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

The state of technological advancement to address challenges in the manufacture of rAAV gene therapies

Current processes for the production of recombinant adeno-associated virus (rAAV) are inadequate to meet the surging demand for rAAV-based gene therapies. This article reviews recent advances that hold the potential to address current limitations in rAAV manufacturing. A multidisciplinary perspective on technological progress in rAAV production is presented, underscoring the necessity to move beyond incremental refinements and adopt a holistic strategy to address existing challenges. Since several recent reviews have thoroughly covered advancements in upstream technology, this article provides only a concise overview of these developments before moving to pivotal areas of rAAV manufacturing not well covered in other reviews, including analytical technologies for rapid and high-throughput measurement of rAAV quality attributes, mathematical modeling for platform and process optimization, and downstream approaches to maximize efficiency and rAAV yield. Novel technologies that have the potential to address the current gaps in rAAV manufacturing are highlighted. Implementation challenges and future research directions are critically discussed.

Analysis of the Structure of 14 Therapeutic Antibodies Using Circular Dichroism Spectroscopy

Understanding the impact of the manufacturing environment on therapeutic monoclonal antibody (mAb) structures requires new process analytical technology. Here, we describe the creation of a new reference set for the circular dichroism (CD) spectra of mAbs. Data sets of the highest quality were collected by synchrotron radiation CD for 14 different mAbs in both native and acid-stressed states. Deconvolution of far-UV spectra for the mAb cohort identified two current reference sets (SP175 and SMP180) as assigning accurate secondary structures, irrespective of the analysis program employed. Scrutiny of spectra revealed significant variation in the far-UV and especially near-UV CD of the 14 mAbs. Two spectral features were found to be sensitive to changes in solution pH, i.e., the far-UV positive peak at 201-202 nm and the near-UV negative exciton couplet around 230-240 nm. The latter feature offers attractive possibilities for in-line CD-based monitoring of the mAb structure during manufacture.

Simple and fast one-step FRET assay of therapeutic mAb bevacizumab using anti-idiotype DNA aptamer for process analytical technology

We developed an aptamer-based fluorescence resonance energy transfer (FRET) assay capable of recognizing therapeutic monoclonal antibody bevacizumab and rapidly quantifying its concentration with just one mixing step. In this assay, two fluorescent dyes (fluorescein and tetramethylrhodamine) labeled aptamers bind to two Fab regions on bevacizumab, and FRET fluorescence is observed when both dyes come into close proximity. We optimized this assay in three different formats, catering to a wide range of analytical needs. When applied to hybridoma culture samples in practical settings, this assay exhibited a signal response that was concentration-dependent, falling within the range of 50-2000 μg/mL. The coefficients of determination (r2) ranged from 0.998 to 0.999, and bias and precision results were within ±24.0 % and 20.3 %, respectively. Additionally, during thermal and UV stress testing, this assay demonstrated the ability to detect denatured samples in a manner comparable to conventional Size Exclusion Chromatography. Notably, it offers the added advantage of detecting decreases in binding activity without changes in molecular weight. In contrast to many existing process analytical technology tools, this assay not only identifies bevacizumab but also directly measures the quality attributes related to mAb efficacy, such as the binding activity. As a result, this assay holds great potential as a valuable platform for providing highly reliable quality attribute information in real-time. We consider this will make a significant contribution to the worldwide distribution of high-quality therapeutic mAbs in various aspects of antibody manufacturing, including production monitoring, quality control, commercial lot release, and stability testing.

Advances and opportunities in process analytical technologies for viral vector manufacturing

Viral vectors are an emerging, exciting class of biologics whose application in vaccines, oncology, and gene therapy has grown exponentially in recent years. Following first regulatory approval, this class of therapeutics has been vigorously pursued to treat monogenic disorders including orphan diseases, entering hundreds of new products into pipelines. Viral vector manufacturing supporting clinical efforts has spurred the introduction of a broad swath of analytical techniques dedicated to assessing the diverse and evolving panel of Critical Quality Attributes (CQAs) of these products. Herein, we provide an overview of the current state of analytics enabling measurement of CQAs such as capsid and vector identities, product titer, transduction efficiency, impurity clearance etc. We highlight orthogonal methods and discuss the advantages and limitations of these techniques while evaluating their adaptation as process analytical technologies. Finally, we identify gaps and propose opportunities in enabling existing technologies for real-time monitoring from hardware, software, and data analysis viewpoints for technology development within viral vector biomanufacturing.

Raman and NIR spectroscopy-based real-time monitoring of the membrane filtration process of a recombinant protein for the diagnosis of SARS-CoV-2

This research shows the detailed comparison of Raman and near-infrared (NIR) spectroscopy as Process Analytical Technology tools for the real-time monitoring of a protein purification process. A comprehensive investigation of the application and model development of Raman and NIR spectroscopy was carried out for the real-time monitoring of a process-related impurity, imidazole, during the tangential flow filtration of Receptor-Binding Domain (RBD) of the SARS-CoV-2 Spike protein. The fast development of Raman and NIR spectroscopy-based calibration models was achieved using offline calibration data, resulting in low calibration and cross-validation errors. Raman model had an RMSEC of 1.53 mM, and an RMSECV of 1.78 mM, and the NIR model had an RMSEC of 1.87 mM and an RMSECV of 2.97 mM. Furthermore, Raman models had good robustness when applied in an inline measurement system, but on the contrary NIR spectroscopy was sensitive to the changes in the measurement environment. By utilizing the developed models, inline Raman and NIR spectroscopy were successfully applied for the real-time monitoring of a process-related impurity during the membrane filtration of a recombinant protein. The results enhance the importance of implementing real-time monitoring approaches for the broader field of diagnostic and therapeutic protein purification and underscore its potential to revolutionize the rapid development of biological products.

