Comparison of batch and continuous multi-column protein A capture processes by optimal design

Integrated continuous downstream process of monoclonal antibody developed by converting the batch platform process based on the process characterization

A continuous downstream process of monoclonal antibody was developed based on the process characterization. Periodic-counter current chromatography (PCCC) with two protein A columns was used for the capture step. For low pH virus inactivation (VI), a batch reactor was employed, which can work as a surge (buffer) tank. Flow-through chromatography (FTC) with two connected columns of different separation modes (anion-mixed mode and cation exchange) was designed as a polish step. After 24 h PCCC run, the collected pool was processed for VI. After adjusting pH and electric conductivity, the solution was fed to the two connected FTC columns for 24 h. Virus filter was also connected to the exit of the connected-column. PCCC and FTC were run in parallel. Six runs of different feed rates (0.5-10 L/day) and feed concentrations (1-3.2 g/L) were performed with protein A columns of 1-5 mL and FTC columns of 3-10 mL. The largest run (feed rate 10 L/day, feed concentration 2 g/L) was carried out at a GMP facility with 15 mL protein A columns and 100 mL FTC columns. Good recovery and purity values were obtained for all runs. The process was found to be flexible and stable for feed fluctuations. Only three surge or pool tanks were needed in addition to the final product pool tank.

Methodology for fast development of digital solutions in integrated continuous downstream processing

The methodology for production of biologics is going through a paradigm shift from batch-wise operation to continuous production. Lot of efforts are focused on integration, intensification, and continuous operation for decreased foot-print, material, equipment, and increased productivity and product quality. These integrated continuous processes with on-line analytics become complex processes, which requires automation, monitoring, and control of the operation, even unmanned or remote, which means bioprocesses with high level of automation or even autonomous capabilities. The development of these digital solutions becomes an important part of the process development and needs to be assessed early in the development chain. This work discusses a platform that allows fast development, advanced studies, and validation of digital solutions for integrated continuous downstream processes. It uses an open, flexible, and extendable real-time supervisory controller, called Orbit, developed in Python. Orbit makes it possible to communicate with a set of different physical setups and on the same time perform real-time execution. Integrated continuous processing often implies parallel operation of several setups and network of Orbit controllers makes it possible to synchronize complex process system. Data handling, storage, and analysis are important properties for handling heterogeneous and asynchronous data generated in complex downstream systems. Digital twin applications, such as advanced model-based and plant-wide monitoring and control, are exemplified using computational extensions in Orbit, exploiting data and models. Examples of novel digital solutions in integrated downstream processes are automatic operation parameter optimization, Kalman filter monitoring, and model-based batch-to-batch control.

A modular and multi-functional purification strategy that enables a common framework for manufacturing scale integrated and continuous biomanufacturing

Biopharmaceutical manufacture is transitioning from batch to integrated and continuous biomanufacturing (ICB). The common framework for most ICB, potentially enables a global biomanufacturing ecosystem utilizing modular and multi-function manufacturing equipment. Integrating unit operation hardware and software from multiple suppliers, complex supply chains enabled by multiple customized single-use flow paths, and large volume buffer production/storage make this ICB vision difficult to achieve with commercially available manufacturing equipment. Thus, we developed SymphonX™, a downstream processing skid with advanced buffer management capabilities, a single disposable generic flow path design that provides plug-and-play flexibility across all downstream unit operations and a single interface to reduce operational risk. Designed for multi-product and multi-process cGMP facilities, SymphonX™ can perform stand-alone batch processing or ICB. This study utilized an Apollo™ X CHO-DG44 mAb-expressing cell line in a steady-state perfusion bioreactor, harvesting product continuously with a cell retention device and connected SymphonX™ purification skids. The downstream process used the same chemistry (resins, buffer composition, membrane composition) as our historical batch processing platform, with SymphonX™ in-line conditioning and buffer concentrates. We used surge vessels between unit operations, single-column chromatography (protein A, cation and anion exchange) and two-tank batch virus inactivation. After the first polishing step (cation exchange), we continuously pooled product for 6 days. These 6 day pools were processed in batch-mode from anion exchange to bulk drug substance. This manufacturing scale proof-of-concept ICB produced 0.54 kg/day of drug substance with consistent product quality attributes and demonstrated successful bioburden control for unit-operations undergoing continuous operation.

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.

