Design space and robustness analysis of batch and counter-current frontal chromatography processes for the removal of antibody aggregates

Hydrophobic interaction chromatography in continuous flow-through mode for product-related variant removal

Product-related impurities are challenging to remove during monoclonal antibody (mAb) purification process due to molecular similarity. Frontal chromatography on hydrophobic interaction resins has demonstrated its capability to effectively remove such impurities. However, process improvements geared towards purity level comes as a trade-off with the yield loss. In this work, we present a hydrophobic interaction chromatography process using multicolumn continuous chromatography (MCC) concept and frontal analysis to remove a high prevalence product related impurity. This design uses a two-column continuous system where the two columns are directly connected during product chase step to capture product wash loss without any in-process adjustment. This polish MCC operation resulted in a 10 % increase in yield while maintaining 99 % purity, despite the presence of 20 % product-related impurities in the feed material. One challenge associated with polish MCC design is that the accumulation of the impurities renders a non-steady state recycling. To surmount this issue and ensure a robust process, a mechanistic model was developed and validated to predict multicomponent breakthrough. This model was capable to predict multiple cycle behavior and accounts for increased impurity concentration. Assisted by the model, the optimized operation parameters and conditions can be determined to account for variation in product load quality. The simulated results demonstrate an effective doubling of productivity compared to conventional batch chromatography.

Process development and characterization for integrated continuous bioprocesses-Highlights from N-mAb

The N-mAb case study was produced by the National Institute for Innovation in Manufacturing Biopharmaceuticals (NIIMBL) to support teaching and learning for both industry and to accelerate adoption of advanced manufacturing process technologies such as integrated continuous bioprocesses (ICB) for mAbs. Similar to the A-mAb case study, N-mAb presents the evolution of an integrated control strategy, from early clinical through process validation and commercial manufacturing with a focus on elements that are unique to integrated continuous bioprocesses. This publication presents a summary of the process design and characterization chapters to allow a greater focus on the unique elements relevant to that phase of development.

Computer-aided design space identification for screening of protein A affinity chromatography resins

The rapidly growing market of monoclonal antibodies (mAbs) within the biopharmaceutical industry has incentivised numerous works on the design of more efficient production processes. Protein A affinity chromatography is regarded as one of the best processes for the capture of mAbs. Although the screening of Protein A resins has been previously examined, process flexibility has not been considered to date. Examining performance alongside flexibility is crucial for the design of processes that can handle disturbances arising from the feed stream. In this work, we present a model-based approach for the identification of design spaces, enhanced by machine learning. We demonstrate its capabilities on the design of a Protein A chromatography unit, screening five industrially relevant resins. The computational results favourably compare to experimental data and a resin performance comparison is presented. An improvement on the computational time by a factor of 300,000 is achieved using the machine learning aided methodology. This allowed for the identification of 5,120 different design spaces in only 19 h.

Model-assisted process development, characterization and design of continuous chromatography for antibody separation

Continuous manufacturing in monoclonal antibody production has generated increased interest due to its consistent quality, high productivity, high equipment utilization, and low cost. One of the major challenges in realizing continuous biological manufacturing lies in implementing continuous chromatography. Given the complex operation mode and various operation parameters, it is challenging to develop a continuous process. Due to the process parameters being mainly determined by the breakthrough curves and elution behaviors, chromatographic modeling has gradually been used to assist in process development and characterization. Model-assisted approaches could realize multi-parameter interaction investigation and multi-objective optimization by integrating continuous process models. These approaches could reduce time and resource consumption while achieving a comprehensive and systematic understanding of the process. This paper reviews the application of modeling tools in continuous chromatography process development, characterization and design. Model-assisted process development approaches for continuous capture and polishing steps are introduced and summarized. The challenges and potential of model-assisted process characterization are discussed, emphasizing the need for further research on the design space determination strategy and parameter robustness analysis method. Additionally, some model applications for process design were highlighted to promote the establishment of the process optimization and process simulation platform.