Development of generic metabolic Raman calibration models using solution titration in aqueous phase and data augmentation for in-line cell culture analysis

This study presents a novel approach for developing generic metabolic Raman calibration models for in-line cell culture analysis using glucose and lactate stock solution titration in an aqueous phase and data augmentation techniques. First, a successful set-up of the titration method was achieved by adding glucose or lactate solution at several different constant rates into the aqueous phase of a bench-top bioreactor. Subsequently, the in-line glucose and lactate concentration were calculated and interpolated based on the rate of glucose and lactate addition, enabling data augmentation and enhancing the robustness of the metabolic calibration model. Nine different combinations of spectra pretreatment, wavenumber range selection, and number of latent variables were evaluated and optimized using aqueous titration data as training set and a historical cell culture data set as validation and prediction set. Finally, Raman spectroscopy data collected from 11 historical cell culture batches (spanning four culture modes and scales ranging from 3 to 200 L) were utilized to predict the corresponding glucose and lactate values. The results demonstrated a high prediction accuracy, with an average root mean square errors of prediction of 0.65 g/L for glucose, and 0.48 g/L for lactate. This innovative method establishes a generic metabolic calibration model, and its applicability can be extended to other metabolites, reducing the cost of deploying real-time cell culture monitoring using Raman spectroscopy in bioprocesses.

Is it advantageous to use quality by design (QbD) to develop nanoparticle-based dosage forms for parenteral drug administration?

Parenteral administration is one of the most commonly used drug delivery routes for nanoparticle-based dosage forms, such as lipid-based and polymeric nanoparticles. For the treatment of various diseases, parenteral administration include intravenous, subcutaneous, and intramuscular route. In drug development phase, multiparameter strategy with a focus on drug physicochemical properties and the specificity of the administration route is required. Nanoparticle properties in terms of size and targeted delivery, among others, are able to surpass many drawbacks of conventional dosage forms, but these unique properties can be a bottleneck for approval by regulatory authorities. Quality by Design (QbD) approach has been widely utilized in development of parenteral nanoparticle-based dosage forms. It fosters knowledge of product and process quality by involving sound scientific data and risk assessment strategies. A full and comprehensive investigation into the state of implementation and applications of the QbD approach in these complex drug products can highlight the gaps and challenges. In this review, the analysis of critical attributes and Design of Experiment (DoE) approach in different nanoparticulate systems, together with the proper utilization of Process Analytical Technology (PAT) applications are described. The essential of QbD approach for the design and development of nanoparticle-based dosage forms for delivery via parenteral routes is discussed thoroughly.

Biosensing-based quality control monitoring of the higher-order structures of therapeutic antibody domains

Advanced biopharmaceutical manufacturing requires novel process analytical technologies for the rapid and sensitive assessment of the higher-order structures of therapeutic proteins. However, conventional physicochemical analyses of denatured proteins have limitations in terms of sensitivity, throughput, analytical resolution, and real-time monitoring capacity. Although probe-based sensing can overcome these limitations, typical non-specific probes lack analytical resolution and provide little to no information regarding which parts of the protein structure have been collapsed. To meet these analytical demands, we generated biosensing probes derived from artificial proteins that could specifically recognize the higher-order structural changes in antibodies at the protein domain level. Biopanning of phage-displayed protein libraries generated artificial proteins that bound to a denatured antibody domain, but not its natively folded structure, with nanomolar affinity. The protein probes not only recognized the higher-order structural changes in intact IgGs but also distinguished between the denatured antibody domains. These domain-specific probes were used to generate response contour plots to visualize the antibody denaturation caused by various process parameters, such as pH, temperature, and holding time for acid elution and virus inactivation. These protein probes can be combined with established analytical techniques, such as surface plasmon resonance for real-time monitoring or plate-based assays for high-throughput analysis, to aid in the development of new analytical technologies for the process optimization and monitoring of antibody manufacturing.

Quantitative and qualitative analysis of cell culture media powders for mammalian cells by Raman microscopy

Cell culture media are essential for large-scale recombinant protein production using mammalian cell cultures. The composition and quality of media significantly impact cell growth and product formation. Analyzing media poses challenges due to complex compositions and undisclosed exact compositions. Traditional methods like NMR and chromatography offer sensitivity but require time-consuming sample preparation and lack spatial information. Raman chemical mapping characterizes solids, but its use in cell culture media analysis is limited so far. We present a chemometric evaluation for Raman maps to qualify and quantify media components, evaluate powder homogeneity, and perform lot-to-lot comparisons. Three lots of a marketed cell culture media powder were measured with Raman mapping technique. Chemometrics techniques have outlined a strategy to extract information from complex data. First, a spectral library has been structured. In addition to the 23 spectra for presumed ingredients, we obtained another 9 pure components with Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS). Then the Spectral Angle Mapper-Orthogonal Projection (SAM-OP) algorithm revealed whether references actually occur in the mapped media powders. Finally, a quantification was provided by Classical Least Squares (CLS) modelling. Quantities of 18 significant amino acids mostly correlated with the reference method. The proposed method can be generally applied even for such complicated samples. Leveraging Raman mapping and innovative chemometric methods enhance recombinant protein production by improving the understanding of the spatial distribution and composition of cell culture media in mammalian cell cultivations.

Revolutionizing cancer treatment: comprehensive insights into immunotherapeutic strategies

Cancer, characterized by the uncontrolled proliferation of aberrant cells, underscores the imperative for innovative therapeutic approaches. Immunotherapy has emerged as a pivotal constituent in cancer treatment, offering improved prognostic outcomes for a substantial patient cohort. Noteworthy for its precision, immunotherapy encompasses strategies such as adoptive cell therapy and checkpoint inhibitors, orchestrating the immune system to recognize and selectively target malignant cells. Exploiting the specificity of the immune response renders immunotherapy efficacious, as it selectively targets the body's immune milieu. Diverse mechanisms underlie cancer immunotherapies, leading to distinct toxicity profiles compared to conventional treatments. A remarkable clinical stride in the anticancer resources is immunotherapy. Remarkably, certain recalcitrant cancers like skin malignancies exhibit resistance to radiation or chemotherapy, yet respond favorably to immunotherapeutic interventions. Notably, combination therapies involving chemotherapy and immunotherapy have exhibited synergistic effects, enhancing overall therapeutic efficacy. Understanding the pivotal role of immunotherapy elucidates its complementary value, bolstering the therapeutic landscape. In this review, we elucidate the taxonomy of cancer immunotherapy, encompassing adoptive cell therapy and checkpoint inhibitors, while scrutinizing their distinct adverse event profiles. Furthermore, we expound on the unprecedented potential of immunogenic vaccines to bolster the anticancer immune response. This comprehensive analysis underscores the significance of immunotherapy in modern oncology, unveiling novel prospects for tailored therapeutic regimens.