Scalable dual column cation exchange affinity chromatography based platform process for recombinant protein purification

A novel tandem affinity tag is presented that enables the use of cation exchange resins for initial affinity purification, followed by an additional column step for enhanced purity and affinity tag self-removal. In this method, the highly charged heparin-binding tag binds strongly and selectively to either a strong or weak cation exchange resin based on electrostatic interactions, effectively acting as an initial affinity tag. Combining the heparin-binding tag (HB-tag) with the self-removing iCapTag™ provides a means for removing both tags in a subsequent self-cleaving step. The result is a convenient platform for the purification of diverse tagless proteins with a range of isoelectric points and molecular weights. In this work, we demonstrate a dual column process in which the tagged protein of interest is first captured from an E. coli cell lysate using a cation exchange column via a fused heparin-binding affinity tag. The partially purified protein is then diluted and loaded onto an iCapTag™ split-intein column, washed, and then incubated overnight to release the tagless target protein from the bound tag. Case studies are provided for enhanced green fluorescent protein (eGFP), beta galactosidase (βgal), maltose binding protein (MBP) and beta lactamase (βlac), where overall purity and host cell DNA clearance is provided. Overall, the proposed dual column process is shown to be a scalable platform technology capable of accessing both the high dynamic binding capacity of ion exchange resins and the high selectivity of affinity tags for the purification of recombinant proteins.

Reviewing the process intensification landscape through the introduction of a novel, multitiered classification for downstream processing

A demand for process intensification in biomanufacturing has increased over the past decade due to the ever-expanding market for biopharmaceuticals. This is largely driven by factors such as a surge in biosimilars as patents expire, an aging population, and a rise in chronic diseases. With these market demands, pressure upon biomanufacturers to produce quality products with rapid turnaround escalates proportionally. Process intensification in biomanufacturing has been well received and accepted across industry based on the demonstration of its benefits of improved productivity and efficiency, while also reducing the cost of goods. However, while these benefits have been shown empirically, the challenges of adopting process intensification into industry remain, from smaller independent start-up to big pharma. Traditionally, moving from batch to a process intensification scheme has been viewed as an "all or nothing" approach involving continuous bioprocessing, in which the factors of complexity and significant capital costs hinder its adoption. In addition, the literature is crowded with a variety of terms used to describe process intensification (continuous, periodic counter-current, connected, intensified, steady-state, etc.). Often, these terms are used inappropriately or as synonyms, which generates confusion in the field. Through a detailed review of current state-of-the-art systems, consumables, and process intensification case studies, we herein propose a defined approach in the implementation of downstream process intensification through a standardized nomenclature and viewing it as distinct independent levels. These can function separately as intensified single-unit operations or be built upon by integration with other process steps allowing for simple, incremental, cost-effective implementation of process intensification in the manufacturing of biopharmaceuticals.

Advanced control strategies for continuous capture of monoclonal antibodies based upon biolayer interferometry

The semi and fully continuous production of monoclonal antibodies (mAbs) has been gaining traction as a lower cost, and efficient production of mAbs to broaden patient access. To be truly flexible and adaptive to process demands, the industry has lacked sufficient advanced control strategies. The variation of the upstream product concentration typically cannot be handled by the downstream capture step, which is configured for a constant feed concentration and fixed binding capacity. This inflexibility leads to losses of efficiency and product yield. This study shows that these challenges can be overcome by a novel advanced control strategy concept that includes dynamic control throughout a perfusion bioreactor, with cell retention by alternating tangential flow, integrated with simulated moving bed (SMB) multi-column chromatography. The automation workflow and advanced control strategy were implemented through the use of a visual programming development environment. This enabled dynamic flow control across the upstream and downstream process integrated with a dynamic column loading of the SMB. A sensor prototype, based on continuous biolayer interferometry measurements was applied to detect mAb breakthrough within the last column flow-through to manage column switching. This novel approach provided higher specificity and lower background signal compared to commonly used spectroscopy methods, resulting in an optimized resin utilization while simultaneously avoiding product loss. The dynamic loading was found to provide a twofold increase of the mAb concentration in the eluate compared to a conservative approach with a predefined recipe with similar impurity removal. This concept shows that advanced control strategies can lead to significant process efficiency and yield improvement.

Comparison of multi-column chromatography configurations through model-based optimization

Integrated continuous bioprocessing has been identified as the next important phase of evolution in biopharmaceutical manufacturing. Multiple platform technologies to enable continuous processing are being developed. Multi-column counter-current chromatography is a step in this direction to provide increased productivity and capacity utilization to capture biomolecules like monoclonal antibodies (mAbs) present in the reactor harvest and remove impurities. Model-based optimization of two prevalent multi-column designs, 3-column and 4-column periodic counter-current chromatography (PCC) was carried out for different concentrations of mAbs in the feed, durations of cleaning-in-place and equilibration protocols. The multi-objective optimization problem comprising three performance measures, namely, product yield, productivity, and capacity utilization was solved using the Radial basis function optimization technique. The superficial velocities during load, wash, and elute operations, along with durations of distinct stages present in the multi-column operations were considered as decision variables. Optimization results without the constraint on number of wash volumes showed that 3-Column PCC performs better than 4-Column PCC. For example, at a feed concentration of 1.2 mg/mL, productivity, yield and capacity utilization, respectively, were 0.024 mg/mL.s, 0.94, and 0.94 for 3-Column PCC and 0.017 mg/mL.s, 0.87, and 0.83 for 4-column PCC. Similar trends were observed at higher feed concentrations also. However, when the constraint on number of wash volumes is included, 4-Column PCC was found to result in consistent productivity and product yield under different operating conditions but at the expense of reduced capacity utilization.

