Manufacture Of Monoclonal Antibodies Research Articles

REGULATORY CHALLENGES AND LANDSCAPES OF MONOCLONAL ANTIBODY REGISTRATION: GLOBAL OUTLOOK

Objective: This review aims to illuminate the unprecedented growth and versatile therapeutic landscape of monoclonal antibody (mAb) products, highlighting their significant impact on diverse medical fields such as oncology, septicemia treatment, infection management, and substance abuse disorder interventions. This review outlines the challenges associated with the development, manufacturing, and regulatory approval of monoclonal antibodies, emphasizing the need for diligent attention to overcome these complexities. The review comprehensively examines the historical evolution and therapeutic applications of monoclonal antibodies, emphasizing their potent and versatile characteristics that have enabled successful interventions in challenging regulatory approvals. It delves into the critical considerations in manufacturing, regulatory navigation, and the strategic integration of expedited approval pathways, providing a holistic understanding of the intricate terrain of innovation, clinical translation, and impactful patient care in the realm of monoclonal antibody products. Monoclonal antibodies have significantly advanced medical treatment in various domains, revolutionizing cancer therapy, offering new avenues for septicemia management, augmenting the arsenal against infections, and opening novel pathways for addressing substance abuse disorders. Their development and regulatory approval are associated with challenges of scientific innovation, manufacturing, and regulatory compliance. Despite the challenges, monoclonal antibodies have demonstrated remarkable potential in addressing complex medical conditions. The review serves as a compass, guiding researchers, clinicians, and regulatory authorities through the intricate terrain of monoclonal antibody innovation and clinical translation. It emphasizes the need for diligent attention to overcome the complexities associated with their development and regulatory approval while highlighting their significant impact on advancing patient care.

Abstract 5741: siteDAR, complete antibody drug conjugate, ADC characterization

Abstract Antibody drug conjugate characterization currently extends to the global determination of the drug -to- antibody ratio (DAR). However, there can be confounding batch variability in pharmacological outcome from ADCs of the same drug, antibody, and DAR. Previously, DAR was obtained by quantifying the extent of modification of the intact antibody or its protein subunits. The coupling chemistry is used to infer which type of amino acids were modified but generally no specific sites of modification are identified and if identification is obtained, it is not quantitative. Borrowing the rigorously reproducible proteolytic digestion methods from multi-atribute mapping (MAM) used in monoclonal antibody manufacture, and compiling a comprehensive quantitative assignment of every abundant peptide in the ADC digest we can both calculate a DAR from the ion volume ratios and a quantitative map of the specific modified sites. This method, termed “siteDAR”, is applied here to both commercial Kadcyla® (ado-trastuzumab emtansine) and in-house preparations of ado-trastuzumab emtansine. We show that preparations of Kadcyla® with the same DAR can have significantly different quantitative maps of modification sites. We use siteDAR analysis in our ADC design cycle to characterize an ADC, and have developed an ADC synthesis method that was quantitatively verified, and had increased biosimilarity with commercially available Kadcyla®. siteDAR for commercial Kadcyla siteDAR for initial in-house Kadcyla Initial biosimilarity Citation Format: Warham L. Martin, Michael Senseney, Bhaskar Kusuma, Julien Dugal-Tessier, Nareshkumar Jain. siteDAR, complete antibody drug conjugate, ADC characterization [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5741.

Continuous multi-column capture of monoclonal antibodies with convective diffusive membrane adsorbers.

Downstream processing is the bottleneck in the continuous manufacturing of monoclonal antibodies (mAbs). To overcome throughput limitations, two different continuous processes with a novel convective diffusive protein A membrane adsorber (MA) were investigated: the rapid cycling parallel multi-column chromatography (RC-PMCC) process and the rapid cycling simulated moving bed (RC-BioSMB) process. First, breakthrough curve experiments were performed to investigate the influence of the flow rate on the mAb dynamic binding capacity and to calculate the duration of the loading steps. In addition, customized control software was developed for an automated MA exchange in case of pressure increase due to membrane fouling to enable robust, uninterrupted, and continuous processing. Both processes were performed for 4 days with 0.61 g L-1 mAb-containing filtrate and process performance, product purity, productivity, and buffer consumption were compared. The mAb was recovered with a yield of approximately 90% and productivities of 1010 g L-1 d-1 (RC-PMCC) and 574 g L-1 d-1 (RC-BioSMB). At the same time, high removal of process-related impurities was achieved with both processes, whereas the buffer consumption was lower for the RC-BioSMB process. Finally, the attainable productivity for perfusion bioreactors of different sizes with suitable MA sizes was calculated to demonstrate the potential to operate both processes on a manufacturing scale with bioreactor volumes of up to 2000 L.

