Optimization study on periodic counter-current chromatography integrated in a monoclonal antibody downstream process

Quality by Design in continuous bioprocessing: Investigating the impact of critical process parameters of multi-column chromatography during steady-state and transient phases

Given the complexities of continuous bioprocessing, it is critical to thoroughly investigate the process parameters unique to multi-column chromatography (MCC) and their potential impacts. However, existing studies have focused on either loading densities or residence time at steady states only, and their combined impact on critical quality attributes (CQAs) especially during transient phases were less known. In this study, we investigated the impact of critical process parameters during both steady-state and transient phases (start-up, close-down, and intermediate perturbation) through full factorial design. Our findings revealed that MCC operation with static control results in a maximum delta UV variation (breakthrough percentage from 1st loading column) of 30 % between the start-up phase and steady state. Additionally, eluate concentration showed a slight increase (with a maximum difference of 1.9 mg/mL, equivalent to 25 % deviation) when transitioning from the start-up phase to steady state but significantly decreased (with a maximum difference of 8.2 mg/mL, equivalent to 93 % deviation) when shifting from steady state to the close-down phase. The monomer purity during start-up and steady-state phases remained above 97 % while the close-down phase eluate purity ranged from 57 % to 98 %, depending on the operating conditions. Nevertheless, the variation in product quality can be potentially mitigated by product diversion or pooling with high-purity eluates from steady-state, highlighting the robustness of MCC operation in maintaining consistent product quality. Therefore, our study underscores the critical need to comprehensively understand the process dynamics of MCC operation at both steady state and transient phases.

Improving the sustainability of biopharmaceutical downstream processing through buffer recycling

The production of biopharmaceuticals is a chemical- and water-intensive process. The consumption of water and chemicals is partly due to the need for many different buffers in large volumes during the downstream process, typically consisting of several chromatography steps. Given the global commitment to the goals for sustainable development and the anticipated growth of the biopharmaceutical market, the consumption of large buffer volumes is expected to become problematic. To address this, we propose the introduction of buffer recycling to reduce the consumption of water and chemicals. For solvent based pharmaceutical processes, solvent recycling through re-distillation is already established, but for water-based processes, this concept is still rather unexplored. In this study, buffer recycling was implemented during the equilibration phase of Protein A chromatography for antibody purification. We have investigated the potential gains of buffer recycling and demonstrated buffer recycling in two technical implementations: buffer recycling in a batch-to-batch process and buffer recycling in a multi-column process. Buffer recycling consists of buffer recovery and buffer reuse. During recovery, buffer that has been used during equilibration is collected and pH adjusted, and during the reuse step, the recovered buffer is reintroduced into the process. By introducing buffer recycling, we could reduce the equilibration buffer consumption by almost 50 % in this phase, corresponding to more than 10 % of the total buffer use in the Protein A protocol, and have seen no changes in antibody yield or purity. Hence, through buffer recycling, we can improve the sustainability in biomanufacturing by using less water and chemicals.

Quality by design for mRNA platform purification based on continuous oligo-dT chromatography

Oligo-deoxythymidine (oligo-dT) ligand-based affinity chromatography is a robust method for purifying mRNA drug substances within the manufacturing process of mRNA-based products, including vaccines and therapeutics. However, the conventional batch mode of operation for oligo-dT chromatography has certain drawbacks that reduce the productivity of this process. Here, we report a new continuous oligo-dT chromatography process for the purification of in vitro transcribed mRNA, which reduces losses, improves the efficiency of oligo-dT resin use, and intensifies the chromatography process. Furthermore, the quality by design (QbD) framework was used to establish a design space for the newly developed method. The optimization of process parameters (PPs), including salt type, salt concentration, load flow rate and mRNA load concentration both in batch and the continuous mode, achieved a greater than 90% yield (mRNA recovery) along with greater than 95% mRNA integrity and greater than 99% purity. The productivity of continuous chromatography was estimated to be 5.75-fold higher, and the operating cost was estimated 15% lower, when compared with batch chromatography. Moreover, the QbD framework was further used to map the relationship between critical quality attributes and key performance indicators as a function of critical process parameters and critical material attributes.