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.

Comparative Evaluation of Commercial Protein A Membranes for the Rapid Purification of Antibodies

Protein A chromatography is ubiquitous to antibody purification. The high specificity of Protein A for binding the Fc-region of antibodies and related products enables unmatched clearance of process impurities like host cell proteins, DNA, and virus particles. A recent development is the commercialization of research-scale Protein A membrane chromatography products that can perform capture step purification with short residence times (RT) on the order of seconds. This study investigates process-relevant performance and physical properties of four Protein A membranes: Purilogics Purexa™ PrA, Gore® Protein Capture Device, Cytiva HiTrap™ Fibro PrismA, and Sartorius Sartobind® Protein A. Performance metrics include dynamic binding capacity, equilibrium binding capacity, regeneration-reuse, impurity clearance, and elution volumes. Physical properties include permeability, pore diameter, specific surface area, and dead volume. Key results indicate that all membranes except the Gore® Protein Capture Device operate with flow rate-independent binding capacities; the Purilogics Purexa™ PrA and Cytiva HiTrap Fibro™ PrismA have binding capacities on par with resins, with orders of magnitude faster throughput; and dead volume and hydrodynamics play major roles in elution behavior. Results from this study will enable bioprocess scientists to understand the ways that Protein A membranes can fit into their antibody process development strategies.

Surrogate-based Optimization of Capture Chromatography Platforms for the Improvement of Computational Efficiency

In this work, we discuss the use of surrogate functions and a new optimization framework to create an efficient and robust computational framework for process design. Our model process is the capture chromatography unit operation for monoclonal antibody purification, an important step in biopharmaceutical manufacturing. Simulating this unit operation involves solving a system of non-linear partial differential equations, which can have high computational cost. We implemented surrogate functions to reduce the computational time and make the framework more attractive for industrial applications. This strategy yielded accurate results with a 93% decrease in processing time. Additionally, we developed a new optimization framework to reduce the number of simulations needed to generate a solution to the optimization problem. We demonstrate the performance of our new framework, which uses MATLAB built-in tools, by comparing its performance against individual optimization algorithms for problems with integer, continuous, and mixed-integer variables.

Computational framework for the techno-economic analysis of monoclonal antibody capture chromatography platforms

We developed a computational framework that integrates commercial software components to perform customizable technoeconomic feasibility analyses. The use of multiple software packages overcomes the shortcomings of each to provide a detailed simulation that can be used for sensitivity analyses and optimizations. In this paper, the framework was used to evaluate the performance of monoclonal antibody capture processes. To this end, the simulation framework incorporated dynamic models for the affinity chromatography step that were validated with experimental breakthrough curves. The results were integrated with an Intelligen SuperPro Designer process simulation for the evaluation of key performance indicators of the operations. As proof of concept, the framework was used to perform a sensitivity analysis and optimization for a case study in which we sought to compare membrane and resin chromatography for disposable and reusable batch capture platforms. Two membranes and one resin were selected for the capture media, which yielded six process alternatives to compare. The objective functions were set to be cost of goods, process time, and buffer utilization. The results of the optimization of these process alternatives were a set of operating conditions that display tradeoffs between competing objectives. From this application exercise, we conclude that the framework can handle multiple variables and objectives, and it is adaptable to platforms with different chromatography media and operating modes. Additionally, the framework is capable of providing ad hoc analyses for decision making in a specific production context.

Computational fluid dynamics simulation and the experimental verification of protein adsorption on a hollow fiber membranes module

Immobilized metal affinity chromatography (IMAC) ensures the specific purification of proteins containing histidine tags through high affinity with transition metal chelators, which has various applications in biological protein separation. Most chromatographic separations currently use a fixed bed. In this form, internal flow pressure drops very sharply, accompanied by uneven solution flow, pore blockages, etc., all of which greatly reduce separation efficiency. Therefore, this study uses hollow fiber membranes (HFMs) with micron-scale inner diameters as a base, thus reducing operating pressure and significantly enhancing mass transmission. Batch adsorption experiments were performed using flat plate membranes to obtain the reaction's thermodynamic and kinetic model parameters for use in a dynamic column breakthrough simulation. The numerical simulation was based on a single HFM model and established a mathematical model for computational fluid dynamics (CFD) in ANSYS Fluent software. Model accuracy was validated by combining the simulation with experiments. The effects of different module and process parameters on the breakthrough curve were investigated by varying parameters such as flow rate, initial feed concentration, and HFM inner diameter. Design parameters and operating conditions contributing to module utilization were subsequently obtained.

Continuous Countercurrent Chromatography in Protein Purification

Continuous countercurrent chromatography can be applied for both capture and polishing steps in the downstream processing of biopharmaceuticals. This chapter explains the concept of countercurrent operation, focusing on twin-column processes and how it can be used to alleviate the trade-offs of traditional batch chromatography with respect to resin utilization/productivity and yield/purity. CaptureSMB and MCSGP, the main twin-column continuous countercurrent chromatography processes, are explained, and the metrics by which they are compared to single-column chromatography are identified. Practical hints for process design and application examples are provided. Finally, regulatory aspects, scale-up, and UV-based process control are covered.