A model-based performance analysis of integrated chromatography-ultrafilter separation systems for monoclonal antibody (mAb) manufacturing

Robust and accurate modelling of bioprocess systems offers the opportunity to visualise strategies for rapid-scale up of production platforms from benchtop to industrial scale, but few studies investigate how mechanistic and hybrid models can be used to design integrated bio-manufacturing. This is especially true for downstream purification technologies used to separate mAbs from culture by-products, e.g. host cell proteins. Polishing chromatography (cation-exchange mode) is commonly used to remove these by-products, but optimal bind and elution operation of these columns is complex. Ultrafiltration is typically applied in conjunction with diafiltration post-polishing chromatography in order to obtain suitable final product titers and excipient concentrations. This study presents a combination of dynamic models to probe batch polishing chromatography and ultrafiltration operating strategies achieving industrial specifications for recovery yield and mAb titer. A series of elution and filtration strategies are implemented, resulting in a total of 40 flowsheets explored. A steric mass action model with 7 pH-dependent parameters is employed to simulate scale-up polishing chromatography column behaviour. Moreover, a published gel layer ultrafiltration model based on Darcy’s law is implemented to purify the outlet of the polishing chromatography column. Strategies that are successful in achieving the target 90% recovery yield and 100 g L−1 concentration specifications are compared via a comprehensive analysis, to deduce the operational protocols which offer minimised salt consumption and pressure drop whilst respecting design criteria.

Contributions of Chinese hamster ovary cell derived extracellular vesicles and other cellular materials to hollow fiber filter fouling during perfusion manufacturing of monoclonal antibodies.

Hollow fiber filter fouling is a common issue plaguing perfusion production process for biologics therapeutics, but the nature of filter foulant has been elusive. Here we studied cell culture materials especially Chinese hamster ovary (CHO) cell-derived extracellular vesicles in perfusion process to determine their role in filter fouling. We found that the decrease of CHO-derived small extracellular vesicles (sEVs) with 50-200 nm in diameter in perfusion permeates always preceded the increase in transmembrane pressure (TMP) and subsequent decrease in product sieving, suggesting that sEVs might have been retained inside filters and contributed to filter fouling. Using scanning electron microscopy and helium ion microscopy, we found sEV-like structures in pores and on foulant patches of hollow fiber tangential flow filtration filter (HF-TFF) membranes. We also observed that the Day 28 TMP of perfusion culture correlated positively with the percentage of foulant patch areas. In addition, energy dispersive X-ray spectroscopy-based elemental mapping microscopy and spectroscopy analysis suggests that foulant patches had enriched cellular materials but not antifoam. Fluorescent staining results further indicate that these cellular materials could be DNA, proteins, and even adherent CHO cells. Lastly, in a small-scale HF-TFF model, addition of CHO-specific sEVs in CHO culture simulated filter fouling behaviors in a concentration-dependent manner. Based on these results, we proposed a mechanism of HF-TFF fouling, in which filter pore constriction by CHO sEVs is followed by cake formation of cellular materials on filter membrane.

Pioneering Just-in-Time (JIT) Strategy for Accelerating Raman Method Development and Implementation for Biologic Continuous Manufacturing.

Raman spectroscopy is a popular process analytical technology (PAT) tool that has been increasingly used to monitor and control the monoclonal antibody (mAb) manufacturing process. Although it allows the characterization of a variety of quality attributes by developing chemometric models, a large quantity of representative data is required, and hence, the model development process can be time-consuming. In recent years, the pharmaceutical industry has been expediting new drug development in order to achieve faster delivery of life-changing drugs to patients. The shortened development timelines have impacted the Raman application, as less time is allowed for data collection. To address this problem, an innovative Just-in-Time (JIT) strategy is proposed with the goal of reducing the time needed for Raman model development and ensuring its implementation. To demonstrate its capabilities, a proof-of-concept study was performed by applying the JIT strategy to a biologic continuous process for producing monoclonal antibody products. Raman spectroscopy and online two-dimensional liquid chromatography (2D-LC) were integrated as a PAT analyzer system. Raman models of antibody titer and aggregate percentage were calibrated by chemometric modeling in real-time. The models were also updated in real-time using new data collected during process monitoring. Initial Raman models with adequate performance were established using data collected from two lab-scale cell culture batches and subsequently updated using one scale-up batch. The JIT strategy is capable of accelerating Raman method development to monitor and guide the expedited biologics process development.