Intramodule pressure profiles and protein accumulation during tangential flow filtration

Tangential flow filtration (TFF) through a 30 kDa nominal molecular weight cut-off (MWCO) ultrafiltration membrane is widely employed to concentrate purified monoclonal antibodies (mAbs) to levels required for their formulation into injectable biologics. While TFF has been used to remove casein from milk for cheese production for over 35 years, and in pharmaceutical manufacture of biotherapeutic proteins for 20 years, the rapid decline in filtration rate (i.e., flux) at high protein concentrations is a limitation that still needs to be addressed. This is particularly important for mAbs, many of which are 140-160 kDa immunoglobulin G (IgG) type proteins recovered at concentrations of 200 mg/mL or higher. This work reports the direct measurement of local transmembrane pressure drops and off-line confocal imaging of protein accumulation in stagnant regions on the surface of a 30 kDa regenerated cellulose membrane in a flat-sheet configuration widely used in manufacture of biotherapeutic proteins. These first-of-a-kind measurements using 150 kDa bovine IgG show that while axial pressure decreases by 58 psi across a process membrane cassette, the decrease in transmembrane pressure drop is constant at about 1.2 psi/cm along the 20.7 cm length of the membrane. Confocal laser scanning microscopy of the membrane surface at the completion of runs where retentate protein concentration exceeds 200 mg/mL, shows a 50 μm thick protein layer is uniformly deposited. The localized measurements made possible by the modified membrane system confirm the role of protein deposition on limiting ultrafiltration rate and indicate possible targets for improving membrane performance.

Automated Online-Sampling Multidimensional Liquid Chromatography with Feedback-Control Capability as a Framework for Real-Time Monitoring of mAb Critical Quality Attributes in Multiple Bioreactors

Real-time monitoring of biopharmaceutical reactors is becoming increasingly important as the processes become more complex. During the continuous manufacturing of monoclonal antibodies (mAbs), the desired mAb product is continually created and collected over a 30 day process, where there can be changes in quality over that time. Liquid chromatography (LC) is the workhorse instrumentation capable of measuring mAb concentration as well as quality attributes such as aggregation, charge variants, oxidation, etc. However, traditional offline sampling is too infrequent to fully characterize bioprocesses, and the typical time from sample generation to data analysis and reporting can take weeks. To circumvent these limitations, an automated online sampling multidimensional workflow was developed to enable streamlined measurements of mAb concentration, aggregation, and charge variants. This analytical framework also facilitates automated data export for real-time analysis of up to six bioreactors, including feedback-controlling capability using readily available LC technology. This workflow increases the data points per bioreactor, improving the understanding of each experiment while also reducing the data turnaround time from weeks to hours. Examples of effective real-time analyses of mAb critical quality attributes are illustrated, showing substantial throughput improvements and accurate results while minimizing labor and manual intervention.

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.

Continuous multi-membrane chromatography of large viral particles

Continuous multi-column chromatography (CMCC) has been successfully implemented to address biopharmaceutical biomolecule instability, to improve process efficiency, and to reduce facility footprint and capital cost. This paper explores the implementation of a continuous multi-membrane chromatography (CMMC) process, using four membrane units, for a large viral particle in just few weeks. CMMC improves the efficiency of the chromatography step by enabling higher loads with smaller membranes for multiple cycles of column use and enables steady-state continuous bioprocessing. The separation performance of CMMC was compared to a conventional batch chromatographic capture step used at full manufacturing scale. The product step yield was 80% using CMMC versus 65% in batch mode while increasing slightly the relative purity. Furthermore, the total amount of membrane area required for the CMMC approach was approximately 10% of the area needed for batch operation, while realizing similar processing times. Since CMMC uses smaller membrane sizes, it can take advantage of the high flow rates achievable for membrane chromatography that are not typically possible at larger membrane scales due to skid flow rate limitations. As such, CMMC offers the potential for more efficient and cost-effective purification trains.

Real time on-line amino acid analysis to explore amino acid trends and link to glycosylation outcomes of a model monoclonal antibody

Bioreactor parameters can have significant effects on the quantity and quality of biotherapeutics. Monoclonal antibody products have one particularly important critical quality attribute being the distribution of product glycoforms. N-linked glycosylation affects the therapeutic properties of the antibody including effector function, immunogenicity, stability, and clearance rate. Our past work revealed that feeding different amino acids to bioreactors altered the productivity and glycan profiles. To facilitate real-time analysis of bioreactor parameters and the glycosylation of antibody products, we developed an on-line system to pull cell-free samples directly from the bioreactors, chemically process them, and deliver them to a chromatography-mass spectroscopy system for rapid identification and quantification. We were able to successfully monitor amino acid concentration on-line within multiple reactors, evaluate glycans off-line, and extract four principal components to assess the amino acid concentration and glycosylation profile relationship. We found that about a third of the variability in the glycosylation data can be predicted from the amino acid concentration. Additionally, we determined that the third and fourth principal component accounts for 72% of our model's predictive power, with the third component indicated to be positively correlated with latent metabolic processes related to galactosylation. Here we present our work on rapid online spent media amino acid analysis and use the determined trends to collate with glycan time progression, further elucidating the correlation between bioreactor parameters such as amino acid nutrient profiles, and product quality. We believe such approaches may be useful for maximizing efficiency and reducing production costs for biotherapeutics.