Process integrated biosensors for real-time monitoring of antibodies for automated affinity purification

Therapeutic monoclonal antibodies (mAbs) provide new means for treatments of a wide range of diseases and comprise a large fraction of all new approved drugs. Production of mAbs is expensive compared to conventional drug production, primarily due to the complex processes involved. The affinity purification step is dominating the cost of goods in mAb manufacturing. Process intensification and automation could reduce costs, but the lack of real-time process analytical technologies (PAT) complicates this development. We show a specific and robust fiber optical localized surface plasmon resonance (LSPR) sensor technology that is optimized for in-line product detection in the effluent in affinity capture steps. The sensor system comprises a flow cell and a replaceable sensor chip functionalized with biorecognition elements for specific analyte detection. The high selectivity of the sensor enable detection of mAbs in complex sample matrices at concentrations below 2.5 μg mL^-1. In place regeneration of the sensor chips allowed for continuous monitoring of multiple consecutive chromatographic separation cycles. Excellent performance was obtained at different purification scales with flow rates up to 200 mL min^-1. This sensor technology facilitates efficient column loading, optimization, and control of chromatography systems, which can pave the way for continuous operation and automation of protein purification steps.

Model-based evaluation and model-free strategy for process development of three-column periodic counter-current chromatography

Multi-column counter-current chromatography is an advanced technology used for continuous capture processes to improve process productivity, resin capacity utilization and product consistency. However, process development is difficult due to process complexity. In this work, some general and convenient guidances for three-column periodic counter-current chromatography (3C-PCC) were developed. Boundaries and distributions of operating windows of 3C-PCC processes were clarified by model-based predictions. Interactive effects of feed concentration (c₀), resin properties (q_max and D_e), recovery and regeneration times (t_RR) were evaluated over a wide range for maximum productivity (P_max). Furthermore, variation of P_max was analyzed considering the constraint factors (capacity utilization target and flow rate limitation). The plateau value of P_max was determined by q_max and t_RR. The operating conditions for P_max were controlled by q_max, t_RR and c₀ interactively, and a critical concentration existed to judge whether the operating conditions of P_max under constraints. Based on the comprehensive understanding on 3C-PCC processes, a model-free strategy was proposed for process development. The optimal operating conditions could be determined based on a set of breakthrough curves, which was used to optimize process performance and screen resins. The approach proposed was validated using monoclonal antibody (mAb) capture with a 3C-PCC system under various mAb and feed concentrations. The results demonstrated that a thorough model-based process understanding on multi-column counter-current chromatography is important and could improve process development and establish a model-free strategy for more convenient applications.

Online optimization of dynamic binding capacity and productivity by model predictive control

In preparative and industrial chromatography, the current viewpoint is that the dynamic binding capacity governs the process economy, and increased dynamic binding capacity and column utilization are achieved at the expense of productivity. The dynamic binding capacity in chromatography increases with residence time until it reaches a plateau, whereas productivity has an optimum. Therefore, the loading step of a chromatographic process is a balancing act between productivity, column utilization, and buffer consumption. This work presents an online optimization approach for capture chromatography that employs a residence time gradient during the loading step to improve the traditional trade-off between productivity and resin utilization. The approach uses the extended Kalman filter as a soft sensor for product concentration in the system and a model predictive controller to accomplish online optimization using the pore diffusion model as a simple mechanistic model. When a soft sensor for the product is placed before and after the column, the model predictive controller can forecast the optimal condition to maximize productivity and resin utilization. The controller can also account for varying feed concentrations. This study examined the robustness as the feed concentration varied within a range of 50%. The online optimization was demonstrated with two model systems: purification of a monoclonal antibody by protein A affinity and lysozyme by cation-exchange chromatography. Using the presented optimization strategy with a controller saves up to 43% of the buffer and increases the productivity together with resin utilization in a similar range as a multi-column continuous counter-current loading process.

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.

3D-Printed microfluidic device for protein purification in batch chromatography

Modern 3D printers enable not only rapid prototyping, but also high-precision printing-microfluidic devices with channel diameters of just a few micrometres can now be readily assembled using this technology. Such devices offer a myriad of benefits (including miniaturization) that significantly reduce sample and buffer volumes and lead to lower process costs. Although such microfluidic devices are already widely used in the field of biotechnology, there is a lack of research regarding the potential of miniaturization by 3D-printed devices in lab-scale chromatography. In this study, the efficacy of a 3D-printed microfluidic device which provides a substantially lower dead-volume compared to established chromatography systems is demonstrated for batch purification applications. Furthermore, this device enables straightforward integration of various components (such as microfluidic valves and chromatographic units) in an unprecedentedly flexible fashion. Initial proof-of-concept experiments demonstrate successful gradient elution with bovine serum albumin (BSA), and the purification of a pharmaceutically relevant IgG monoclonal antibody (mAb).

