Towards real-time monitoring of therapeutic protein quality in mammalian cell processes

Soft sensor for viable cell counting by measuring dynamic oxygen uptake rate

Regulatory authorities in biopharmaceutical industry emphasize process design by process understanding but applicable tools that are easy to implement are still missing. Soft sensors are a promising tool for the implementation of the Quality by Design (QbD) approach and Process Analytical Technology (PAT). In particular, the correlation between viable cell counting and oxygen consumption was investigated, but problems remained: Either the process had to be modified for excluding CO2 in pH control, or complex kLa models had to be set up for specific processes. In this work, a non-invasive soft sensor for simplified on-line cell counting based on dynamic oxygen uptake rate was developed with no need of special equipment. The dynamic oxygen uptake rates were determined by automated and periodic interruptions of gas supply in DASGIP® bioreactor systems, realized by a programmed Visual Basic script in the DASware® control software. With off-line cell counting, the two parameters were correlated based on linear regression and led to a robust model with a correlation coefficient of 0.92. Avoidance of oxygen starvation was achieved by gas flow reactivation at a certain minimum dissolved oxygen concentration. The soft sensor model was established in the exponential growth phase of a Chinese Hamster Ovary fed-batch process. Control studies showed no impact on cell growth by the discontinuous gas supply. This soft sensor is the first to be presented that does not require any specialized additional equipment as the methodology relies solely on the direct measurement of oxygen consumed by the cells in the bioreactor.

Current and future technologies for monitoring cultured meat: A review

The high population growth rate, massive animal food consumption, fast economic progress, and limited food resources could lead to a food crisis in the future. There is a huge requirement for dietary proteins including cultured meat is being progressed to fulfill the need for meat-derived proteins in the diet. However, production of cultured meat requires monitoring numerous bioprocess parameters. This review presents a comprehensive overview of various widely adopted techniques (optical, spectroscopic, electrochemical, capacitive, FETs, resistive, microscopy, and ultrasound) for monitoring physical, chemical, and biological parameters that can improve the bioprocess control in cultured meat. The methods, operating principle, merits/demerits, and the main open challenges are reviewed with the aim to support the readers in advancing knowledge on novel sensing systems for cultured meat applications.

Analysis of Protein Glycosylation after Rapid Digestion Using Protease-Containing Membranes in Spin Columns

Glycosylation is an important protein post-translational modification that plays a pivotal role in the bioactivity of therapeutic proteins and in the infectivity of viral proteins. Liquid chromatography with tandem mass spectrometry readily identifies protein glycans with site specificity. However, the overnight incubation used in conventional in-solution proteolysis leads to high turnaround times for glycosylation analysis, particularly when sequential in-solution digestions are needed for site-specific glycan identification. Using bovine fetuin as a model glycoprotein, this work first shows that in-membrane digestion in ∼3 min yields similar glycan identification and quantitation when compared to overnight in-solution digestion. Protease-containing membranes in a spin column enable digestion of therapeutic proteins (trastuzumab and erythropoietin) and a viral protein (SARS-CoV-2 receptor binding domain) in ∼30 s. Glycan identification is similar after in-solution and in-membrane digestion, and limited in-membrane digestion enhances the identification of high-mannose glycans in trastuzumab. Finally, stacked membranes containing trypsin and chymotrypsin allow fast sequential proteolytic digestion to site-specifically identify the glycans of SARS-CoV-2 receptor binding domain. One can easily assemble the protease-containing membranes in commercial spin columns, and spinning multiple columns simultaneously will facilitate parallel analyses.

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.

Measurement of the Size Distribution of Multimodal Colloidal Systems by Laser Diffraction

Laser diffraction (LD) is a well-established tool for the measurement of particle size distribution. Recently, its demand and use for the measurement of complex biological systems have increased. Among the challenges that these types of samples present, there is the presence of multiple particle populations whose modal size may span across several orders of magnitude. In this study, we assessed the accuracy of LD for the measurement of the modal diameter of both single and mixed populations of polystyrene particles with diameters ranging from 60 nm to 40 μm. We discuss the application of different available algorithms to the analysis of the data and their impact on the measurement results. Independent methods were applied to guide the selection of the algorithms and validate the measured size distributions. We found that the modal diameters of the particle size distribution measured by LD for the mixed suspension was accurate within 2 % for particles larger than 1 μm and generally within 25 % for the particles tested. Method repeatability was found to be robust, with deviations below 1%. The method was also found to be useful for estimating the relative concentration of the particle populations in the mixed samples. This study provides confidence in the use of LD for the measurement of complex multimodal colloidal samples.