Evaluating end-to-end continuous antibody manufacture with column-free capture alternatives from economic, environmental, and robustness perspectives.

Process intensification efforts have renewed interest in the potential of end-to-end continuous manufacture with column-free capture alternatives. This article describes a decisional tool that encompasses mass balance and design equations, process economics, stochastic simulation and multi-criteria decision-making and enables the evaluation of different batch, and continuous flowsheets for monoclonal antibody (mAb) manufacture. The traditional batch process was compared with end-to-end continuous bioprocesses with either protein A capture or column-free capture employing aqueous two-phase extraction or precipitation from economic, environmental, and robustness perspectives. The cost of goods analysis predicted that continuous flowsheets could offer substantial cost savings (~20%-40%) over the batch process at low and medium annual commercial demands (100-500 kg); however, at tonnage demands they resulted in either comparable or higher costs. Comparing the continuous options, the continuous flowsheets with protein A or precipitation yielded similar COG/g values, while aqueous two-phase extraction presented higher costs. The analysis of overall process mass intensities accounting for water and consumables suggested that the continuous flowsheet with protein A would result in the lowest environmental burden. When the economic, environmental, and operational criteria were reconciled using multi-criteria decision-making analysis, the continuous protein A-based flowsheet was found to be the most favorable. A target analysis highlighted the need for process improvements in the following parameters to reduce the manufacturing costs of the continuous column-free capture options below that of protein A: the perfusion volumetric productivity, the harvested cell culture fluid percentage in column-free operations, the column-free step yields along with the implementation of buffer concentrates.

Tensorial approaches combining time series and batch data for the end-to-end batch manufacturing of monoclonal antibodies

The product quality for biopharmaceutical production processes is characterized in terms of critical quality attributes. Some quality attributes, however, cannot be easily measured in a timely fashion to support effective intervention and mitigation, particularly for assays that are time-consuming and/or late in the purification process. This article describes the application of predictive modeling techniques to industrial end-to-end biomanufacturing datasets for two monoclonal antibodies to predict critical quality attributes. Methods are proposed for combining time series and batch data that significantly improve the accuracy of the model predictions. These tools are able to take batch-to-batch correlations into account to construct more accurate predictive models from biomanufacturing datasets.

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.

Identification and characterization of CHO host-cell proteins in monoclonal antibody bioprocessing.

Host-cell proteins (HCPs)are the foremost class of process-related impurities to be controlled and removed in downstream processing steps in monoclonal antibody (mAb) manufacturing. However, some HCPs may evade clearance in multiple purification steps and reach the final drug product, potentially threatening drug stability and patient safety. This study extends prior work on HCP characterization and persistence in mAb process streams by using mass spectrometry (MS)-based methods to track HCPs through downstream processing steps for seven mAbs that were generated by five different cell lines. The results show considerable variability in HCP identities in the processing steps but extensive commonality in the identities and quantities of the most abundant HCPs in the harvests for different processes. Analysis of HCP abundance in the harvests shows a likely relationship between abundance and the reproducibility of quantification measurements and suggests that some groups of HCPs may hinder the characterization. Quantitative monitoring of HCPs persisting through purification steps coupled with the findings from the harvest analysis suggest that multiple factors, including HCP abundance and mAb-HCPinteractions, can contribute to the persistence of individual HCPs and the identification of groups of common, persistent HCPs in mAb manufacturing.

Utilizing targeted integration CHO pools to potentially accelerate the GMP manufacturing of monoclonal and bispecific antibodies.

Monoclonal antibodies (mAbs) are effective therapeutic agents against many acute infectious diseases including COVID-19, Ebola, RSV, Clostridium difficile, and Anthrax. mAbs can therefore help combat a future pandemic. Unfortunately, mAb development typically takes years, limiting its potential to save lives during a pandemic. Therefore "pandemic mAb" timelines need to be shortened. One acceleration tool is "deferred cloning" and leverages new Chinese hamster ovary (CHO) technology based on targeted gene integration (TI). CHO pools, instead of CHO clones, can be used for Phase I/II clinical material production. A final CHO clone (producing the mAb with a similar product quality profile and preferably with a higher titer) can then be used for Phase III trials and commercial manufacturing. This substitution reduces timelines by ~3 months. We evaluated our novel CHO TI platform to enable deferred cloning. We created four unique CHO pools expressing three unique mAbs (mAb1, mAb2, and mAb3), and a bispecific mAb (BsAb1). We then performed single-cell cloning for mAb1 and mAb2, identifying three high-expressing clones from each pool. CHO pools and clones were inoculated side-by-side in ambr15 bioreactors. CHO pools yielded mAb titers as high as 10.4 g/L (mAb3) and 7.1 g/L (BsAb1). Subcloning yielded CHO clones expressing higher titers relative to the CHO pools while yielding similar product quality profiles. Finally, we showed that CHO TI pools were stable by performing a 3-month cell aging study. In summary, our CHO TI platform can increase the speed to clinic for a future "pandemic mAb."