Modeling and techno-economic analysis of downstream manufacturing process intensification strategies for existing biopharmaceutical facilities

Downstream process (DSP) intensification technologies have the potential to provide faster, more sustainable, and more profitable processes. Nevertheless, the calculation of the possible benefits obtained from the implementation of these technologies is not always evident and usually depends on a particular production scenario. In the present work, we developed a framework for techno-economic feasibility analysis to assess the impact of changes in protein A capture, polishing, and viral filtration on process performance. The simulation used in this analysis is based on fundamental knowledge of the process and incorporates previously developed tools for calculating multi-column chromatography (MCC) and ultrafiltration-diafiltration variables. This framework was used to simulate production scenarios featuring intensified production schedules, increases in feed titers, MCC, integrated batch polishing, and high throughput viral filtration. These process alternatives were compared through key performance indicators that were selected to address specific questions on the suitability of these process intensification strategies in a particular context. Results were presented graphically for decision-makers to easily identify the best process alternatives for a given production scenario. For the conditions proposed in this work, we find that the scheduling practices, and not the unit operation processing times, have the greatest impact on process productivity. For instance, doubling the harvesting frequency resulted in a productivity increase of up to 61 %. Meanwhile, technological intensification strategies like MCC cause the greatest impact on operating costs, reducing cost of goods of the DSP by up to 27 %. Overall, intensification of individual unit operations can yield benefits from a sustainability and cost perspective, but to achieve higher throughputs, it is necessary to have fully intensified DSP and scheduling practices.

Application of a fluorescent dye-based microfluidic sensor for real-time detection of mAb aggregates

The lack of process analytical technologies able to provide real-time information and process control over a biopharmaceutical process has long impaired the transition to continuous biomanufacturing. For the monoclonal antibody (mAb) production, aggregate formation is a major critical quality attribute (CQA) with several known process parameters (i.e., protein concentration and agitation) influencing this phenomenon. The development of a real-time tool to monitor aggregate formation is then crucial to gain control and achieve a continuous processing. Due to an inherent short operation time, miniaturized biosensors placed after each step can be a powerful solution. In this work, the development of a fluorescent dye-based microfluidic sensor for fast at-line PAT is described, using fluorescent dyes to examine possible mAb size differences. A zigzag microchannel, which provides 90% of mixing efficiency under 30 s, coupled to an UV-Vis detector, and using four FDs, was studied and validated. With different generated mAb aggregation samples, the FDs Bis-ANS and CCVJ were able to robustly detect from, at least, 2.5% to 10% of aggregation. The proposed FD-based micromixer is then ultimately implemented and validated in a lab-scale purification system, demonstrating the potential of a miniaturized biosensor to speed up CQAs measurement in a continuous process.

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.

Sensors and chemometrics in downstream processing

The biopharmaceutical industry is still running in batch mode, mostly because it is highly regulated. In the past, sensors were not readily available and in-process control was mainly executed offline. The most important product parameters are quantity, purity, and potency, in addition to adventitious agents and bioburden. New concepts using disposable single-use technologies and integrated bioprocessing for manufacturing will dominate the future of bioprocessing. To ensure the quality of pharmaceuticals, initiatives such as Process Analytical Technologies, Quality by Design, and Continuous Integrated Manufacturing have been established. The aim is that these initiatives, together with technology development, will pave the way for process automation and autonomous bioprocessing without any human intervention. Then, real-time release would be realized, leading to a highly predictive and robust biomanufacturing system. The steps toward such automated and autonomous bioprocessing are reviewed in the context of monitoring and control. It is possible to integrate real-time monitoring gradually, and it should be considered from a soft sensor perspective. This concept has already been successfully implemented in other industries and requires relatively simple model training and the use of established statistical tools, such as multivariate statistics or neural networks. This review describes a scenario for integrating soft sensors and predictive chemometrics into modern process control. This is exemplified by selective downstream processing steps, such as chromatography and membrane filtration, the most common unit operations for separation of biopharmaceuticals.