Multiplexed Microfluidic Cartridge for At-Line Protein Monitoring in Mammalian Cell Culture Processes for Biopharmaceutical Production

The biopharmaceutical market has been rapidly growing in recent years, creating a highly competitive arena where R&D is critical to strike a balance between clinical safety and profitability. Toward process optimization, the recent development and adoption of new process analytical technologies (PAT) highlight the dynamic complexity of mammalian/human cell culture processes, as well as the importance of fine-tuning and modeling key metabolites and proteins. In this context, simple, rapid, and cost-effective devices allowing routine at-line monitoring of specific proteins during process development and production are currently lacking. Here, we report the development of a versatile microfluidic protein analysis cartridge allowing the multiplexed bead-based immunodetection of specific proteins directly from complex mixtures with minimal hands-on time. Colorimetric quantification of Chinese hamster ovary (CHO) host cell proteins as key impurities, monoclonal antibodies as target biopharmaceuticals, and lactate dehydrogenase as a marker of cell viability was achieved with limits of detection in the 1–10 ng/mL range and analysis times as short as 30 min. The device was further demonstrated for the monitoring of a Rituximab-producing CHO cell bioreactor over the course of 8 days, providing comparable recoveries to standard enzyme-linked immunosorbent assay (ELISA) kits. The high sensitivity combined with robustness to matrix interference highlights the potential of the device to perform at-line measurements spanning from the bioreactor to the downstream processing.

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.

ATR-FTIR spectroscopy and spectroscopic imaging for the analysis of biopharmaceuticals

Attenuated Total Reflection Fourier Transform Infrared (ATR-FTIR) spectroscopy is a label-free, non-destructive technique that can be applied to a vast range of biological applications, from imaging cancer tissues and live cells, to determining protein content and protein secondary structure composition. This review summarises the recent advances in applications of ATR-FTIR spectroscopy to biopharmaceuticals, the application of this technique to biosimilars, and the current uses of FTIR spectroscopy in biopharmaceutical production. We discuss the use of ATR-FTIR spectroscopic imaging to investigate biopharmaceuticals, and finally, give an outlook on the possible future developments and applications of ATR-FTIR spectroscopy and spectroscopic imaging to this field. Throughout the review comparisons will be made between FTIR spectroscopy and alternative analytical techniques, and areas will be identified where FTIR spectroscopy could perhaps offer a better alternative in future studies. This review focuses on the most recent advances in the field of using ATR-FTIR spectroscopy and spectroscopic imaging to characterise and evaluate biopharmaceuticals, both in industrial and academic research based environments.

Portable Analytical Techniques for Monitoring Volatile Organic Chemicals in Biomanufacturing Processes: Recent Advances and Limitations

It is essential to develop effective analytical techniques for accurate and continuous monitoring of various biomanufacturing processes, such as the production of monoclonal antibodies and vaccines, through sensitive and quantitative detection of characteristic aqueous or gaseous metabolites and other analytes in the cell culture media. A comprehensive summary toward the use of mainstream techniques for bioprocess monitoring is critically reviewed here, which illustrates the instrumental and procedural advances and limitations of several major analytical tools in biomanufacturing applications. Despite those drawbacks present in modern detection systems such as mass spectrometry, gas chromatography or chemical/biological sensors, a considerable number of useful solutions and inspirations such as electronic or optoelectronic noses can be offered to greatly overcome the restrictions and facilitate the development of advanced analytical techniques that can target a more diverse range of key nutritious components, products or potential contaminants in different biomanufacturing processes.

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.

