to attain, numerous alternative strategies arose for obtaining parallel analysis of multiple analytes in one single device. Additionally, one of the upcoming challenges in this field will be to succeed in using SPR platforms for continuous measurements and in vivo sensing, and as such match up other biosensing platforms where these goals have been already conquered. Overall, this review will give insight into multiple possibilities that have become available over the years for boosting the performance of SPR biosensors. However, because combining them all into one optimal sensor is practically not feasible, the final application needs to be considered while designing an SPR biosensor, as this will determine the requirements of the bioassay and will thus help in selecting the essential elements from the recent progress made in SPR sensing.