Automatic procedure for modelling, calibration, and optimization of a three-component chromatographic separation

The current landscape of biopharmaceutical production necessitates an ever-growing set of tools to meet the demands for shorter development times and lower production costs. One path towards meeting these demands is the implementation of digital tools in the development stages. Mathematical modelling of process chromatography, one of the key unit operations in the biopharmaceutical downstream process, is one such tool. However, obtaining parameter values for such models is a time-consuming task that grows in complexity with the number of compounds in the mixture being purified. In this study, we tackle this issue by developing an automated model calibration procedure for purification of a multi-component mixture by linear gradient ion exchange chromatography. The procedure was implemented using the Orbit software (Lund University, Department of Chemical Engineering), which both generates a mathematical model structure and performs the experiments necessary to obtain data for model calibration. The procedure was extended to suggest operating points for the purification of one of the components in the mixture by means of multi-objective optimization using three different objectives. The procedure was tested on a three-component protein mixture and was able to generate a calibrated model capable of reproducing the experimental chromatograms to a satisfactory degree, using a total of six assays. An additional seventh experiment was performed to validate the model response under one of the suggested optimum conditions, respecting a 95 % purity requirement. All of the above was automated and set in motion by the push of a button. With these results, we have taken a step towards fully automating model calibration and thus accelerating digitalization in the development stages of new biopharmaceuticals.

Current challenges and recent advances on the path towards continuous biomanufacturing

Continuous biopharmaceutical manufacturing is currently a field of intense research due to its potential to make the entire production process more optimal for the modern, ever-evolving biopharmaceutical market. Compared to traditional batch manufacturing, continuous bioprocessing is more efficient, adjustable, and sustainable and has reduced capital costs. However, despite its clear advantages, continuous bioprocessing is yet to be widely adopted in commercial manufacturing. This article provides an overview of the technological roadblocks for extensive adoptions and points out the recent advances that could help overcome them. In total, three key areas for improvement are identified: Quality by Design (QbD) implementation, integration of upstream and downstream technologies, and data and knowledge management. First, the challenges to QbD implementation are explored. Specifically, process control, process analytical technology (PAT), critical process parameter (CPP) identification, and mathematical models for bioprocess control and design are recognized as crucial for successful QbD realizations. Next, the difficulties of end-to-end process integration are examined, with a particular emphasis on downstream processing. Finally, the problem of data and knowledge management and its potential solutions are outlined where ontologies and data standards are pointed out as key drivers of progress.

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.

Real-time detection of mAb aggregates in an integrated downstream process

The implementation of continuous processing in the biopharmaceutical industry is hindered by the scarcity of process analytical technologies (PAT). To monitor and control a continuous process, PAT tools will be crucial to measure real-time product quality attributes such as protein aggregation. Miniaturizing these analytical techniques can increase measurement speed and enable faster decision-making. A fluorescent dye (FD)-based miniaturized sensor has previously been developed: a zigzag microchannel which mixes two streams under 30 s. Bis-ANS and CCVJ, two established FDs, were employed in this micromixer to detect aggregation of the biopharmaceutical monoclonal antibody (mAb). Both FDs were able to robustly detect aggregation levels starting at 2.5%. However, the real-time measurement provided by the microfluidic sensor still needs to be implemented and assessed in an integrated continuous downstream process. In this work, the micromixer is implemented in a lab-scale integrated system for the purification of mAbs, established in an ÄKTA™ unit. A viral inactivation and two polishing steps were reproduced, sending a sample of the product pool after each phase directly to the microfluidic sensor for aggregate detection. An additional UV sensor was connected after the micromixer and an increase in its signal would indicate that aggregates were present in the sample. The at-line miniaturized PAT tool provides a fast aggregation measurement, under 10 min, enabling better process understanding and control.