Control strategy for multi-column continuous periodic counter current chromatography subject to fluctuating inlet stream concentration

Fluctuations of the inlet feed stream concentration are a challenge in controlling continuous multi-column counter current chromatography systems with standard methods. We propose a new control strategy based on calculated product column breakthrough from UV sensor signals by neglecting an impurity baseline and instead using the impurity to product ratio. This calculation is independent of the inlet feed concentration. In-silico simulation showed that the proposed method can calculate the product column breakthrough perfectly even with fluctuating and highly unstable inlet feed concentration during a loading cycle. Applying the proposed method to control a three column periodic counter current chromatography process with fluctuating inlet feed concentration resulted in constant column loading in each cycle, while using the standard method failed to do so. Unavoidable band broadening caused by diffusion and dispersion has been identified as an inherent limiting factor for accurate calculation of column breakthrough comparing inlet and outlet UV signals. The proposed advanced calculations increase the robustness of periodic counter current chromatography and extend the capability to process unstable inlet streams.

Mimicking continuous capture chromatography for virus clearance using a single chromatography column model

Continuous chromatography is increasingly being used across the biotechnology industry due to its economic advantages. For adoption in commercial manufacturing, also models for virus clearance studies must be available. We demonstrate how for a virus clearance study for a multispecific antibody, the continuous protein A capture chromatography process, being run on multiple interconnected columns, can be mimicked with only a single column. With this mimicking small-scale model, resources and complexity can be minimized, when conducting virus clearance studies at a contract research organization (CRO) lab. Obtained log reduction values (LRV) for xMuLV and MVM virus, used as model viruses, are comparable to batch protein A chromatography and results described by other groups. The feasibility of this mimicking small-scale model helps to further reduce barriers to adoption when implementing continuous chromatography. This article is protected by copyright. All rights reserved.

A regressive approach to the design of continuous capture process with multi-column chromatography for monoclonal antibodies

Although empirical methods have been introduced in the process development of continuous chromatography, the common approach to optimize a multi-column continuous capture chromatography (periodic counter-current chromatography, PCCC) process heavily relies on numerical model simulations and the number of experiments. In addition, different multi-column settings in PCCC add more design variables in process development. In this study, we have developed a rational method for designing PCCC processes based on iterative calculations by mechanistic model-based simulations. Breakthrough curves of a monoclonal antibody were measured at different residence times for three protein A resins of different particle sizes and capacities to obtain the parameters needed for the simulation. Numerical calculations were performed for the protein sample concentration in the range of 1.5 to 4 g/L. Regression curves were developed to describe the relative process performances compared with batch operation, including the resin capacity utilization and the buffer consumption. Another linear correlation was established between breakthrough cut-off (BT%) and a modified group composed of residence time, mass transfer coefficient, and particle size. By normalizing BT% with binding capacity and switching time, the linear regression curves were established for the three protein A resins, which are useful for the design and optimization of PCCC to reduce the process development time.

Comparison of Protein A affinity resins for twin-column continuous capture processes: Process performance and resin characteristics

Continuous chromatography is a promising technology for downstream processing of biopharmaceuticals. The operation of continuous processes is significantly different to batch-mode chromatography and needs comprehensive evaluation. In this work, the performances of four Protein A affinity resins were studied systematically for twin-column continuous capture processes. A model-based approach was used to evaluate the process performance (productivity and capacity utilization) under varying operation conditions, and the objective was to reveal the crucial resin properties for continuous capture. The trade-off between productivity and capacity utilization was found, and it is necessary to select appropriate resins for different feedstock and operation conditions. The capacity utilization heavily depends on mass transfer, and steep breakthrough curves are favorable for high capacity utilization. The productivity is determined by both equilibrium binding capacity and mass transfer, and the balance of feed amount and feed time is critical. Moreover, the influence of binding capacity and mass transfer on process productivity and parameter sensitivity with two important resin properties (equilibrium binding capacity q_max and effective pore diffusion coefficient D_e) were assessed by the model, and suitable resin parameter ranges for twin-column continuous capture were determined. The model-based approach is an effective and useful tool to evaluate the complex performance of different resins and guide the design of next-generation resins for continuous processes.

Affinity precipitation of monoclonal antibodies using ELP-Z in the elution without resolubilization mode

This paper describes a simplified affinity precipitation process for the purification of mAbs from complex mixtures using elastin-like polypeptide fused to a single Z domain of protein A (ELP-Z). This approach eliminates several steps in the original process by directly extracting the mAb from the affinity precipitate, without the need for resolubilization. The efficacy of this elution without resolubilization (EWR) approach for obtaining pure mAb is demonstrated and the effects of mixing are examined. This simplification of the affinity precipitation process may facilitate the implementation of ELP-Z based mAb bioprocessing, particularly in a continuous scenario.