Holographic Imaging of Insect Cell Cultures: Online Non-Invasive Monitoring of Adeno-Associated Virus Production and Cell Concentration

The insect cell-baculovirus vector system has become one of the favorite platforms for the expression of viral vectors for vaccination and gene therapy purposes. As it is a lytic system, it is essential to balance maximum recombinant product expression with harvest time, minimizing product exposure to detrimental proteases. With this purpose, new bioprocess monitoring solutions are needed to accurately estimate culture progression. Herein, we used online digital holographic microscopy (DHM) to monitor bioreactor cultures of Sf9 insect cells. Batches of baculovirus-infected Sf9 cells producing recombinant adeno-associated virus (AAV) and non-infected cells were used to evaluate DHM prediction capabilities for viable cell concentration, culture viability and AAV titer. Over 30 cell-related optical attributes were quantified using DHM, followed by a forward stepwise regression to select the most significant (p < 0.05) parameters for each variable. We then applied multiple linear regression to obtain models which were able to predict culture variables with root mean squared errors (RMSE) of 7 × 105 cells/mL, 3% for cell viability and 2 × 103 AAV/cell for 3-fold cross-validation. Overall, this work shows that DHM can be implemented for online monitoring of Sf9 concentration and viability, also permitting to monitor product titer, namely AAV, or culture progression in lytic systems, making it a valuable tool to support the time of harvest decision and for the establishment of controlled feeding strategies.

The Rocky Road From Fed-Batch to Continuous Processing With E. coli

Escherichia coli still serves as a beloved workhorse for the production of many biopharmaceuticals as it fulfills essential criteria, such as having fast doubling times, exhibiting a low risk of contamination, and being easy to upscale. Most industrial processes in E. coli are carried out in fed-batch mode. However, recent trends show that the biotech industry is moving toward time-independent processing, trying to improve the space-time yield, and especially targeting constant quality attributes. In the 1950s, the term "chemostat" was introduced for the first time by Novick and Szilard, who followed up on the previous work performed by Monod. Chemostat processing resulted in a major hype 10 years after its official introduction. However, enthusiasm decreased as experiments suffered from genetic instabilities and physiology issues. Major improvements in strain engineering and the usage of tunable promotor systems facilitated chemostat processes. In addition, critical process parameters have been identified, and the effects they have on diverse quality attributes are understood in much more depth, thereby easing process control. By pooling the knowledge gained throughout the recent years, new applications, such as parallelization, cascade processing, and population controls, are applied nowadays. However, to control the highly heterogeneous cultivation broth to achieve stable productivity throughout long-term cultivations is still tricky. Within this review, we discuss the current state of E. coli fed-batch process understanding and its tech transfer potential within continuous processing. Furthermore, the achievements in the continuous upstream applications of E. coli and the continuous downstream processing of intracellular proteins will be discussed.

High-Throughput Process Development for Biopharmaceuticals

The ability to conduct multiple experiments in parallel significantly reduces the time that it takes to develop a manufacturing process for a biopharmaceutical. This is particularly significant before clinical entry, because process development and manufacturing are on the "critical path" for a drug candidate to enter clinical development. High-throughput process development (HTPD) methodologies can be similarly impactful during late-stage development, both for developing the final commercial process as well as for process characterization and scale-down validation activities that form a key component of the licensure filing package. This review examines the current state of the art for HTPD methodologies as they apply to cell culture, downstream purification, and analytical techniques. In addition, we provide a vision of how HTPD activities across all of these spaces can integrate to create a rapid process development engine that can accelerate biopharmaceutical drug development. Graphical Abstract.

Prediction of N-linked Glycoform Profiles of Monoclonal Antibody with Extracellular Metabolites and Two-Step Intracellular Models

Monoclonal antibodies (mAbs) are commonly glycosylated and show varying levels of galactose attachment. A set of experiments in our work showed that the galactosylation level of mAbs was altered by the culture conditions of hybridoma cells. The uridine diphosphate galactose (UDP-Gal) is one of the substrates of galactosylation. Based on that, we proposed a two-step model to predict N-linked glycoform profiles by solely using extracellular metabolites from cell culture. At the first step, the flux level of UDP-Gal in each culture was estimated based on a computational flux balance analysis (FBA); its level was found to be linear with the galactosylation degree on mAbs. At the second step, the glycoform profiles especially for G0F (agalactosylated), G1F (monogalactosylated) and G2F (digalactosylated) were predicted by a kinetic model. The model outputs well matched with the experimental data. Our study demonstrated that the integrated mathematical approach combining FBA and kinetic model is a promising strategy to predict glycoform profiles for mAbs during cell culture processes.