A fluidized-bed-riser adsorption system for continuous bioproduct recovery from crude feedstock

In this work, a novel technique for continuous purification of biologics from a crude feedstock is demonstrated with equipment referred to as Fluidized Bed Adsorption System (FBRAS). The development and validation of such unit operations were performed utilizing lysozyme as a model protein and Relisorb™ SP405/EB as a carrier. The performance of FBRAS to carry out combined clarification and purification was evaluated by capturing of antifungal peptides directly from the lysed broth. The novel technique reduced the number of process unit operations from six to three without having an impact on purity. Overall productivity increased by 250% in comparison to the existing downstream processing routine.

Automated quality analysis in continuous downstream processes for small-scale applications

Development of integrated, continuous biomanufacturing (ICB) processes brings along the challenge of streamlining the acquisition of data that can be used for process monitoring, product quality testing and process control. Manually performing sample acquisition, preparation, and analysis during process and product development on ICB platforms requires time and labor that diverts attention from the development itself. It also introduces variability in terms of human error in the handling of samples. To address this, a platform for automatic sampling, sample preparation and analysis for use in small-scale biopharmaceutical downstream processes was developed. The automatic quality analysis system (QAS) consisted of an ÄKTA Explorer chromatography system for sample retrieval, storage, and preparation, as well as an Agilent 1260 Infinity II analytical HPLC system for analysis. The ÄKTA Explorer system was fitted with a superloop in which samples could be stored, conditioned, and diluted before being sent to the injection loop of the Agilent system. The Python-based software Orbit, developed at the department of chemical engineering at Lund university, was used to control and create a communication framework for the systems. To demonstrate the QAS in action, a continuous capture chromatography process utilizing periodic counter-current chromatography was set up on an ÄKTA Pure chromatography system to purify the clarified harvest from a bioreactor for monoclonal antibody production. The QAS was connected to the process to collect two types of samples: 1) the bioreactor supernatant and 2) the product pool from the capture chromatography. Once collected, the samples were conditioned and diluted in the superloop before being sent to the Agilent system, where both aggregate content and charge variant composition were determined using size-exclusion and ion-exchange chromatography, respectively. The QAS was successfully implemented during a continuous run of the capture process, enabling the acquisition of process data with consistent quality and without human intervention, clearing the path for automated process monitoring and data-based control.

An automated buffer management system for small-scale continuous downstream bioprocessing

Buffer management for biopharmaceutical purification processes include buffer preparation, storage of buffers and restocking the buffers when needed. This is usually performed manually by the operators for small scale operations. However, buffer management can become a bottleneck when running integrated continuous purification processes for prolonged times, even at small scale. To address this issue, a buffer management system for the application in continuous lab-scale bioprocessing is presented in this paper. For this purpose, an ÄKTA™ explorer chromatography system was reconfigured to perform the buffer formulation. The system formulated all buffers from stock solutions and water according to pre-specified recipes. A digital twin of the physical system was introduced in the research software Orbit, written in python. Orbit was also used for full automation and control of the buffer system, which could run independently without operator input and handle buffer management for one or several connected buffer-consuming purification systems. The developed buffer management system performed automatic monitoring of buffer volumes, buffer order handling as well as buffer preparation and delivery. To demonstrate the capability of the developed system, it was integrated with a continuous downstream process and supplied all 9 required buffers to the process equipment during a 10-day operation. The buffer management system processed 55 orders and delivered 38 L of buffers, corresponding to 20% of its capacity. The pH and conductivity profiles observed during the purification steps were consistent across the cycles. The deviation in conductivity and pH from the measured average value was within ±0.89% in conductivity and ±0.045 in pH, well within the typical specification for buffer release, indicating that the prepared buffers had the correct composition. The operation of the developed buffer management system was robust and fully automated, and provides one solution to the buffer management bottleneck on lab scale for integrated continuous downstream bioprocessing.