Hybrid Models for the simulation and prediction of chromatographic processes for protein capture

The biopharmaceutical industries are continuously faced with the pressure to reduce the development costs and accelerate development time scales. The traditional approach of heuristic-based or platform process-based optimization is soon getting obsolete, and more generalized tools for process development and optimization are required to keep pace with the emerging trends. Thus, advanced model-based methods that can reduce the can ensure accelerated development of robust processes with minimal experiments are necessary. Though mechanistic models for chromatography are quite popular, their success is limited by the need to have accurate knowledge of adsorption isotherms and mass transfer kinetics. As an alternative, in this work, a hybrid modeling approach is proposed. Thereby, the chromatographic unit behavior is learned by a combination of neural network and mechanistic model while fitting suitable experimental breakthrough curves. Since this approach does not require identifying suitable mechanistic assumptions for all the phenomena, it can be developed with lower effort. Thus, allowing the scientists to concentrate their focus on process development. The performance of the hybrid model is compared with the mechanistic Lumped kinetic Model for in-silico data and experiments conducted on a system of industrial relevance. The flexibility of the hybrid modeling approach results in about three times higher accuracies compared to Lumped Kinetic Model. This is validated for five different isotherm models used to simulate data, with the hybrid model showing about two to three times lower prediction errors in all the cases. Not only in prediction, but we could also show that the hybrid model is more robust in extrapolating across process conditions with about three times lower error than the LKM. Additionally, it could be demonstrated that an appropriately tailored formulation of the hybrid model can be used to generate representations for the underlying principles such as adsorption equilibria and mass transfer kinetics.

Enhancing protein A productivity and resin utilization within integrated or intensified processes

Recent interest in continuous manufacturing of biologics has driven the development and evaluation of multicolumn chromatography systems to drive down resin costs by increasing productivity and maximizing resin utilization, especially for the expensive protein A capture step. Single-pass tangential flow filtration can be used to reduce the volume of perfusion harvest, enabling a further increase in the productivity of the capture step by up to fivefold. However, there are expected to be practical limits for the productivity of the capture step, which must be determined based on the manufacturing batch size, duration, and frequency, especially as it relates to efficient utilization of the column lifetime. For short fed-batch manufacturing campaigns, intensified capture processes may result in up to 82% lower resin consumption, while avoiding the long-term storage of used resin. For perfusion processes and longer fed-batch campaigns, it may be more efficient to operate at a lower productivity that enables the column lifetime to be routinely achieved and achieves the desired resin and buffer savings without introducing unnecessary process risk or complexity. An intensified batch capture process, "super-batch," will be compared as an alternative to multicolumn chromatography processes to achieve high productivity and resin utilization with a potentially simpler process.

A common framework for integrated and continuous biomanufacturing

There is a growing application of integrated and continuous bioprocessing (ICB) for manufacturing recombinant protein therapeutics produced from mammalian cells. At first glance, the newly evolved ICB has created a vast diversity of platforms. A closer inspection reveals convergent evolution: nearly all of the major ICB methods have a common framework that could allow manufacturing across a global ecosystem of manufacturers using simple, yet effective, equipment designs. The framework is capable of supporting the manufacturing of most major biopharmaceutical ICB and legacy processes without major changes in the regulatory license. This article reviews the ICB that are being used, or are soon to be used, in a GMP manufacturing setting for recombinant protein production from mammalian cells. The adaptation of the various ICB modes to the common ICB framework will be discussed, along with the pros and cons of such adaptation. The equipment used in the common framework is generally described. This review is presented in sufficient detail to enable discussions of IBC implementation strategy in biopharmaceutical companies and contract manufacturers, and to provide a road map for vendors equipment design. An example plant built on the common framework will be discussed. The flexibility of the plant is demonstrated with batches as small as 0.5 kg or as large as 500 kg. The yearly output of the plant is as much as 8 tons.

Continued insights into virus clearance validation across continuous capture chromatography

Multi-column capture chromatography (MCC) has gained increased attention lately due to the significant economic and process-related advantages it offers compared to traditional batch mode chromatography. However, for wide adoption of this technology in the clinical and commercial space, it requires scalable models for viral validation. In this study, additional viral validation studies were conducted under cGLP guidelines to assess retro-(X-MuLV) and parvo-virus (minute virus of mice) clearance across twin-column continuous capture chromatography (CaptureSMB) to supplement work previously performed. A surrogate model was validated using standard batch mode chromatography equipment based on flow path modifications to mimic the loading strategy employed in CaptureSMB. In addition, aged resin was used in this surrogate format to assess the impact of resin lifetime on viral clearance during continuous capture operation. The impact of column loading was also explored to shed light on the viral clearance mechanisms of protein A chromatography in overloading conditions. The proposed approach greatly simplifies MCC virus validation studies, and provides a robust strategy for regulatory filing of continuous biomanufacturing processes.