Real-time monitoring and model-based prediction of purity and quantity during a chromatographic capture of fibroblast growth factor 2

Process analytical technology combines understanding and control of the process with real‐time monitoring of critical quality and performance attributes. The goal is to ensure the quality of the final product. Currently, chromatographic processes in biopharmaceutical production are predominantly monitored with UV/Vis absorbance and a direct correlation with purity and quantity is limited. In this study, a chromatographic workstation was equipped with additional online sensors, such as multi‐angle light scattering, refractive index, attenuated total reflection Fourier‐transform infrared, and fluorescence spectroscopy. Models to predict quantity, host cell proteins (HCP), and double‐stranded DNA (dsDNA) content simultaneously were developed and exemplified by a cation exchange capture step for fibroblast growth factor 2 expressed in Escherichia coliOnline data and corresponding offline data for product quantity and co‐eluting impurities, such as dsDNA and HCP, were analyzed using boosted structured additive regression. Different sensor combinations were used to achieve the best prediction performance for each quality attribute. Quantity can be adequately predicted by applying a small predictor set of the typical chromatographic workstation sensor signals with a test error of 0.85 mg/ml (range in training data: 0.1–28 mg/ml). For HCP and dsDNA additional fluorescence and/or attenuated total reflection Fourier‐transform infrared spectral information was important to achieve prediction errors of 200 (2–6579 ppm) and 340 ppm (8–3773 ppm), respectively.

Accelerated Bioprocess Development of Endopolygalacturonase-Production with Saccharomyces cerevisiae Using Multivariate Prediction in a 48 Mini-Bioreactor Automated Platform

Mini-bioreactor systems enabling automatized operation of numerous parallel cultivations are a promising alternative to accelerate and optimize bioprocess development allowing for sophisticated cultivation experiments in high throughput. These include fed-batch and continuous cultivations with multiple options of process control and sample analysis which deliver valuable screening tools for industrial production. However, the model-based methods needed to operate these robotic facilities efficiently considering the complexity of biological processes are missing. We present an automated experiment facility that integrates online data handling, visualization and treatment using multivariate analysis approaches to design and operate dynamical experimental campaigns in up to 48 mini-bioreactors (8⁻12 mL) in parallel. In this study, the characterization of Saccharomyces cerevisiae AH22 secreting recombinant endopolygalacturonase is performed, running and comparing 16 experimental conditions in triplicate. Data-driven multivariate methods were developed to allow for fast, automated decision making as well as online predictive data analysis regarding endopolygalacturonase production. Using dynamic process information, a cultivation with abnormal behavior could be detected by principal component analysis as well as two clusters of similarly behaving cultivations, later classified according to the feeding rate. By decision tree analysis, cultivation conditions leading to an optimal recombinant product formation could be identified automatically. The developed method is easily adaptable to different strains and cultivation strategies, and suitable for automatized process development reducing the experimental times and costs.

Bioengineering Solutions for Manufacturing Challenges in CAR T Cells

The next generation of therapeutic products to be approved for the clinic is anticipated to be cell therapies, termed "living drugs" for their capacity to dynamically and temporally respond to changes during their production ex vivo and after their administration in vivo. Genetically engineered chimeric antigen receptor (CAR) T cells have rapidly developed into powerful tools to harness the power of immune system manipulation against cancer. Regulatory agencies are beginning to approve CAR T cell therapies due to their striking efficacy in treating some hematological malignancies. However, the engineering and manufacturing of such cells remains a challenge for widespread adoption of this technology. Bioengineering approaches including biomaterials, synthetic biology, metabolic engineering, process control and automation, and in vitro disease modeling could offer promising methods to overcome some of these challenges. Here, we describe the manufacturing process of CAR T cells, highlighting potential roles for bioengineers to partner with biologists and clinicians to advance the manufacture of these complex cellular products under rigorous regulatory and quality control.