High-throughput capillary electrophoresis analysis of biopharmaceuticals utilizing sequential injections

The complexity of biotherapeutic products implies an ever-increasing list of product quality attributes that need to be monitored and characterized. In addition, the growing interest in implementing process analytical technology in biopharmaceutical production has further increased the testing burden, together with the need for rapid testing that can facilitate real-time or near-real-time decision-making. Capillary electrophoresis (CE) has made a place in biopharmaceutical analysis but is regarded as a low-throughput method, with the instrument dead time constituting more than 80% of the total time of analysis. In this study, the dead time of CE was utilized to analyse 3 mAb samples in a single-CE run. This approach resulted in an up to 77% reduction in the total analysis time and increased the productivity by up to 300%, compared to traditional single CE-ultraviolet runs, without compromising resolution or relative peak areas. Additionally, good method reproducibility was observed. The compatibility of the method has been demonstrated with protein A eluate and cation exchange chromatography fractions. We, thus, propose that sequential injections can be applied for fast and robust CE analysis of biopharmaceuticals.

Advances in bioreactor control for production of biotherapeutic products

Advanced control strategies are well established in chemical, pharmaceutical, and food processing industries. Over the past decade, the application of these strategies is being explored for control of bioreactors for manufacturing of biotherapeutics. Most of the industrial bioreactor control strategies apply classical control techniques, with the control system designed for the facility at hand. However, with the recent progress in sensors, machinery, and industrial internet of things, and advancements in deeper understanding of the biological processes, coupled with the requirement of flexible production, the need to develop a robust and advanced process control system that can ease process intensification has emerged. This has further fuelled the development of advanced monitoring approaches, modeling techniques, process analytical technologies, and soft sensors. It is seen that proper application of these concepts can significantly improve bioreactor process performance, productivity, and reproducibility. This review is on the recent advancements in bioreactor control and its related aspects along with the associated challenges. This study also offers an insight into the future prospects for development of control strategies that can be designed for industrial-scale production of biotherapeutic products.

rAAV Manufacturing: The Challenges of Soft Sensing during Upstream Processing

Recombinant adeno-associated virus (rAAV) is the most effective viral vector technology for directly translating the genomic revolution into medicinal therapies. However, the manufacturing of rAAV viral vectors remains challenging in the upstream processing with low rAAV yield in large-scale production and high cost, limiting the generalization of rAAV-based treatments. This situation can be improved by real-time monitoring of critical process parameters (CPP) that affect critical quality attributes (CQA). To achieve this aim, soft sensing combined with predictive modeling is an important strategy that can be used for optimizing the upstream process of rAAV production by monitoring critical process variables in real time. However, the development of soft sensors for rAAV production as a fast and low-cost monitoring approach is not an easy task. This review article describes four challenges and critically discusses the possible solutions that can enable the application of soft sensors for rAAV production monitoring. The challenges from a data scientist's perspective are (i) a predictor variable (soft-sensor inputs) set without AAV viral titer, (ii) multi-step forecasting, (iii) multiple process phases, and (iv) soft-sensor development composed of the mechanistic model.

Continuous integrated manufacturing for biopharmaceuticals: A new paradigm or an empty promise?

Continuous integrated bioprocessing has elicited considerable interest from the biopharma industry for the many purported benefits it promises. Today many major biopharma manufacturers around the world are engaged in the development of continuous process platforms for their products. In spite of great potential, the path toward continuous integrated bioprocessing remains unclear for the biologics industry due to legacy infrastructure, process integration challenges, vague regulatory guidelines, and a diverging focus toward novel therapies. In this article, we present a review and perspective on this topic. We explore the status of the implementation of continuous integrated bioprocessing among biopharmaceutical manufacturers. We also present some of the key hurdles that manufacturers are likely to face during this implementation. Finally, we hypothesize that the real impact of continuous manufacturing is likely to come when the cost of manufacturing is a substantial portion of the cost of product development, such as in the case of biosimilar manufacturing and emerging economies.

Continuous monitoring of IgG using immobilized fluorescent reporters

In the manufacture of therapeutic monoclonal antibodies, the clarified cell culture fluid (CCF) is typically loaded onto an initial protein A affinity capture column. Imperfect mass transfer and loading to maximum capacity can risk antibody breakthrough and loss of valuable product, but conservative underloading wastes expensive protein A resin. In addition, the effects of column fouling and ligand degradation require the frequent optimization of immunoglobulin G (IgG) loading to avoid wastage. Continuous real-time monitoring of IgG flowthrough is of great interest, therefore. We previously developed a fluorescence-based monitoring technology that allows batch mix-and-read mAb detection in the CCF. Here, we report the use of reporters immobilized on cyanogenbromide-activated Sepharose 4B resin for continuous detection of IgG in column breakthrough. The column effluent is continuously contacted with immobilized fluorescein-labeled Fc-binding ligands in a small monitoring column to produce an immediately-detectable change in fluorescence intensity. The technology allows rapid and reliable monitoring of IgG in a flowing stream of clarified CCF emerging from a protein A column, without prior sample preparation. We observed a significant change in fluorescence intensity at 0.5 g/L human IgG, sufficient to detect a 5% breakthrough of a 10 g/L load, within 18 s at a flow rate of 0.5 ml/min. The current small-scale technology is suitable for use in process development, but the chemistry should be readily adaptable to larger scale applications using fiber-optic sensors, and continuous IgG monitoring could be applicable in a variety of upstream and downstream process settings.

Characterizing viral samples using machine learning for Raman and absorption spectroscopy

Machine learning methods can be used as robust techniques to provide invaluable information for analyzing biological samples in pharmaceutical industries, such as predicting the concentration of viral particles of interest in biological samples. Here, we utilized both convolutional neural networks (CNNs) and random forests (RFs) to predict the concentration of the samples containing measles, mumps, rubella, and varicella-zoster viruses (ProQuad®) based on Raman and absorption spectroscopy. We prepared Raman and absorption spectra data sets with known concentration values, then used the Raman and absorption signals individually and together to train RFs and CNNs. We demonstrated that both RFs and CNNs can make predictions with R2 values as high as 95%. We proposed two different networks to jointly use the Raman and absorption spectra, where our results demonstrated that concatenating the Raman and absorption data increases the prediction accuracy compared to using either Raman or absorption spectrum alone. Additionally, we further verified the advantage of using joint Raman-absorption with principal component analysis. Furthermore, our method can be extended to characterize properties other than concentration, such as the type of viral particles.

