Protein adsorption on ion exchange resins and monoclonal antibody charge variant modulation

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.

Robust mechanistic modeling of protein ion-exchange chromatography

Mechanistic models for ion-exchange chromatography of proteins are well-established and a broad consensus exists on most aspects of the detailed mathematical and physical description. A variety of specializations of these models can typically capture the general locations of elution peaks, but discrepancies are often observed in peak position and shape, especially if the column load level is in the non-linear range. These discrepancies may prevent the use of models for high-fidelity predictive applications such as process characterization and development of high-purity and -productivity process steps. Our objective is to develop a sufficiently robust mechanistic framework to make both conventional and anomalous phenomena more readily predictable using model parameters that can be evaluated based on independent measurements or well-accepted correlations. This work demonstrates the implementation of this approach for industry-relevant case studies using both a model protein, lysozyme, and biopharmaceutical product monoclonal antibodies, using cation-exchange resins with a variety of architectures (SP Sepharose FF, Fractogel EMD SO₃^-, Capto S and Toyopearl SP650M). The modeling employs the general rate model with the extension of the surface diffusivity to be variable, as a function of ionic strength or binding affinity. A colloidal isotherm that accounts for protein-surface and protein-protein interactions independently was used, with each characterized by a parameter determined as a function of ionic strength and pH. Both of these isotherm parameters, along with the variable surface diffusivity, were successfully estimated using breakthrough data at different ionic strengths and pH. The model developed was used to predict overloads and elution curves with high accuracy for a wide variety of gradients and different flow rates and protein loads. The in-silico methodology used in this work for parameter estimation, along with a minimal amount of experimental data, can help the industry adopt model-based optimization and control of preparative ion-exchange chromatography with high accuracy.

Protein adsorption on ion exchange adsorbers: A comparison of a stoichiometric and non-stoichiometric modeling approach

For mechanistic modeling of ion exchange (IEX) processes, a profound understanding of the adsorption mechanism is important. While the description of protein adsorption in IEX processes has been dominated by stoichiometric models like the steric mass action (SMA) model, discrepancies between experimental data and model results suggest that the conceptually simple stoichiometric description of protein adsorption provides not always an accurate representation of nonlinear adsorption behavior. In this work an alternative colloidal particle adsorption (CPA) model is introduced. Based on the colloidal nature of proteins, the CPA model provides a non-stoichiometric description of electrostatic interactions within IEX columns. Steric hindrance at the adsorber surface is considered by hard-body interactions between proteins using the scaled-particle theory. The model's capability of describing nonlinear protein adsorption is demonstrated by simulating adsorption isotherms of a monoclonal antibody (mAb) over a wide range of ionic strength and pH. A comparison of the CPA model with the SMA model shows comparable model results in the linear adsorption range, but significant differences in the nonlinear adsorption range due to the different mechanistic interpretation of steric hindrance in both models. The results suggest that nonlinear adsorption effects can be overestimated by the stoichiometric formalism of the SMA model and are generally better reproduced by the CPA model.

Control of surge tanks for continuous manufacturing of monoclonal antibodies

Surge tanks are critical but often overlooked enablers of continuous bioprocessing. They provide multiple benefits including dampening of concentration gradients and allowing process resumption efforts in case of equipment failure or unexpected deviations, which can occur during a continuous campaign of weeks or months. They are also useful in enabling steady-state operation across a continuous train by facilitating mass balance between unit operations such as chromatography which have periodic loading and elution cycles. In this paper, we propose a design of a system of surge tanks for a monoclonal antibody (mAb) production process consisting of cell culture, clarification, capture chromatography, viral inactivation, polishing chromatography, and single-pass ultrafiltration and diafiltration. A Python controller has been developed for robust control of the continuous train. The controller has four layers, namely data acquisition, process scheduling, deviation handling, and real-time execution. A set of general guidelines for surge tank placement and sizing have been proposed together with process control strategies based on the design space of the individual unit operations, failure modes analysis of the different equipment, and expected variability in the process feed streams for both fed-batch and perfusion bioreactors. The control system has been successfully demonstrated for several continuous runs of up to 36 h in duration and is able to leverage surge tanks for robust control of the continuous train in the face of product variability as well as process errors while maintaining critical quality attributes. The proposed set of strategies for surge tank control are adaptable to most continuous processing setups for mAbs, and together form the first framework that can fully realize the benefits of surge tanks in continuous bioprocessing.