Mathematical modeling and process analytical technology for continuous chromatography of biopharmaceutical products

Chromatography is a widely used separation method that is inherently a batch operation. However, the demand for higher productivity and lower cost and labor has prompted industries such as the petrochemical and food industries to transition from batch to continuous chromatography. Growing market competition in the biopharmaceutical industry and the rise of novel biotherapeutics modalities have brought about promising continuous chromatography methods as well as next-generation tools to enable continuous operation in bioprocessing. While these continuous chromatography methods outperform their batch counterpart, their implementation presents challenges due to their greater complexity. This review discusses two key technologies that are essential for the implementation of continuous chromatography: mathematical modeling and novel process analytical technologies. Mechanistic-based models not only aid in process development and optimization but also allow for greater process control and automation.

Design and economic investigation of a Multicolumn Countercurrent Solvent Gradient Purification unit for the separation of an industrially relevant PEGylated protein

Conjugation of biopharmaceuticals to polyethylene glycol chains, known as PEGylation, is nowadays an efficient and widely exploited strategy to improve critical properties of the active molecule, including stability, biodistribution profile, and reduced clearance. A crucial step in the manufacturing of PEGylated drugs is the purification. The reference process in industrial settings is single-column chromatography, which can meet the stringent purity requisites only at the expenses of poor product recoveries. A valuable solution to this trade-off is the Multicolumn Countercurrent Solvent Gradient Purification (MCSGP), which allows the internal and automated recycling of product-containing side fractions that are typically discarded in the batch processes. In this study, an ad hoc design procedure was applied to the single-column batch purification of an industrially relevant PEGylated protein, with the aim of defining optimal collection window, elution duration and elution buffer ionic strength to be then transferred to the MCSGP. This significantly alleviates the design of the continuous operation, subjected to manifold process parameters. The MCSGP designed by directly transferring the optimal parameters allowed to improve the yield and productivity by 8.2% and 17.8%, respectively, when compared to the corresponding optimized batch process, ensuring a purity specification of 98.0%. Once the efficacy of MCSGP was demonstrated, a detailed analysis of its cost of goods was performed and compared to the case of single-column purification. To the best of our knowledge, this is the first example of a detailed economic investigation of the MCSGP across different manufacturing scenarios and process cadences of industrial relevance, which demonstrated not only the viability of this continuous technology but also its flexibility.

The separation regularity of the three-phase solvent system of counter-current chromatography based on polarity parameter modeling

The three-phase solvent system of counter-current chromatography can separate compounds with a wide range of polarity, but there is no study of its separation regularity. Therefore, in this work, the separation regularity of the three-phase solvent system was initially investigated from the perspective of solvent polarities and compound polarities. The standard compounds covering a wide polarity range were selected, and three-phase solvent systems, n-hexane/methyl acetate/acetonitrile/water, and n-hexane/methyl tert-butyl ether/acetonitrile/water were used for modeling. The results showed that in the three-phase solvent system, the partition coefficient for the middle and lower phases (lgK_M/L) increased with increasing logP values in three intervals logP < 0, 0 < logP < 4, and logP > 4. In addition, the partition coefficient for the upper and middle phases (lgK_U/M) between the upper and middle phases of the small polarity compounds increases with increasing logP values. LogP vs lgK_M/L of 7 solvent systems were employed for the smoothing spline fit through a predictive model design of the curve fitting toolbox in MATLAB software, and good results were achieved. LogP versus lgK_M/L for n-hexane/methyl tert-butyl ether/acetonitrile/water solvent systems were used for the second-order power fit, and satisfactory results were obtained. The relationship between polarity parameters and separation case parameters was explored using a heat map approach. The separation regularity of the three-phase solvent system was preliminarily investigated. This regularity study gives hope of assistance to the chemists studying three-phase solvents and counter-current chromatography.