Recent Advances and Future Directions in Downstream Processing of Therapeutic Antibodies

Despite the advent of many new therapies, therapeutic monoclonal antibodies remain a prominent biologics product, with a market value of billions of dollars annually. A variety of downstream processing technological advances have led to a paradigm shift in how therapeutic antibodies are developed and manufactured. A key driver of change has been the increased adoption of single-use technologies for process development and manufacturing. An early-stage developability assessment of potential lead antibodies, using both in silico and high-throughput experimental approaches, is critical to de-risk development and identify molecules amenable to manufacturing. Both statistical and mechanistic modelling approaches are being increasingly applied to downstream process development, allowing for deeper process understanding of chromatographic unit operations. Given the greater adoption of perfusion processes for antibody production, continuous and semi-continuous downstream processes are being increasingly explored as alternatives to batch processes. As part of the Quality by Design (QbD) paradigm, ever more sophisticated process analytical technologies play a key role in understanding antibody product quality in real-time. We should expect that computational prediction and modelling approaches will continue to be advanced and exploited, given the increasing sophistication and robustness of predictive methods compared to the costs, time, and resources required for experimental studies.

Converting a mAb downstream process from batch to continuous using process modeling and process analytical technology

The biopharmaceutical market is driving the revolution from traditional batch processes to continuous manufacturing for higher productivity and lower costs. In this work, a batch mAb downstream process has been converted into an integrated continuous process with the combination of multiple techniques. For process intensification, two batch mode unit operations (protein A capture chromatography, ultrafiltration/diafiltration) are converted into continuous ones; For continuity, surge tanks were used between adjacent steps, and level signals were used to trigger process start or stop, forming a holistic continuous process. For process automation, manual operations (e.g., pH and conductivity adjustment) were changed into automatic operation and load mass was controlled with process analytical technology (PAT). A model-based simulation was applied to estimate the loading conditions for the continuous capture process, resulting in 21% resin capacity utilization and 28% productivity improvement as compared to the batch process. Automatic load mass control of cation exchange chromatography was achieved through a customized in-line protein quantity monitoring system, with a difference of less than 1.3% as compared to off-line analysis. Total process time was shortened from 4 days (batch process) to less than 24 hours using the continuous downstream process with the overall productivity of 23.8 g mAb /day for the bench-scale system. Comparable yield and quality data were obtained in three test runs, indicating a successful conversion from a batch process to a continuous process. The insight of this work could be a reference to other similar situations. This article is protected by copyright. All rights reserved.

Challenges and Opportunities of Implementing Data Fusion in Process Analytical Technology-A Review

The release of the FDA's guidance on Process Analytical Technology has motivated and supported the pharmaceutical industry to deliver consistent quality medicine by acquiring a deeper understanding of the product performance and process interplay. The technical opportunities to reach this high-level control have considerably evolved since 2004 due to the development of advanced analytical sensors and chemometric tools. However, their transfer to the highly regulated pharmaceutical sector has been limited. To this respect, data fusion strategies have been extensively applied in different sectors, such as food or chemical, to provide a more robust performance of the analytical platforms. This survey evaluates the challenges and opportunities of implementing data fusion within the PAT concept by identifying transfer opportunities from other sectors. Special attention is given to the data types available from pharmaceutical manufacturing and their compatibility with data fusion strategies. Furthermore, the integration into Pharma 4.0 is discussed.

A Feedback Control Strategy for a Fed-Batch Monoclonal Antibody Production Process Utilising Infrequent and Irregular Sampled Measurements

The ability to take non-invasive Raman measurements presents a unique opportunity to use one Raman probe across multiple vessels in parallel, reducing costs but making measurements infrequent. Under these conditions, infrequent and irregular feedback signals can result in poor closed-loop control performance. This study addressed the issue of infrequent and irregular Raman measurements using a linear dynamic model developed from interpolated data to predict more frequent measurements of the controlled variable. The simulated monoclonal antibody production was sampled hourly with white noise added to the simulated glucose concentration to replicate real Raman measurements. The hourly samples were interpolated into 15 min intervals and a linear dynamic model was developed to predict the glucose concentration at 15 min intervals. These predicted values were then used in a feedback control loop by using model predictive control or a conventional proportional and integral controller to control the glucose concentration at 15 min sampling intervals. For setpoint tracking, the model predictive control reduced the integral of absolute errors to 14,600 from 15,900 (with a 1 h sampling time) or 8.2% reduction. With adaptive model predictive control, the integral of absolute errors was reduced from 14,500 (1 h sampling time) to 14,200 for setpoint tracking and from 13,500 (1 h sampling time) to 13,300 for disturbance rejection. A final comparison demonstrated that the proposed method can also cope with random variations in the sampling time.

Design of 3D-Printed Electronic Fiber Optic Sensor to Detect Rhodamine B Reagent: An Initiation to Potential Virus Detection

A fluorescence device based on ultraviolet light is proposed in this paper, which currently stands at the design stage with the eventual aim to potentially detect virus/antibody fluorescence reactions. The designed device is proposed to have the characteristics of high reflectivity, low power consumption, wide spectrum of light source, and proper silver coating. For fabrication and raising product quality, 3D printing technology and a sputtering test will be used. In this connection, this paper firstly introduces the design sources; then, the ideas of inventing fluorescence detection devices based on ultraviolet light, followed by the data analysis as well as discussing the results of computer simulations. The design process, materials, methods, and experiments are demonstrated following the reality work procedure. Instead of directly using a virus or antibodies for the experiment, at the current design stage, we focus on using this device to detect the rhodamine B reagent. Experiment shows that this reagent can be successfully detected. With this achievement, we logically believe that such type of an ultraviolet optical sensor, with further development and testing, may have the possible value to detect a single virus such as COVID-19, as well as other viruses or small molecules. Though there is long way to go to achieve such a goal, future works experimenting with the detection device on real virus or antibodies can take place more efficiently with a good foundation.