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

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

Multidimensional protein characterisation using microfluidic post-column analysis

The biological function of proteins is dictated by the formation of supra-molecular complexes that act as the basic machinery of the cell. As such, measuring the properties of protein species in heterogeneous mixtures is of key importance for understanding the molecular basis of biological function. Here, we describe the combination of analytical microfluidic tools with liquid chromatography for multidimensional characterisation of biomolecules in complex mixtures in the solution phase. Following chromatographic separation, a small fraction of the flow-through is distributed to multiple microfluidic devices for analysis. The microfluidic device developed here allows the simultaneous determination of the hydrodynamic radius, electrophoretic mobility, effective molecular charge and isoelectric point of isolated protein species. We demonstrate the operation principle of this approach with a mixture of three unlabelled model proteins varying in size and charge. We further extend the analytical potential of the presented approach by analysing a mixture of interacting streptavidin with biotinylated BSA and fluorophores, which form a mixture of stable complexes with diverse biophysical properties and stoichiometries. The presented microfluidic device positioned in-line with liquid chromatography presents an advanced tool for characterising multidimensional physical properties of proteins in biological samples to further understand the assembly/disassembly mechanism of proteins and the nature of complex mixtures.

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.

Highland games: A benchmarking exercise in predicting biophysical and drug properties of monoclonal antibodies from amino acid sequences

Biopharmaceutical product and process development do not yet take advantage of predictive computational modeling to nearly the degree seen in industries based on smaller molecules. To assess and advance progress in this area, spirited coopetition (mutually beneficial collaboration between competitors) was successfully used to motivate industrial scientists to develop, share, and compare data and methods which would normally have remained confidential. The first "Highland Games" competition was held in conjunction with the October 2018 Recovery of Biological Products Conference in Ashville, NC, with the goal of benchmarking and assessment of the ability to predict development-related properties of six antibodies from their amino acid sequences alone. Predictions included purification-influencing properties such as isoelectric point and protein A elution pH, and biophysical properties such as stability and viscosity at very high concentrations. Essential contributions were made by a large variety of individuals, including companies which consented to provide antibody amino acid sequences and test materials, volunteers who undertook the preparation and experimental characterization of these materials, and prediction teams who attempted to predict antibody properties from sequence alone. Best practices were identified and shared, and areas in which the community excels at making predictions were identified, as well as areas presenting opportunities for considerable improvement. Predictions of isoelectric point and protein A elution pH were especially good with all-prediction average errors of 0.2 and 1.6 pH unit, respectively, while predictions of some other properties were notably less good. This manuscript presents the events, methods, and results of the competition, and can serve as a tutorial and as a reference for in-house benchmarking by others. Organizations vary in their policies concerning disclosure of methods, but most managements were very cooperative with the Highland Games exercise, and considerable insight into common and best practices is available from the contributed methods. The accumulated data set will serve as a benchmarking tool for further development of in silico prediction tools.

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

Increasing molecular diversity and market competition requires biopharmaceutical manufacturers to intensify their processes. In this respect, frontal chromatography on cation exchange resins has shown its potential to effectively remove aggregates. However, yield losses during the wash step need to be accepted in order to ensure robust product quality. In this work, we present a novel counter-current frontal chromatography process called Flow2, which uses inline dilution during an interconnected wash phase to allow high monomer recovery without contaminating the product pool with impurities. Its model-based design spaces under purity and yield constraints are compared with those corresponding to traditional batch processes in terms of size and process attributes yield and productivity. The Flow2 process shows the largest extent of feasible operating points independent of feed conditions. Thereby, it allows the implementation of higher ionic strength wash, thus widening the range of operating conditions resulting in yields above 95% compared to batch processes. Productivities of batch and counter-current processes are the same at short regeneration times and equal residence time. However, long regeneration times, while influencing the size of the Flow2 design space, are not detrimental for its productivity resulting in twice as high values as obtained for the batch process. Furthermore, process robustness is evaluated by the ability of the process to maintain the required product quality when subjected to process parameter perturbations. It is found that the Flow2 process is able to retain a larger design space associated also with higher yields showing its ability to improve process attributes without sacrificing robustness at the same time.