Smart process analytics for the end-to-end batch manufacturing of monoclonal antibodies

For many modern biopharmaceutical processes, manufacturers develop data-driven models using data analytics/machine learning (DA/ML) methods. The challenge is how to select the best methods for a specific dataset to construct the most accurate and reliable model. This article describes the application of smart process data analytics software to industrial end-to-end biomanufacturing datasets for monoclonal antibody production to automate the determination of the best DA/ML tools for model construction and process understanding. The application demonstrates that smart process data analytics software captures product- and process-specific characteristics for two different monoclonal antibody productions. This study provides tools that can be widely applied to biomanufacturing processes for root cause analysis, prediction, and control.

Biomimetic affinity chromatography for antibody purification: Host cell protein binding and impurity removal

Peptide affinity chromatography has received increasing attention as an alternative to protein A chromatography in antibody purification. However, its lower selectivity than protein A chromatography has impeded its success in practical applications. In particular, efficient removal of contaminants, including host cell proteins (HCPs) and DNA, is a great challenge for peptide affinity chromatography in monoclonal antibody (mAb) manufacturing. In this work, a biomimetic peptide ligand (bPL), FYWHCLDE, was coupled onto Sepharose 6 Fast Flow (SepFF) to synthesize a peptide affinity gel, SepFF-bPL, for the investigation of the binding mechanism of HCP as well as the feasibility of antibody capture. The results showed that the SepFF-bPL column exhibited effective removal of mAb aggregates as well as mAb capture from feedstocks of various origins, whereas poor removal of HCP and DNA was found. Mechanistic studies of HCP binding indicated that electrostatic interactions dominated HCP binding on the SepFF-bPL gel and that ionic conductivity had a significant influence on HCP binding at low salt concentrations. Thus, combined chromatin extraction and anion exchange adsorption were introduced prior to SepFF-bPL chromatography for initial contaminant removal to reduce mAb aggregation induced by HCP and the loading burden of contaminants in SepFF-bPL chromatography. A proof-of-concept study of the purification train demonstrated a high recovery of mAb (68.7%) and low levels of HCP (23 ppm) and DNA (below the limit of detection) in the final product, which were acceptable for the mandatory requirements in clinical applications. This research provided a deep understanding of HCP binding on the peptide affinity column and led to the development of an effective purification train.

Efficient optimization of time-varying inputs in a fed-batch cell culture process using design of dynamic experiments.

In cell culture process development, we rely largely on an iterative, one-factor-at-a-time procedure based on experiments that explore a limited process space. Design of experiments (DoE) addresses this issue by allowing us to analyze the effects of process inputs on process responses systematically and efficiently. However, DoE cannot be applied directly to study time-varying process inputs unless an impractically large number of bioreactors is used. Here, we adopt the methodology of design of dynamic experiments (DoDE) and incorporate dynamic feeding profiles efficiently in late-stage process development of the manufacture of therapeutic monoclonal antibodies. We found that, for the specific cell line used in this article, (1) not only can we estimate the effect of nutrient feed amount on various product attributes, but we can also estimate the effect, develop a statistical model, and use the model to optimize the slope of time-trended feed rates; (2) in addition to the slope, higher-order dynamic characteristics of time-trended feed rates can be incorporated in the design but do not have any significant effect on the responses we measured. Based on the DoDE data, we developed a statistical model and used the model to optimize several process conditions. Our effort resulted in a tangible improvement in productivity-compared with the baseline process without dynamic feeding, this optimized process in a 200-L batch achieved a 27% increase in titer and > 92% viability. We anticipate our application of DoDE to be a starting point for more efficient workflows to optimize dynamic process conditions in process development.

Trace metal optimization in CHO cell culture through statistical design of experiments.