Linear flow-velocity gradient chromatography-An efficient method for increasing the process efficiency of batch and continuous capture chromatography of proteins

A new method was proposed for increasing the capture chromatography process efficiency, linear flow-velocity gradient (LFG). The method uses a linear decreasing flow-velocity gradient with time during the sample loading. The initial flow velocity, the final flow velocity and the gradient time are the parameters to be tuned. We have developed a method for determining these parameters by using the total column capacity and the total loaded amount as a function of time. The capacity can be calculated by using the relationships between dynamic binding capacity (DBC) and residence time. By leveraging the capacity, loading amount, and the required conditions, the optimum LFG can be designed. The method was verified by ion-exchange and protein A chromatography of monoclonal antibodies (mAbs). A two-fold increase in the productivity during the sample loading was possible by LFG compared with the constant flow-velocity (CF) operation. LFG was also applied to a 4-column continuous process. The simulation showed that the cost of resin per unit amount of processed mAbs can be reduced by 13% while 1.4 times enhancement in productivity was preserved after optimization by LFG compared to CF. The process efficiency improvement is more pronounced when the isotherm is highly favorable and the loading volume is large.

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.

Digital Twins in Biomanufacturing

In recent years process modelling has become an established method which generates digital twins of manufacturing plant operation with the aid of numerically solved process models. This article discusses the benefits of establishing process modelling, in-house or by cooperation, in order to support the workflow from process development, piloting and engineering up to manufacturing. The examples are chosen from the variety of botanicals and biologics manufacturing thus proving the broad applicability from variable feedstock of natural plant extracts of secondary metabolites to fermentation of complex molecules like mAbs, fragments, proteins and peptides.Consistent models and methods to simulate whole processes are available. To determine the physical properties used as model parameters, efficient laboratory-scale experiments are implemented. These parameters are case specific since there is no database for complex molecules of biologics and botanicals in pharmaceutical industry, yet.Moreover, Quality-by-Design approaches, demanded by regulatory authorities, are integrated within those predictive modelling procedures. The models could be proven to be valid and predictive under regulatory aspects. Process modelling does earn its money from the first day of application. Process modelling is a key-enabling tool towards cost-efficient digitalization in chemical-pharmaceutical industries.

Modern trends in downstream processing of biotherapeutics through continuous chromatography: The potential of Multicolumn Countercurrent Solvent Gradient Purification

Single-column (batch) preparative chromatography is the technique of choice for purification of biotherapeutics but it is often characterized by an intrinsic limitation in terms of yield-purity trade-off, especially for separations containing a larger number of product-related impurities. This drawback can be alleviated by employing multicolumn continuous chromatography. Among the different methods working in continuous mode, in this paper we will focus in particular on Multicolumn Countercurrent Solvent Gradient Purification (MCSGP) which has been specifically designed for challenging separations of target biomolecules from their product-related impurities. The improvements come from the automatic internal recycling of the impure fractions inside the chromatographic system, which results in an increased yield without compromising the purity of the pool. In this article, steps of the manufacturing process of biopharmaceuticals will be described, as well as the advantages of continuous chromatography over batch processes, by particularly focusing on MCSGP.

Biomanufacturing evolution from conventional to intensified processes for productivity improvement: a case study

Process intensification has shown great potential to increase productivity and reduce costs in biomanufacturing. This case study describes the evolution of a manufacturing process from a conventional processing scheme at 1000-L scale (Process A, n = 5) to intensified processing schemes at both 1000-L (Process B, n = 8) and 2000-L scales (Process C, n = 3) for the production of a monoclonal antibody by a Chinese hamster ovary cell line. For the upstream part of the process, we implemented an intensified seed culture scheme to enhance cell densities at the seed culture step (N-1) prior to the production bioreactor (N) by using either enriched N-1 seed culture medium for Process B or by operating the N-1 step in perfusion mode for Process C. The increased final cell densities at the N-1 step allowed for much higher inoculation densities in the production bioreactor operated in fed-batch mode and substantially increased titers by 4-fold from Process A to B and 8-fold from Process A to C, while maintaining comparable final product quality. Multiple changes were made to intensify the downstream process to accommodate the increased titers. New high-capacity resins were implemented for the Protein A and anion exchange chromatography (AEX) steps, and the cation exchange chromatography (CEX) step was changed from bind-elute to flow-through mode for the streamlined Process B. Multi-column chromatography was developed for Protein A capture, and an integrated AEX-CEX pool-less polishing steps allowed semi-continuous Process C with increased productivity as well as reductions in resin requirements, buffer consumption, and processing times. A cost-of-goods analysis on consumables showed 6.7–10.1 fold cost reduction from the conventional Process A to the intensified Process C. The hybrid-intensified process described here is easy to implement in manufacturing and lays a good foundation to develop a fully continuous manufacturing with even higher productivity in the future.