Investigation of an Uncommon Artifact during Reducing Capillary Electrophoresis-Sodium Dodecyl Sulfate Analysis of a Monoclonal Antibody with Dynamic Light Scattering and Reversed Phase High-Performance Liquid Chromatography

PURPOSES

In reducing capillary electrophoresis sodium dodecyl sulfate (CE-SDS) analysis of a monoclonal antibody (mAb-1), the peak area ratio of heavy chain (HC) to light chain (LC) was out of balance, while multiple artifact peaks were observed following the migration of HC. The main purposes of this study were to describe the techniques utilized to eliminate this artifact and clarify the root cause for this interesting phenomenon.

METHODS

We optimized the CE-SDS analysis of mAb-1 by a vairety of techniques including changing the concentration of protein or replacing SDS with a more hydrophobic surfactant (i.e., sodium hexadecyl sulfate (SHS) or sodium tetradecyl sulfate (STS) instead of SDS) in sample and/or the sieving gel buffer. Dynamic light scattering (DLS) and reversed phase high-performance liquid chromatography (RP-HPLC) were used to study the protein-surfactant complex.

RESULTS

The artifact could be partially mitigated by reducing the protein concentration and replacing SDS with SHS or STS in the sample and/or the sieving gel buffer solutions. Due to replacing a more hydrophobic surfactant, the HC-surfactant complex formed was more resistant to dissociation, preventing additional hydrophobic HC-HC interaction and aggregation, thus eliminating the artifact problem.

CONCLUSIONS

DLS and RP-HPLC are powerful supplementary techniques in characterizing the protein-surfactant complex, and hydrophobic surfactants such as SHS and STS could afford more normal electropherograms during the analysis of mAbs.

Laser-Assisted Nanotexturing and Silver Immobilization on Titanium Implant Surfaces to Enhance Bone Cell Mineralization and Antimicrobial Properties

Despite the great advancement and wide use of titanium (Ti) and Ti-based alloys in different orthopedic implants, device-related infections remain the major complication in modern orthopedic and trauma surgery. Most of these infections are often caused by both poor antibacterial and osteoinductive properties of the implant surface. Here, we have demonstrated a facile two-step laser nanotexturing and immobilization of silver onto the titanium implants to improve both cellular integration and antibacterial properties of Ti surfaces. The required threshold laser processing power for effective nanotexturing and osseointegration was systematically determined by the level of osteoblast cells mineralized on the laser nanotextured Ti (LN-Ti) surfaces using a neodymium-doped yttrium aluminum garnet laser (Nd:YAG, wavelength of 1.06 μm). Laser processing powers above 24 W resulted in the formation of hierarchical nanoporous structures (average pore 190 nm) on the Ti surface with a 2.5-fold increase in osseointegration as compared to the pristine Ti surface. Immobilization of silver nanoparticles onto the LN-Ti surface was conducted by dip coating in an aqueous silver ionic solution and subsequently converted to silver nanoparticles (AgNPs) by using a low power laser-assisted photocatalytic reduction process. Structural and surface morphology analysis via XRD and SEM revealed a uniform distribution of Ag and the formation of an AgTi-alloy interface on the Ti surface. The antibacterial efficacy of the LN-Ti with laser immobilized silver (LN-Ti/LI-Ag) was tested against both Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli) bacteria. The LN-Ti/LI-Ag surface was observed to have efficient and stable antimicrobial properties for over 6 days. In addition, it was found that the LN-Ti/LI-Ag maintained a cytocompatibility and bone cell mineralization property similar to the LN-Ti surface. The differential toxicity of the LN-Ti/LI-Ag between bacterial and cellular species qualifies this approach as a promising candidate for novel rapid surface modification of biomedical metal implants.

Towards continuous mAb purification: clearance of host cell proteins from CHO cell culture harvests via "flow-through affinity chromatography" using peptide-based adsorbents

The growth of advanced analytics in manufacturing monoclonal antibodies (mAb) has highlighted the challenges associated with the clearance of host cell proteins (HCPs). Of special concern is the removal of "persistent" HCPs, including immunogenic and mAb-degrading proteins, that co-elute from the Protein A resin and can escape the polishing steps. Responding to this challenge, we introduced an ensemble of peptide ligands that target the HCPs in Chinese hamster ovary (CHO) cell culture fluids and enable mAb purification via flow-through affinity chromatography. This work describes their integration into LigaGuardTM, an affinity adsorbent featuring an equilibrium binding capacity of ~30 mg of HCPs per mL of resin as well as dynamic capacities up to 16 and 22 mg/mL at 1- and 2-minute residence times, respectively. When evaluated against cell culture harvests with different mAb and HCP titers and properties, LigaGuardTM afforded high HCP clearance, with logarithmic removal values (LRVs) up to 1.5, and mAb yield above 90%. Proteomic analysis of the effluents confirmed the removal of high-risk HCPs, including cathepsins, histones, glutathione-S transferase, and lipoprotein lipases. Finally, combining LigaGuardTM for HCP removal with affinity adsorbents for product capture afforded a global mAb yield of 85%, and HCP and DNA LRVs > 4. This article is protected by copyright. All rights reserved.

CDMOs Play a Critical Role in the Biopharmaceutical Ecosystem

Biopharmaceutical industries have advanced significantly after the millennium. Novel biopharmaceuticals have been developed one after another, and blockbuster drugs have been produced. Accompanying the increase in the demand for biopharmaceuticals, a business model called “contract development manufacturing organization (CDMO)” has emerged. A CDMO is entrusted with the development and manufacturing of production processes from pharmaceutical companies. In this review, we identify the success factors of the biopharmaceutical CDMO by analyzing the foundry business for the semiconductor industry. Furthermore, we also review monoclonal antibody production platforms and new technologies that are critical aspects of differentiation strategies in the biopharmaceutical CDMO.