A majority of the biotherapeutics industry today relies on the manufacturing of monoclonal antibodies from Chinese hamster ovary (CHO) cells, yet challenges remain with maintaining consistent product quality from high-producing cell lines. Previous studies report the impact of individual trace metal supplemental on CHO cells, and thus, the combinatorial effects of these metals could be leveraged to improve bioprocesses further. A three-level factorial experimental design was performed in fed-batch shake flasks to evaluate the impact of time wise addition of individual or combined trace metals (zinc and copper) on CHO cell culture performance. Correlations among each factor (experimental parameters) and response variables (changes in cell culture performance) were examined based on their significance and goodness of fit to a partial least square's regression model. The model indicated that zinc concentration and time of addition counter-influence peak viable cell density and antibody production. Meanwhile, early copper supplementation influenced late-stage ROS activity in a dose-dependent manner likely by alleviating cellular oxidative stress. Regression coefficients indicated that combined metal addition had less significant impact on titer and specific productivity compared to zinc addition alone, although titer increased the most under combined metal addition. Glycan analysis showed that combined metal addition reduced galactosylation to a greater extent than single metals when supplemented during the early growth phase. A validation experiment was performed to confirm the validity of the regression model by testing an optimized setpoint of metal supplement time and concentration to improve protein productivity.

Repressing expression of difficult-to-express recombinant proteins during the selection process increases productivity of CHO stable pools.

More than half of licensed therapeutic recombinant proteins (r-proteins) are manufactured using constitutively-expressing, stably-transfected Chinese hamster ovary (CHO) clones. While constitutive CHO expression systems have proven their efficacy for the manufacturing of monoclonal antibodies, many next-generation therapeutics such as cytokines and bispecific antibodies as well as biological targets such as ectodomains of transmembrane receptors remain intrinsically challenging to produce. Herein, we exploited a cumate-inducible CHO platform allowing reduced expression of various classes of r-proteins during selection of stable pools. Following stable pool generation, fed-batch productions showed that pools generated without cumate (OFF-pools) were significantly more productive than pools selected in the presence of cumate (ON-pools) for 8out of the 10r-proteins tested, including cytokines, G-protein coupled receptors (GPCRs), the HVEM membrane receptor ectodomain, the multifunctional protein High Mobility Group protein B1 (HMGB1), as well as monoclonal and bispecific T-cell engager antibodies. We showed that OFF-pools contain a significantly larger proportion of cells producing high levels of r-proteins and that these cells tend to proliferate faster when expression is turned off, suggesting that r-protein overexpression imposes a metabolic burden on the cells. Cell viability was lower and pool recovery was delayed during selection of ON-pools (mimicking constitutive expression), suggesting that high producers were likely lost or overgrown by faster-growing, low-producing cells. We also observed a correlation between the expression levels of the GPCRs with Binding immunoglobulin Protein, an endoplasmic reticulum (ER) stress marker. Taken together, these data suggest that using an inducible system to minimize r-protein expression during stable CHO pool selection reduces cellular stresses, including ER stress and metabolic burden, leading to pools with greater frequency of high-expressing cells, resulting in improved volumetric productivity.

Engineering protein A ligands to mitigate antibody loss during high-pH washes in protein A chromatography

Protein A chromatography is a workhorse in monoclonal antibody (mAb) manufacture since it provides effective separation of mAbs from impurities such as host-cell proteins (HCPs) in a single capture step. HCP clearance can be aided by the inclusion of a wash step prior to low-pH elution. Although high-pH washes can be effective in removing additional HCPs from the loaded column, they may also contribute to a reduced mAb yield. In this work we show that this yield loss is reflected in a pH-dependent variation of the equilibrium binding capacity of the protein A resin, which is also observed for the capacity of the Fc fragments alone and therefore not a result of steric interactions involving the Fab fragments in the intact mAbs. We therefore hypothesized that the high-pH wash loss was due to protonation or deprotonation of ionizable residues on the protein A ligand. To evaluate this, we applied a rational protein engineering approach to the Z domain (the Fc-binding component of most commercial protein A ligands) and expressed engineered mutants in E. coli. Biolayer interferometry and affinity chromatography experiments showed that some of the Z domain mutants were able to mitigate wash loss at high pH while maintaining similar binding characteristics at neutral pH. These experiments enabled elucidation of the roles of specific interactions in the Z domain - Fc complex, but more importantly offer a route to ameliorating the disadvantages of high-pH washes in protein A chromatography.