Batch chromatography with recycle lag. I-Concept and design

This is the first of a two-part study in which we explore the concept of batch chromatography with recycle lag, concluding with the design, construction, and experimental validation of a prototype that embodies the physical realization of this concept. Moreover, the apparatus is simple to set up in particular in view of large-scale applications. Here the theory behind batch chromatography with recycle lag is revisited and extended, with emphasis on the mathematical formulation and procedure for deriving the single-column batch analogue of any variant of multicolumn simulated countercurrent chromatography. By resorting to selected examples, namely GE Healthcare Bio-science's three-column periodic countercurrent chromatography, Novasep's sequential multicolumn chromatography, and a few hypothetical multicolumn processes, we discuss how the theory can be operationalized. Finally, we conclude by describing the design of a device or apparatus-an eluate recycling device (ERD)-to physically realize the proposed concept. The ERD implements an approximate "first in, first out" method for organizing and manipulating the to-be-recycled fractions of eluate collected from the chromatography column, where the oldest (first) amount fluid, or 'head' of the fraction, is the first to exit and be recycled to the column.

Mechanistic Modeling of Preparative Column Chromatography for Biotherapeutics

Chromatography has long been, and remains, the workhorse of downstream processing in the production of biopharmaceuticals. As bioprocessing has matured, there has been a growing trend toward seeking a detailed fundamental understanding of the relevant unit operations, which for some operations include the use of mechanistic modeling in a way similar to its use in the conventional chemical process industries. Mechanistic models of chromatography have been developed for almost a century, but although the essential features are generally understood, the specialization of such models to biopharmaceutical processing includes several areas that require further elucidation. This review outlines the overall approaches used in such modeling and emphasizes current needs, specifically in the context of typical uses of such models; these include selection and improvement of isotherm models and methods to estimate isotherm and transport parameters independently. Further insights are likely to be aided by molecular-level modeling, as well as by the copious amounts of empirical data available for existing processes.

From batch to continuous chromatographic purification of a therapeutic peptide through multicolumn countercurrent solvent gradient purification

A twin-column Multicolumn Countercurrent Solvent Gradient Purification (MCSGP) process has been developed for the purification of a therapeutic peptide, glucagon, from a crude synthetic mixture. This semi-continuous process uses two identical columns operating either in interconnected or in batch mode, thus enabling the internal recycle of the portions of the eluting stream which do not comply with purity specifications. Because of this feature, which actually results in the simulated countercurrent movement of the stationary phase with respect to the mobile one, the yield-purity trade-off typical of traditional batch preparative chromatography can be alleviated. Moreover, the purification process can be completely automatized. Aim of this work is to present a simple procedure for the development of the MCSGP process based on a single batch experiment, in the case of a therapeutic peptide of industrial relevance. This allowed to recover roughly 90% of the injected glucagon in a purified pool with a purity of about 90%. A comparison between the performance of the MCSGP process and the classical single column batch process indicates that percentage increase in the recovery of target product is +23% when transferring the method from batch conditions to MCSGP, with an unchanged purity of around 89%. This improvement comes at the expenses of a reduction of about 38% in productivity.

Batch chromatography with recycle lag. II-Physical realization and experimental validation

This is the second of a two-part study in which we explore the concept of batch chromatography with recycle lag, concluding with the design, construction, and experimental validation of a prototype-an eluate recycling device (ERD)-that embodies the physical realization of this concept. The ERD implements an approximate "first in, first out" method of organizing and manipulating the to-be-recycled fractions of eluate collected from the chromatography column, where the oldest (first) amount fluid, or 'head' of the fraction, is the first to exit and be recycled back to the column. Moreover, the apparatus is simple to set up in particular in view of large-scale applications. Here we detail the construction of the ERD and assembly of a setup to interconnect the ERD and a chromatography column. Through the coordinated operation of two-way valves and two-position six-port switching valves it is possible to implement a diverse set of configurations or operating modes interconnecting the chromatography column and the ERD. The setup is validated experimentally with success using the separation of a nucleoside mixture by reversed phase chromatography as a model problem. It is also shown that by redesigning the fluid distributor using 3D printing technology the ERD performance can be improved.

Truly continuous low pH viral inactivation for biopharmaceutical process integration

Continuous virus inactivation (VI) has received little attention in the efforts to realize fully continuous biomanufacturing in the future. Implementation of continuous VI must assure a specific minimum incubation time, typically 60 min. To guarantee the minimum incubation time, we implemented a packed bed continuous viral inactivation reactor (CVIR) with narrow residence time distribution (RTD) for low pH incubation. We show that the RTD does not broaden significantly over a wide range of linear flow velocities-which highlights the flexibility and robustness of the design. Prolonged exposure to acidic pH has no impact on bed stability, assuring constant RTD throughout long term operation. The suitability of the packed bed CVIR for low pH inactivation is shown with two industry-standard model viruses, that is xenotropic murine leukemia virus and pseudorabies virus. Controls at neutral pH showed no system-induced VI. At low pH, significant VI is observed, even after only 15 min. Based on the low pH inactivation kinetics, the continuous process is equivalent to traditional batch operation. This study establishes a concept for continuous low pH inactivation and, together with previous reports, highlights the versatility of the packed bed reactor for continuous VI, regardless of the inactivation method.