A Comprehensive Review on Therapeutic Perspectives of Phytosterols in Insulin Resistance: A Mechanistic Approach

Natural products in the form of functional foods have become increasingly popular due to their protective effects against life-threatening diseases, low risk of adverse effects, affordability, and accessibility. Plant components such as phytosterol, in particular, have drawn a lot of press recently due to a link between their consumption and a modest incidence of global problems, such as Type 2 Diabetes mellitus (T2DM), cancer, and cardiovascular disease. In the management of diet-related metabolic diseases, such as T2DM and cardiovascular disorders, these plant-based functional foods and nutritional supplements have unquestionably led the market in terms of cost-effectiveness, therapeutic efficacy, and safety. Diabetes mellitus is a metabolic disorder categoriszed by high blood sugar and insulin resistance, which influence major metabolic organs, such as the liver, adipose tissue, and skeletal muscle. These chronic hyperglycemia fallouts result in decreased glucose consumption by body cells, increased fat mobilisation from fat storage cells, and protein depletion in human tissues, keeping the tissues in a state of crisis. In addition, functional foods such as phytosterols improve the body’s healing process from these crises by promoting a proper physiological metabolism and cellular activities. They are plant-derived steroid molecules having structure and function similar to cholesterol, which is found in vegetables, grains, nuts, olive oil, wood pulp, legumes, cereals, and leaves, and are abundant in nature, along with phytosterol derivatives. The most copious phytosterols seen in the human diet are sitosterol, stigmasterol, and campesterol, which can be found in free form, as fatty acid/cinnamic acid esters or as glycosides processed by pancreatic enzymes. Accumulating evidence reveals that phytosterols and diets enriched with them can control glucose and lipid metabolism, as well as insulin resistance. Despite this, few studies on the advantages of sterol control in diabetes care have been published. As a basis, the primary objective of this review is to convey extensive updated information on the possibility of managing diabetes and associated complications with sterol-rich foods in molecular aspects.

Multi-Channel Based Image Processing Scheme for Pneumonia Identification

Pneumonia is a prevalent severe respiratory infection that affects the distal and alveoli airways. Across the globe, it is a serious public health issue that has caused high mortality rate of children below five years old and the aged citizens who must have had previous chronic-related ailment. Pneumonia can be caused by a wide range of microorganisms, including virus, fungus, bacteria, which varies greatly across the globe. The spread of the ailment has gained computer-aided diagnosis (CAD) attention. This paper presents a multi-channel-based image processing scheme to automatically extract features and identify pneumonia from chest X-ray images. The proposed approach intends to address the problem of low quality and identify pneumonia in CXR images. Three channels of CXR images, namely, the Local Binary Pattern (LBP), Contrast Enhanced Canny Edge Detection (CECED), and Contrast Limited Adaptive Histogram Equalization (CLAHE) CXR images are processed by deep neural networks. CXR-related features of LBP images are extracted using shallow CNN, features of the CLAHE CXR images are extracted by pre-trained inception-V3, whereas the features of CECED CXR images are extracted using pre-trained MobileNet-V3. The final feature weights of the three channels are concatenated and softmax classification is utilized to determine the final identification result. The proposed network can accurately classify pneumonia according to the experimental result. The proposed method tested on publicly available dataset reports accuracy of 98.3%, sensitivity of 98.9%, and specificity of 99.2%. Compared with the single models and the state-of-the-art models, our proposed network achieves comparable performance.

Enablers of continuous processing of biotherapeutic products

The benefits of continuous processing over batch manufacturing are widely acknowledged across the biopharmaceutical industry, primary of which are higher productivity and greater consistency in product quality. Furthermore, the reduced equipment and facility footprint lead to significantly lower capital costs. Technology enablers have a major role in this migration from batch to continuous processing. In this review, we highlight the various enablers that are facilitating adoption of continuous upstream and downstream bioprocessing. This includes new bioreactors and cell retention devices for upstream operations, and on-column and continuous flow refolding, novel continuous chromatography, and single-pass filtration systems for downstream processes. We also elucidate the significant roles of process integration and control as well as of data analytics in these processes.

Benchtop Bioreactors in Mammalian Cell Culture: Overview and Guidelines

Bioreactors are manufactured apparatuses that allow the generation of a specific environment for the highly controlled cultivation of living cells. Originally used for microbial production systems, they have found widespread applications in fields as diverse as vaccine production, plant cell cultivation, and the growth of human brain organoids and exist in equally diverse designs (Chu and Robinson, Curr Opin Biotechnol 12(2):180-187, 2001; Qian et al., Nat Protoc 13:565-580, 2018). Manufacturing of biologics is currently mostly performed using a stirred tank bioreactor and CHO host cells and represents the most "classical" bioreactor production process. In this chapter, we will therefore use the cultivation of suspension Chinese hamster ovary (CHO) cells for recombinant protein production in a stirred tank bioreactor as an example. However, general guidelines provided in this chapter are transferable to different bioreactor types and host cells (Li et al., MAbs 2(5):466-479, 2010).The preparation and operation of a bioreactor (also referred to as upstream process in a biotechnological/industrial setting) is comprised of three main steps: expansion (generation of biomass), production (batch, fed-batch, or continuous process), and harvest. The expansion of cells can last from few days to weeks depending on the number of cells at the start, the cellular doubling time, and the required biomass to inoculate the production bioreactor. The production phase lasts a few weeks and is a highly sensitive phase as the concentration of different chemicals and physical parameters need to be tightly controlled. Finally, the harvest will allow the separation of the product of interest from large particles and then the desired material (cell culture supernatant or cells) is transferred to the downstream process.The raw materials used during the upstream phase (all three steps) need to be aligned with the final purpose of the manufactured product, as the presence of residual impurities may have an impact on suitability of the final product for a desired purpose.

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.