Host cell protein quantification workflow using optimized standards combined with data-independent acquisition mass spectrometry

Monitoring of host cell proteins (HCPs) during the manufacturing of monoclonal antibodies (mAb) has become a critical requirement to provide effective and safe drug products. Enzyme-linked immunosorbent assays are still the gold standard methods for the quantification of protein impurities. However, this technique has several limitations and does, among others, not enable the precise identification of proteins. In this context, mass spectrometry (MS) became an alternative and orthogonal method that delivers qualitative and quantitative information on all identified HCPs. However, in order to be routinely implemented in biopharmaceutical companies, liquid chromatography-MS based methods still need to be standardized to provide highest sensitivity and robust and accurate quantification. Here, we present a promising MS-based analytical workflow coupling the use of an innovative quantification standard, the HCP Profiler solution, with a spectral library-based data-independent acquisition (DIA) method and strict data validation criteria. The performances of the HCP Profiler solution were compared to more conventional standard protein spikes and the DIA approach was benchmarked against a classical data-dependent acquisition on a series of samples produced at various stages of the manufacturing process. While we also explored spectral library-free DIA interpretation, the spectral library-based approach still showed highest accuracy and reproducibility (coefficients of variation < 10%) with a sensitivity down to the sub-ng/mg mAb level. Thus, this workflow is today mature to be used as a robust and straightforward method to support mAb manufacturing process developments and drug products quality control.

Systematic analytical workflow for characterisation and identification of partially reduced species in monoclonal antibody manufacturing

Fragmentation is a major degradation pathway ubiquitous to all therapeutic monoclonal antibody (mAb) and therefore, monitored throughout the manufacturing process. Here, we describe a three-step approach to 1) detect, 2) confirm and 3) characterize partially reduced fragment species in an immunoglobulin G1 (IgG1) mAb with prolonged hold time of harvested cell culture fluid (HCCF). Microchip capillary electrophoresis (MCE) and high-performance size exclusion chromatography (HPSEC) were used as fast and efficient screening methods to detect fragmentation. HPSEC was found to be underestimating fragmentation levels. To confirm and characterize the fragments, capillary electrophoresis-sodium dodecyl sulphate (CE-SDS) was employed. Interestingly, the absence of fragments in the reduced CE-SDS analysis suggested partial reduction of disulphide bonds contributing to fragmentation in this mAb lot. This was further confirmed using reverse phase high performance liquid chromatography (RP-HPLC) coupled with mass spectrometry, which established the presence of heavy-heavy-light (HHL), heavy-heavy (HH), light-light dimer (LL), light chain (LC) and half antibody (HL) fragments with good mass accuracy. In this study, we demonstrated a readily applicable systematic strategy to support process development and investigate anomalous events in manufacturing. An additional highlight of this work is the data-driven comprehensive comparison of modern and conventional analytical techniques for fragment analysis.

Continuous manufacturing of monoclonal antibodies: Dynamic control of multiple integrated polishing chromatography steps using BioSMB

We propose a strategy for automation and control of multi-step polishing chromatography in integrated continuous manufacturing of monoclonal antibodies. The strategy is demonstrated for a multi-step polishing process consisting of cation exchange chromatography in bind-and-elute mode followed by mixed-mode chromatography in flowthrough mode. A BioSMB system with a customized Python control layer is used for automation and scheduling of both the chromatography steps. Further, the BioSMB valve manifold is leveraged for in-line conditioning between the two steps, as tight control of pH and conductivity is essential when operating with multimodal resins because even slight fluctuations in load conditions adversely affect the chromatography performance. The pH and conductivity of the load to the multimodal chromatography columns is consistent, despite the elution gradient of the preceding cation exchange chromatography step. Inputs from the BioSMB pH and conductivity sensors are used for real-time control of the 7 pumps and 240 valves to achieve in-line conditioning inside the BioSMB manifold in a fully automated manner. This is confirmed by showcasing different elution strategies in cation exchange chromatography, including linear gradient, step gradient and process deviations like tubing leakage. In all the above cases, the model was able to maintain the pH and conductivity of multimodal chromatography load within the range of 6 ± 0.1 pH and 7 ± 0.3 mS/cm conductivity. The strategy eliminates the need for using multiple BioSMB units or integrating external pumps, valves, mixers, surge tanks, or sensors between the two steps as is currently the standard approach, thus offering a simple and robust structure for integrating multiple polishing chromatography steps in continuous downstream monoclonal antibody purification trains.