Real-time monitoring of antibody glycosylation site occupancy by in situ Raman spectroscopy during bioreactor CHO cell cultures

The glycosylation of therapeutic monoclonal antibodies (mAbs), a known critical quality attribute, is often greatly modified during the production process by animal cells. It is essential for biopharmaceutical industries to monitor and control this glycosylation. However, current glycosylation characterization techniques involve time- and labor-intensive analyses, often carried out at the end of the culture when the product is already synthesized. This study proposes a novel methodology for real-time monitoring of antibody glycosylation site occupancy using Raman spectroscopy. It was first observed in CHO cell batch culture that when low nutrient concentrations were reached, a decrease in mAb glycosylation was induced, which made it essential to rapidly detect this loss of product quality. By combining in situ Raman spectroscopy with chemometric tools, efficient prediction models were then developed for both glycosylated and nonglycosylated mAbs. By comparing variable importance in projection profiles of the prediction models, it was confirmed that Raman spectroscopy is a powerful method to distinguish extremely similar molecules, despite the high complexity of the culture medium. Finally, the Raman prediction models were used to monitor batch and feed-harvest cultures in situ. For the first time, it was demonstrated that the concentrations of glycosylated and nonglycosylated mAbs could be successfully and simultaneously estimated in real time with high accuracy, including their sudden variations due to medium exchanges. Raman spectroscopy can thus be considered as a promising PAT tool for feedback process control dedicated to on-line optimization of mAb quality. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:486-493, 2018.

Nanofluidic device for continuous multiparameter quality assurance of biologics

Process analytical technology (PAT) is critical for the manufacture of high-quality biologics as it enables continuous, real-time and on-line/at-line monitoring during biomanufacturing processes. The conventional analytical tools currently used have many restrictions to realizing the PAT of current and future biomanufacturing. Here we describe a nanofluidic device for the continuous monitoring of biologics' purity and bioactivity with high sensitivity, resolution and speed. Periodic and angled nanofilter arrays served as the molecular sieve structures to conduct a continuous size-based analysis of biologics. A multiparameter quality monitoring of three separate commercial biologic samples within 50 minutes has been demonstrated, with 20 µl of sample consumption, inclusive of dead volume in the reservoirs. Additionally, a proof-of-concept prototype system, which integrates an on-line sample-preparation system and the nanofluidic device, was demonstrated for at-line monitoring. Thus, the system is ideal for on-site monitoring, and the real-time quality assurance of biologics throughout the biomanufacturing processes.

Applications of Raman Spectroscopy in Biopharmaceutical Manufacturing: A Short Review

The production of active pharmaceutical ingredients (APIs) is currently undergoing its biggest transformation in a century. The changes are based on the rapid and dramatic introduction of protein- and macromolecule-based drugs (collectively known as biopharmaceuticals) and can be traced back to the huge investment in biomedical science (in particular in genomics and proteomics) that has been ongoing since the 1970s. Biopharmaceuticals (or biologics) are manufactured using biological-expression systems (such as mammalian, bacterial, insect cells, etc.) and have spawned a large (>€35 billion sales annually in Europe) and growing biopharmaceutical industry (BioPharma). The structural and chemical complexity of biologics, combined with the intricacy of cell-based manufacturing, imposes a huge analytical burden to correctly characterize and quantify both processes (upstream) and products (downstream). In small molecule manufacturing, advances in analytical and computational methods have been extensively exploited to generate process analytical technologies (PAT) that are now used for routine process control, leading to more efficient processes and safer medicines. In the analytical domain, biologic manufacturing is considerably behind and there is both a huge scope and need to produce relevant PAT tools with which to better control processes, and better characterize product macromolecules. Raman spectroscopy, a vibrational spectroscopy with a number of useful properties (nondestructive, non-contact, robustness) has significant potential advantages in BioPharma. Key among them are intrinsically high molecular specificity, the ability to measure in water, the requirement for minimal (or no) sample pre-treatment, the flexibility of sampling configurations, and suitability for automation. Here, we review and discuss a representative selection of the more important Raman applications in BioPharma (with particular emphasis on mammalian cell culture). The review shows that the properties of Raman have been successfully exploited to deliver unique and useful analytical solutions, particularly for online process monitoring. However, it also shows that its inherent susceptibility to fluorescence interference and the weakness of the Raman effect mean that it can never be a panacea. In particular, Raman-based methods are intrinsically limited by the chemical complexity and wide analyte-concentration-profiles of cell culture media/bioprocessing broths which limit their use for quantitative analysis. Nevertheless, with appropriate foreknowledge of these limitations and good experimental design, robust analytical methods can be produced. In addition, new technological developments such as time-resolved detectors, advanced lasers, and plasmonics offer potential of new Raman-based methods to resolve existing limitations and/or provide new analytical insights.