Continuous countercurrent chromatographic twin-column purification of oligonucleotides: the role of the displacement effect

Oligonucleotides (ONs) are breaking through in the biopharmaceutical industry as a promising class of biotherapeutics. The main success of these molecules is due to their peculiar way of acting in the cellular process, regulating the gene expression and hence influencing the protein synthesis at a pre-translational level. Although the Food and Drug Administration (FDA) already approved a few ON-based therapeutics, their production cost strongly limits large scale manufacturing: a situation that can be alleviated through process intensification. In this work, we address this problem by developing an efficient and continuous chromatographic purification process for ONs. In particular, we considered the chromatographic purification of a ON crude prepared by chemical synthesis using anion exchange resins. We demonstrate that in this system the competitive adsorption of the various species on the same sites of the resin leads to the displacement of the more weakly adsorbing species by the more strongly adsorbing ones. This phenomenon affects the behavior of the chromatographic units and it has been investigated in detail. Then, we developed a continuous countercurrent solvent gradient purification (MCSGP) process, which can significantly improve the productivity and buffer consumption compared to a classical single-column, batch chromatographic process. This article is protected by copyright. All rights reserved.

A novel framework of surrogate-based feasibility analysis for establishing design space of twin-column continuous chromatography

Multi-column periodic counter-current chromatography (PCC) has attracted wide attention for the primary capture for the purpose of achieving continuous biomanufacturing. Consequently, determining the design space of the continuous capture process is very important to facilitate process understanding and improving product quality. In this work, we proposed a novel approach to identify the design space of continuous chromatography to balance the computational complexity and model predictions. Specifically, surrogate-based feasibility analysis with adaptive sampling is applied to establish the design space of twin-column CaptureSMB process. The surrogate model is constructed based on the developed mechanistic model for the identification of the design space. The effects of process variables (including interconnected loading time, interconnected flowrate, and batch flowrate) on the design space are comprehensively examined based on an active set strategy. Besides, essential factors like recovery-regeneration time and constraints of column performance parameters (yield, productivity, and capacity utilization) are thoroughly investigated. The impact of design variables such as column length is also studied.

Analysis and optimal design of batch and two-column continuous chromatographic frontal processes for monoclonal antibody purification

The increasing demand for efficient and robust processes in the purification of monoclonal antibodies (mAbs) has recently brought frontal chromatography to the forefront. Applied during the polishing step, it enables the removal of high molecular weight aggregates from the target product, achieving high purities. Typically, this process is operated in batch using a single column, which makes it intrinsically subjected to a purity-yield tradeoff. This means that high purities can only be achieved at the cost of lowering the product yield and vice versa. Recently, a two-column continuous implementation of frontal chromatography, referred to as Flow2, was developed. Despite being able of alleviating the purity-yield tradeoff typical of batch operations, the increase in the number of process parameters complicates its optimal design, with the risk of not exploiting its full potential. In this study, we developed an ad hoc design procedure (DP) suitable for the optimization of both batch frontal chromatography and Flow2 in terms of purity, yield, and productivity. This procedure provided similar results as a multiobjective optimization based on genetic algorithm but with lower computational effort. Then, batch and Flow2 operated at their optimal conditions were compared. Besides showing a more favorable Pareto front of yield and productivity at a specified purity, the Flow2 process demonstrated improved robustness compared to the batch process with respect to modifications in the loading linear velocity, washing buffer ionic strength and loading time, thus providing an appealing operation for integrated processes.

PAT for Continuous Chromatography Integrated into Continuous Manufacturing of Biologics towards Autonomous Operation

This study proposes a reliable inline PAT concept for the simultaneous monitoring of different product components after chromatography. The feed for purification consisted of four main components, IgG monomer, dimer, and two lower molecular weight components of 4.4 kDa and 1 kDa molecular weight. The proposed measurement setup consists of a UV–VIS diode-array detector and a fluorescence detector. Applying this system, a R2 of 0.93 for the target component, a R2 of 0.67 for the dimer, a R2 of 0.91 for the first side component and a R2 of 0.93 for the second side component is achieved. Root mean square error for IgG monomer was 0.027 g/L, for dimer 0.0047 g/L, for side component 1 0.016 g/L and for the side component 2 0.014 g/L. The proposed measurement concept tracked component concentration reliably down to 0.05 g/L. Zero-point fluctuations were kept within a standard deviation of 0.018 g/L for samples with no IgG concentration but with side components present, allowing a reliable detection of the target component. The main reason inline concentration measurements have not been established yet, is the false-positive measurement of target components when side components are present. This problem was eliminated using the combination of fluorescence and UV–VIS data for the test system. The use of this measurement system is simulated for the test system, allowing an automatic fraction cut at 0.05 g/L. In this simulation a consistent yield of >99% was achieved. Process disturbances for processed feed volume, feed purity and feed IgG concentration can be compensated with this setup. Compared to a timed process control, yield can be increased by up to 12.5%, if unexpected process disturbances occur.