Adsorption of Ethylenediaminetetraacetic Acid on a Gel-Type Ion-Exchange Resin for Purification of Liquid Waste Containing Cs Ions

Because of its excellent chelating property, ethylenediaminetetraacetic acid (EDTA) is used as a complex agent, not only for heavy metals, but also for radioactive isotopes during the decontamination of nuclear facilities. The removal of EDTA was investigated by adsorption with commercially available, gel-type, anion-exchange resins (AERs), which are based on cross-linked polystyrene with positive tertiary amine groups. Because of the positive charge on AERs, they could adsorb EDTA effectively even in a solution mixed with ions of cesium (Cs) via electrostatic attraction. Because EDTA adsorption by cation-exchange resins (CERs) was not possible, it was concluded that the negative charges on CERs do not contribute to the interaction with EDTA. The maximum adsorption capacity (q_max) of AER (2 g/L) for EDTA removal, calculated by the Langmuir isotherm model was 0.47 mmol/g for initial EDTA concentrations in the range of 0.01–1 mM in the EDTA/Cs mixed solution. The Langmuir isotherm model was found to be suitable for EDTA adsorption on AERs, indicative of monolayer adsorption. The results clearly suggested that the AERs could efficiently remove EDTA, regardless of the presence of nuclides, such as Cs ions in the aqueous solution.

Protein adsorption in polyelectrolyte brush type cation-exchangers

Ion exchange chromatography materials functionalized with polyelectrolyte brushes (PEB) are becoming an integral part of many protein purification steps. Adsorption onto these materials is different than that onto traditional materials, due to the 3D partitioning of proteins into the polyelectrolyte brushes. Despite this mechanistic difference, many works have described the chromatographic behavior of proteins on polyelectrolyte brush type ion exchangers with much of the same methods as used for traditional materials. In this work, unconventional chromatographic behavior on polyelectrolyte brush type materials is observed for several proteins: the peaks shapes reveal first anti-Langmuirian and then Langmuirian types of interactions, with increasing injection volumes. An experimental and model based description of these materials is carried out in order to explain this behavior. The reason for this behavior is shown to be the 3D partitioning of proteins into the polyelectrolyte brushes: proteins that fully and readily utilize the 3D structure of the PEB phase during adsorption show this behavior, whereas those that do not show traditional ion exchange behavior.

Purification of Monoclonal Antibodies Using a Fiber Based Cation-Exchange Stationary Phase: Parameter Determination and Modeling

Monoclonal antibodies (mAb) currently dominate the market for protein therapeutics. Because chromatography unit operations are critical for the purification of therapeutic proteins, the process integration of novel chromatographic stationary phases, driven by the demand for more economic process schemes, is a field of ongoing research. Within this study it was demonstrated that the description and prediction of mAb purification on a novel fiber based cation-exchange stationary phase can be achieved using a physico-chemical model. All relevant mass-transport phenomena during a bind and elute chromatographic cycle, namely convection, axial dispersion, boundary layer mass-transfer, and the salt dependent binding behavior in the fiber bed were described. This work highlights the combination of model adaption, simulation, and experimental parameter determination through separate measurements, correlations, or geometric considerations, independent from the chromatographic cycle. The salt dependent binding behavior of a purified mAb was determined by the measurement of adsorption isotherms using batch adsorption experiments. Utilizing a combination of size exclusion and protein A chromatography as analytic techniques, this approach can be extended to a cell culture broth, describing the salt dependent binding behavior of multiple components. Model testing and validation was performed with experimental bind and elute cycles using purified mAb as well as a clarified cell culture broth. A comparison between model calculations and experimental data showed a good agreement. The influence of the model parameters is discussed in detail.

Purification of organic acids by chromatography with strong anionic resins: Investigation of uptake mechanisms

Bio-based organic acids are promising renewable carbon sources for the chemical industry. However energy-consuming purification processes are used, like distillation or crystallization, to reach high purities required in some applications. That is why preparative chromatography was studied as an alternative separation technique. In a previous work dealing with the purification of lactic, succinic and citric acids, the Langmuir model was insufficient to explain the elution profiles obtained with a strong anionic resin. Consequently the Langmuir model was coupled with a usual ion-exchange model to take into account the retention of their conjugate bases (<2%), which are commonly neglected at low pH (<1.5). Elution simulations with both uptake mechanisms fitted very well with experimental pulse tests. Only two parameters were optimized (equilibrium constant of acid uptake and ion-exchange selectivity coefficient of conjugate base) and their value were coherent with experimental and resin suppliers' data. These results confirmed that the singular tailing and apparent delay observed with succinic and citric acids can be explained by the high affinity of succinate and citrate for resin cationic sites. The model was implemented in a preparative chromatography simulation program in order to optimize operating parameters of our pilot-scale ISMB unit (Improved Simulated Moving Bed). The comparison with experimental ISMB profiles was conclusive.