Digital twin of a continuous chromatography process for mAb purification: Design and model-based control

Model-based design of integrated continuous train coupled with online process analytical technology (PAT) tool can be a potent facilitator for monitoring and control of Critical Quality Attributes (CQAs) in real time. Charge variants are product related variants and are often regarded as CQAs as they may impact potency and efficacy of drug. Robust pooling decision is required for achieving uniform charge variant composition for mAbs as baseline separation between closely related variants is rarely achieved in process scale chromatography. In this study, we propose a digital twin of a continuous chromatography process, integrated with an online HPLC-PAT tool for delivering real time pooling decisions to achieve uniform charge variant composition. The integrated downstream process comprised continuous multicolumn capture protein A chromatography, viral inactivation in coiled flow inverter reactor (CFIR), and multicolumn CEX polishing step. An online HPLC was connected to the harvest tank before protein A chromatography. Both empirical and mechanistic modeling have been considered. The model states were updated in real time using online HPLC charge variant data for prediction of the initial and final cut point for CEX eluate, according to which the process chromatography was directed to switch from collection to waste to achieve the desired charge variant composition in the CEX pool. Two case studies were carried out to demonstrate this control strategy. In the first case study, the continuous train was run for initially 14 h for harvest of fixed charge variant composition as feed. In the second case study, charge variant composition was dynamically changed by introducing forced perturbation to mimic the deviations that may be encountered during perfusion cell culture. The control strategy was successfully implemented for more than ±5% variability in the acidic variants of the feed with its composition in the range of acidic (13%-17%), main (18%-23%), and basic (59%-68%) variants. Both the case studies yielded CEX pool of uniform distribution of acidic, main and basic profiles in the range of 15 ± 0.8, 31 ± 0.3, and 53 ± 0.5%, respectively, in the case of empirical modeling and 15 ± 0.5, 31 ± 0.3, and 53 ± 0.3%, respectively, in the case of mechanistic modeling. In both cases, process yield for main species was >85% and the use of online HPLC early in the purification train helped in making quicker decision for pooling of CEX eluate. The results thus successfully demonstrate the technical feasibility of creating digital twins of bioprocess operations and their utility for process control.

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.

Integrated continuous biomanufacturing on pilot scale for acid-sensitive monoclonal antibodies

In this study, we demonstrated the first, to our knowledge, integrated continuous bioprocess (ICB) designed for the production of acid-sensitive monoclonal antibodies, prone to aggregate at low pH, on pilot scale. A high cell density perfusion culture, stably maintained at 100 x 10⁶ cells/mL, was integrated with the downstream process, consisting of a capture step with the recently developed Protein A ligand, Z_Ca ; a solvent/detergent-based virus inactivation; and two ion exchange chromatography steps. The use of a mild pH in the downstream process makes this ICB suitable for the purification of acid-sensitive monoclonal antibodies. Integration and automation of the downstream process were achieved using the Orbit software, and the same equipment and control system were used in initial small-scale trials and the pilot-scale downstream process. High recovery yields of around 90% and a productivity close to 1 g purified antibody/L/day were achieved, with a stable glycosylation pattern and efficient removal of impurities, such as host cell proteins and DNA. Finally, negligible levels of antibody aggregates were detected owing to the mild conditions used throughout the process. The present work paves the way for future industrial-scale integrated continuous biomanufacturing of all types of antibodies, regardless of acid stability. This article is protected by copyright. All rights reserved.

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

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

Design of an integrated continuous downstream process for acid-sensitive monoclonal antibodies based on a calcium-dependent Protein A ligand

Monoclonal antibodies (mAb) are used as therapeutics and for diagnostics of a variety of diseases, and novel antibodies are continuously being developed to find treatments for new diseases. Therefore, the manufacturing process must accommodate a range of mAb characteristics. Acid-sensitive mAbs can severely compromise product purity and yield in the purification process due to the potential formation of aggregates. To address this problem, we have developed an integrated downstream process for the purification of pH-sensitive mAbs at mild conditions. A calcium-dependent Protein A-based ligand, called Z_Ca, was used in the capture step in a 3-column periodic counter-current chromatography operation. The binding of Z_Ca to antibodies is regulated by calcium, meaning that acidic conditions are not needed to break the interaction and elute the antibodies. Further, the virus inactivation was achieved by a solvent/detergent method, where the pH could remain unchanged. The polishing steps included a cation and an anion exchange chromatography step, and screening of the capture and polishing steps was performed to allow for a seamless integration of the process steps. The process was implemented at laboratory scale for 9 days obtaining a high yield, and a consistently pure drug substance, including high reduction values of the host cell protein and DNA concentrations, as well as aggregate levels below the detection limit, which is attributed to the mild conditions used in the process.