A brief review on recent development of multidisciplinary engineering in fermentation of Saccharomyces cerevisiae

Fermentation technology has unprecedented potential to upgrade state-of-art biotechnology and refine the processes used in existing ones, taking into account of complex technical, economic and environmental factors. Given the economic importance and ongoing challenges of biotech sector, multidisciplinary engineering technologies is poised to become an increasingly important tool along with the emergence of modern technology and innovation. This article reviews recent technology advancement in the field of fermentation using Saccharomyces cerevisiae. Interesting research progress has been made by leveraging multiple engineering fields such as electrical engineering, information engineering, electrochemical engineering and new material development, leading to recent development of novel real-time probes (electronic nose technology, analysis of yeast morphology and metabolites, timely control of glucose feed), improved understanding of electro-fermentation (enhanced electronic transfer provision), as well as application of cost-effective and sustainable materials (bioreactor vessel manufactured from textile, and yeast immobilisation support matrix made from abundant natural biomass). To the best of our knowledge, the subject is reviewed for the first time in recent years. Furthermore, this review also constitutes a futuristic S. cerevisiae fermentation process based on the recent advancement discussed.

Biosensors Coupled with Signal Amplification Technology for the Detection of Pathogenic Bacteria: A Review

Foodborne disease caused by foodborne pathogens is a very important issue in food safety. Therefore, the rapid screening and sensitive detection of foodborne pathogens is of great significance for ensuring food safety. At present, many research works have reported the application of biosensors and signal amplification technologies to achieve the rapid and sensitive detection of pathogenic bacteria. Thus, this review summarized the use of biosensors coupled with signal amplification technology for the detection of pathogenic bacteria, including (1) the development, concept, and principle of biosensors; (2) types of biosensors, such as electrochemical biosensors, optical biosensors, microfluidic biosensors, and so on; and (3) different kinds of signal amplification technologies applied in biosensors, such as enzyme catalysis, nucleic acid chain reaction, biotin-streptavidin, click chemistry, cascade reaction, nanomaterials, and so on. In addition, the challenges and future trends for pathogenic bacteria based on biosensor and signal amplification technology were also discussed and summarized.

Integrative overview of antibodies against SARS-CoV-2 and their possible applications in COVID-19 prophylaxis and treatment

SARS-CoV-2 is a novel β-coronavirus that caused the COVID-19 pandemic disease, which spread rapidly, infecting more than 134 million people, and killing almost 2.9 million thus far. Based on the urgent need for therapeutic and prophylactic strategies, the identification and characterization of antibodies has been accelerated, since they have been fundamental in treating other viral diseases. Here, we summarized in an integrative manner the present understanding of the immune response and physiopathology caused by SARS-CoV-2, including the activation of the humoral immune response in SARS-CoV-2 infection and therefore, the synthesis of antibodies. Furthermore, we also discussed about the antibodies that can be generated in COVID-19 convalescent sera and their associated clinical studies, including a detailed characterization of a variety of human antibodies and identification of antibodies from other sources, which have powerful neutralizing capacities. Accordingly, the development of effective treatments to mitigate COVID-19 is expected. Finally, we reviewed the challenges faced in producing potential therapeutic antibodies and nanobodies by cell factories at an industrial level while ensuring their quality, efficacy, and safety.

Manufacturing of bacteriophages for therapeutic applications

Bacteriophages, or simply phages, are the most abundant biological entities on Earth. One of the most interesting characteristics of these viruses, which infect and use bacteria as their host organisms, is their high level of specificity. Since their discovery, phages became a tool for the comprehension of basic molecular biology and originated applications in a variety of areas such as agriculture, biotechnology, food safety, veterinary, pollution remediation and wastewater treatment. In particular, phages offer a solution to one of the major problems in public health nowadays, i.e. the emergence of multidrug-resistant bacteria. In these situations, the use of virulent phages as therapeutic agents offers an alternative to the classic, antibiotic-based strategies. The development of phage therapies should be accompanied by the improvement of phage biomanufacturing processes, both at laboratory and industrial scales. In this review, we first present some historical and general aspects related with the discovery, usage and biology of phages and provide a brief overview of the most relevant phage therapy applications. Then, we showcase current processes used for the production and purification of phages and future alternatives in development. On the production side, key factors such as the bacterial physiological state, the conditions of phage infection and the operation parameters are described alongside with the different operation modes, from batch to semi-continuous and continuous. Traditional purification methods used in the initial phage isolation steps are then described followed by the presentation of current state-of-the-art purification approaches. Continuous purification of phages is finally presented as a future biomanufacturing trend.

Advanced control strategies for bioprocess chromatography: Challenges and opportunities for intensified processes and next generation products

Recent advances in process analytical technologies and modelling techniques present opportunities to improve industrial chromatography control strategies to enhance process robustness, increase productivity and move towards real-time release testing. This paper provides a critical overview of batch and continuous industrial chromatography control systems for therapeutic protein purification. Firstly, the limitations of conventional industrial fractionation control strategies using in-line UV spectroscopy and on-line HPLC are outlined. Following this, an evaluation of monitoring and control techniques showing promise within research, process development and manufacturing is provided. These novel control strategies combine rapid in-line data capture (e.g. NIR, MALS and variable pathlength UV) with enhanced process understanding obtained from mechanistic and empirical modelling techniques. Finally, a summary of the future states of industrial chromatography control systems is proposed, including strategies to control buffer formulation, product fractionation, column switching and column fouling. The implementation of these control systems improves process capabilities to fulfil product quality criteria as processes are scaled, transferred and operated, thus fast tracking the delivery of new medicines to market.

Raman spectra-based deep learning: A tool to identify microbial contamination

Deep learning has the potential to enhance the output of in‐line, on‐line, and at‐line instrumentation used for process analytical technology in the pharmaceutical industry. Here, we used Raman spectroscopy‐based deep learning strategies to develop a tool for detecting microbial contamination. We built a Raman dataset for microorganisms that are common contaminants in the pharmaceutical industry for Chinese Hamster Ovary (CHO) cells, which are often used in the production of biologics. Using a convolution neural network (CNN), we classified the different samples comprising individual microbes and microbes mixed with CHO cells with an accuracy of 95%–100%. The set of 12 microbes spans across Gram‐positive and Gram‐negative bacteria as well as fungi. We also created an attention map for different microbes and CHO cells to highlight which segments of the Raman spectra contribute the most to help discriminate between different species. This dataset and algorithm provide a route for implementing Raman spectroscopy for detecting microbial contamination in the pharmaceutical industry.