A Multidimensional Analytical Comparison of Remicade and the Biosimilar Remsima

In April 2016, the Food and Drug Administration approved the first biosimilar monoclonal antibody (mAb), Inflectra/Remsima (Celltrion), based off the original product Remicade (infliximab, Janssen). Biosimilars promise significant cost savings for patients, but the unavoidable differences between innovator and copycat biologics raise questions regarding product interchangeability. In this study, Remicade and Remsima were examined by native mass spectrometry, ion mobility, and quantitative peptide mapping. The levels of oxidation, deamidation, and mutation of individual amino acids were remarkably similar. We found different levels of C-terminal truncation, soluble protein aggregates, and glycation that all likely have a limited clinical impact. Importantly, we identified more than 25 glycoforms for each product and observed glycoform population differences, with afucosylated glycans accounting for 19.7% of Remicade and 13.2% of Remsima glycoforms, which translated into a 2-fold reduction in the level of FcγIIIa receptor binding for Remsima. While this difference was acknowledged in Remsima regulatory filings, our glycoform analysis and receptor binding results appear to be somewhat different from the published values, likely because of methodological differences between laboratories and improved glycoform identification by our laboratory using a peptide map-based method. Our mass spectrometry-based analysis provides rapid and robust analytical information vital for biosimilar development. We have demonstrated the utility of our multiple-attribute monitoring workflow using the model mAbs Remicade and Remsima and have provided a template for analysis of future mAb biosimilars.

Development of a quantitative mass spectrometry multi-attribute method for characterization, quality control testing and disposition of biologics

Regulatory agencies have recently recommended a Quality by Design (QbD) approach for the manufacturing of therapeutic molecules. A QbD strategy requires deep understanding at the molecular level of the attributes that are crucial for safety and efficacy and for insuring that the desired quality of the purified protein drug product is met at the end of the manufacturing process. A mass spectrometry (MS)-based approach to simultaneously monitor the extensive array of product quality attributes (PQAs) present on therapeutic molecules has been developed. This multi-attribute method (MAM) uses a combination of high mass accuracy / high resolution MS data generated by Orbitrap technology and automated identification and relative quantification of PQAs with dedicated software (Pinpoint). The MAM has the potential to replace several conventional electrophoretic and chromatographic methods currently used in Quality Control to release therapeutic molecules. The MAM represents an optimized analytical solution to focus on the attributes of the therapeutic molecule essential for function and implement QbD principles across process development, manufacturing and drug disposition.

A framework for real-time glycosylation monitoring (RT-GM) in mammalian cell culture

Glycosylation is a critical characteristic of biotherapeutics because of its central role in in vivo efficacy. Multiple factors including medium composition and process conditions impact protein glycosylation and characterizing cellular response to these changes is essential to understand the underlying relationships. Current practice typically involves glycosylation characterization at the end of a fed-batch culture, which in addition to being an aggregate of the process, reflects a bias towards the end of the culture where a majority of the product is made. In an attempt to rigorously characterize the entire time-course of a fed-batch culture, a real-time glycosylation monitoring (RT-GM) framework was developed. It involves using the micro sequential injection (μSI) system as a sample preparation platform coupled with an ultra-performance liquid chromatography (UPLC) system for real-time monitoring of the antibody glycan profile. Automated sampling and sample preparations were performed using the μSI system and this framework was used to study manganese (Mn)-induced glycosylation changes over the course of a fed-batch culture. As expected, Mn-supplemented cultures exhibited higher galactosylation levels compared to control while the fucosylation and mannosylation were consistent for both supplemented and control cultures. Overall, the approach presented in the study allows real time monitoring of glycosylation changes and this information can be rapidly translated into process control and/or process optimization decisions to accelerate process development.