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.

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.

An integrated continuous downstream process with real-time control: A case study with periodic countercurrent chromatography and continuous virus inactivation

Integrated continuous downstream processes with process analytical technology offer a promising opportunity to reduce production costs and increase process flexibility and adaptability. In this case study, an integrated continuous process was used to purify a recombinant protein on laboratory scale in a two-system setup that can be used as a general downstream setup offering multiproduct and multipurpose manufacturing capabilities. The process consisted of continuous solvent/detergent virus inactivation followed by periodic countercurrent chromatography in the capture step, and a final chromatographic polishing step. A real-time controller was implemented to ensure stable operation by adapting the downstream process to external changes. A concentration disturbance was introduced to test the controller. After the disturbance was applied, the product output recovered within 6 h, showing the effectiveness of the controller. In a comparison of the process with and without the controller, the product output per cycle increased by 27%, the resin utilization increased from 71.4% to 87.9%, and the specific buffer consumption was decreased by 21% with the controller, while maintaining a similar yield and purity as in the process without the disturbance. In addition, the integrated continuous process outperformed the batch process, increasing the productivity by 95% and the yield by 28%.

Process development and optimization of continuous capture with three-column periodic counter-current chromatography

Continuous capture with affinity chromatography is one of the most important units for continuous manufacturing of monoclonal antibody (mAb). Due to the complexity of three-column periodic counter-current chromatography (3C-PCC), three approaches (experimental, model-based, and simplified approaches) were studied for process development and optimization. The effects of residence time for interconnected load (RT _C ), breakthrough percentage of the first column for interconnected load (s) and feed protein concentration (c ₀ ) on productivity and capacity utilization were focused. The model-based approach was found superior to the experimental approach in process optimization and evaluation. Two phases of productivity were observed and the optimal RT _C for the maximum productivity was located at the boundary of the two phases. The comprehensive effects of the operating parameters (RT _C , s, and c ₀ ) were evaluated by the model-based approach, and the operation space was predicted. The best performance of 34.5 g/L/h productivity and 97.6% capacity utilization were attained for MabSelect SuRe LX resin under 5 g/L concentration at RT _C  = 2.8 min and s = 87.5%. Moreover, a simplified approach was suggested to obtain the optimal RT _C for the maximum productivity. The results demonstrated that model-assisted tools are useful to determine the optimum conditions for 3C-PCC continuous capture with high productivity and capacity utilization.

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.

Optimal loading flow rate trajectory in monoclonal antibody capture chromatography

In this paper, we determined the optimal flow rate trajectory during the loading phase of a mAb capture column. For this purpose, a multi-objective function was used, consisting of productivity and resin utilization. Several general types of trajectories were considered, and the optimal Pareto points were obtained for all of them. In particular, the presented trajectories include a constant-flow loading process as a nominal approach, a stepwise trajectory, and a linear trajectory. Selected trajectories were then applied in experiments with the state-of-the-art protein A resin mAb Select PrismA^TM, running in batch mode on a standard single-column chromatography setup, and using both a purified mAb solution as well as a clarified supernatant. The results show that this simple approach, programming the volumetric flow rate according to either of the explored strategies, can improve the process economics by increasing productivity by up to 12% and resin utilization by up to 9% compared to a constant-flow process, while obtaining a yield higher than 99%. The productivity values were similar to the ones obtained in a multi-column continuous process, and ranged from 0.23 to 0.35 mg/min/mL resin. Additionally, it is shown that a model calibration carried out at constant flow can be applied in the simulation and optimization of flow trajectories. The selected processes were scaled up to pilot scale and simulated to prove that even higher productivity and resin utilization can be achieved at larger scales, and therefore confirm that the trajectories are generalizable across process scales for this resin.