Developments and opportunities in continuous biopharmaceutical manufacturing

Today's biologics manufacturing practices incur high costs to the drug makers, which can contribute to high prices for patients. Timely investment in the development and implementation of continuous biomanufacturing can increase the production of consistent-quality drugs at a lower cost and a faster pace, to meet growing demand. Efficient use of equipment, manufacturing footprint, and labor also offer the potential to improve drug accessibility. Although technological efforts enabling continuous biomanufacturing have commenced, challenges remain in the integration, monitoring, and control of traditionally segmented unit operations. Here, we discuss recent developments supporting the implementation of continuous biomanufacturing, along with their benefits.

Model-assisted approaches for continuous chromatography: Current situation and challenges

Continuous bioprocessing is a promising trend in biopharmaceutical production, and multi-column continuous chromatography shows advantages of high productivity, high resin capacity utilization, small footprint, low buffer consumption and less waste. Due to the complexity and dynamic nature of continuous processing, traditional experiment-based approaches are often time-consuming and inefficient. In this review, model-assisted approaches were focused and their applications in continuous chromatography process development, validation and control were discussed. Chromatographic models are useful in describing particular process performances of continuous capture and polishing with multi-column chromatography. Model-assisted tools showed powerful ability in evaluating multiple operating parameters and identifying optimal points over the entire design space. The residence time distribution models, model-assisted process analytical technologies and model-predictive control strategies were also developed to reveal the propagation of disturbances, enhance real time monitor and achieve adaptive control to match the transient disturbances and deviations of continuous processes. Moreover, artificial neural networks and machine learning concepts were integrated into modeling approaches to improve data treatment. In general, further development in research and applications of model-assisted approaches for continuous chromatography are needed urgently to support the continuous manufacturing.

Analytical, Preparative, and Industrial-Scale Separation of Substances by Methods of Countercurrent Liquid-Liquid Chromatography

Countercurrent liquid-liquid chromatographic techniques (CCC), similar to solvent extraction, are based on the different distribution of compounds between two immiscible liquids and have been most widely used in natural product separations. Due to its high load capacity, low solvent consumption, the diversity of separation methods, and easy scale-up, CCC provides an attractive tool to obtain pure compounds in the analytical, preparative, and industrial-scale separations. This review focuses on the steady-state and non-steady-state CCC separations ranging from conventional CCC to more novel methods such as different modifications of dual mode, closed-loop recycling, and closed-loop recycling dual modes. The design and modeling of various embodiments of CCC separation processes have been described.

Displacement to separate host-cell proteins and aggregates in cation-exchange chromatography of monoclonal antibodies

An efficient and consistent method of monoclonal antibody (mAb) purification can improve process productivity and product consistency. Although protein A chromatography removes most host-cell proteins (HCPs), mAb aggregates and the remaining HCPs are challenging to remove in a typical bind-and-elute cation-exchange chromatography (CEX) polishing step. A variant of the bind-and-elute mode is the displacement mode, which allows strongly binding impurities to be preferentially retained and significantly improves resin utilization. Improved resin utilization renders displacement chromatography particularly suitable in continuous chromatography operations. In this study we demonstrate and exploit sample displacement between a mAb and impurities present at low prevalence (0.002%-1.4%) using different multicolumn designs and recycling. Aggregate displacement depends on the residence time, sample concentration, and solution environment, the latter by enhancing the differences between the binding affinities of the product and the impurities. Displacement among the mAb and low-prevalence HCPs resulted in an effectively bimodal-like distribution of HCPs along the length of a multi-column system, with the mAb separating the relatively more basic group of HCPs from those that are more acidic. Our findings demonstrate that displacement of low-prevalence impurities along multiple CEX columns allows for selective separation of mAb aggregates and HCPs that persist through protein A chromatography.