Prediction tool for loading, isocratic elution, gradient elution and scaling up of ion exchange chromatography of proteins

Coupling cation and anion exchange chromatography for fast separation of monoclonal antibody charge variants

A design procedure for the separation of charge variants of a monoclonal antibody (mAb) was developed, which was based on the coupling of cation-exchange chromatography (CEX) and anion-exchange chromatography (AEX) under high loading conditions. The design of the coupled process was supported by a dynamic model. The model was calibrated on the basis of band profiles of variants determined experimentally for the mAb materials of different variant compositions. The numerical simulations were used to select the coupling configuration and the loading conditions that allowed for efficient separation of the mAb materials into three products enriched with each individual variant: the acidic (av), main (mv) and basic (bv) one. In the CEX section, a two-step pH gradient was used to split the loaded mass of mAb into a weakly bound fraction enriched with av and mv, and a strongly bound fraction containing the bv-rich product. The weakly bound fraction was further processed in the AEX section, where the mv-rich product was eluted in flowthrough, while the av-rich product was collected by a step change in pH. The choice of flow distribution and the number of columns in the CEX and AEX sections depended on the variant composition of the mAb material. For the selected configurations, the optimized mAb loading density in the CEX columns ranged from 10 to 26 mg mL-1, while in the AEX columns it was as high as 300 or 600 mg mL-1, depending on the variant composition of the mAb material. By proper selection of the loading condition, a trade-off between yield and purity of the products could be reached.

Digital twin in high throughput chromatographic process development for monoclonal antibodies

The monoclonal antibody (mAb) industry is becoming increasingly digitalized. Digital twins are becoming increasingly important to test or validate processes before manufacturing. High-Throughput Process Development (HTPD) has been progressively used as a tool for process development and innovation. The combination of High-Throughput Screening with fast computational methods allows to study processes in-silico in a fast and efficient manner. This paper presents a hybrid approach for HTPD where equal importance is given to experimental, computational and decision-making stages. Equilibrium adsorption isotherms of 13 protein A and 16 Cation-Exchange resins were determined with pure mAb. The influence of other components in the clarified cell culture supernatant (harvest) has been under-investigated. This work contributes with a methodology for the study of equilibrium adsorption of mAb in harvest to different protein A resins and compares the adsorption behavior with the pure sample experiments. Column chromatography was modelled using a Lumped Kinetic Model, with an overall mass transfer coefficient parameter (kov). The screening results showed that the harvest solution had virtually no influence on the adsorption behavior of mAb to the different protein A resins tested. kov was found to have a linear correlation with the sample feed concentration, which is in line with mass transfer theory. The hybrid approach for HTPD presented highlights the roles of the computational, experimental, and decision-making stages in process development, and how it can be implemented to develop a chromatographic process. The proposed white-box digital twin helps to accelerate chromatographic process development.

Coupling of chromatography and precipitation for adjusting acidic variant content in a monoclonal antibody pool

The acidic charge variants (av) of monoclonal antibodies (mAb) are often reported to have reduced therapeutic potency compared with the main (mv) and basic variants (bv), therefore reduction in the av content in mAb pools is often prioritized over reduction in the bv content. In previous studies we described two different methods for reducing the av content, which were based on either ion exchange chromatography or selective precipitation in polyethylene glycol (PEG) solutions. In this study, we have developed a coupled process, in which advantages of simplicity and ease in realization of PEG-aided precipitation and high separation selectivity of anion exchange chromatography (AEX) were exploited. The design of AEX was supported by the kinetic-dispersive model, which was supplemented with the colloidal particle adsorption isotherm, whereas the precipitation process and its coupling with AEX was quantified by simple mass balance equations and underlying thermodynamic dependencies. The model was used to assess the performance of the coupling of AEX and precipitation under different operating conditions. The advantage of the coupled process over the stand-alone AEX depended on the demand for the av reduction as well as the initial variant composition of the mAb pool, e.g., the improvement in the throughput provided by the optimized sequence of AEX and PREC varied from 70 to 600% for the initial av content changed from 35 to 50% w/w, and the reduction demand changed from 30 to 60%.

The use of predictive models to develop chromatography-based purification processes

Chromatography is the workhorse of biopharmaceutical downstream processing because it can selectively enrich a target product while removing impurities from complex feed streams. This is achieved by exploiting differences in molecular properties, such as size, charge and hydrophobicity (alone or in different combinations). Accordingly, many parameters must be tested during process development in order to maximize product purity and recovery, including resin and ligand types, conductivity, pH, gradient profiles, and the sequence of separation operations. The number of possible experimental conditions quickly becomes unmanageable. Although the range of suitable conditions can be narrowed based on experience, the time and cost of the work remain high even when using high-throughput laboratory automation. In contrast, chromatography modeling using inexpensive, parallelized computer hardware can provide expert knowledge, predicting conditions that achieve high purity and efficient recovery. The prediction of suitable conditions in silico reduces the number of empirical tests required and provides in-depth process understanding, which is recommended by regulatory authorities. In this article, we discuss the benefits and specific challenges of chromatography modeling. We describe the experimental characterization of chromatography devices and settings prior to modeling, such as the determination of column porosity. We also consider the challenges that must be overcome when models are set up and calibrated, including the cross-validation and verification of data-driven and hybrid (combined data-driven and mechanistic) models. This review will therefore support researchers intending to establish a chromatography modeling workflow in their laboratory.

Mass transfer of proteins in chromatographic media: Comparison of pure and crude feed solutions

Elucidation of intraparticle mass transfer mechanisms in protein chromatography is essential for process design. This study investigates the differences of adsorption and diffusion parameters of basic human fibroblast factor 2 (hFGF2) in a simple (purified) and a complex (clarified homogenate) feed solution on the grafted agarose-based strong cation exchanger Capto S. Microscopic investigations using confocal laser scanning microscopy revealed slower intraparticle diffusion of hFGF2 in the clarified homogenate compared to purified hFGF2. Diffusive adsorption fronts indicated a strong contribution of solid diffusion to the overall mass transfer flux. Protein adsorption methods such as batch uptake and shallow bed as well as breakthrough curve experiments confirmed a 40-fold reduction of the mass transfer flux for hFGF2 in the homogenate compared to pure hFGF2. The slower mass transfer was induced by components of the clarified homogenate. Essentially, the increased dynamic viscosity caused by a higher concentration of dsDNA and membrane lipids in the clarified homogenate contributed to this decrease in mass transfer. Moreover, binding capacity for hFGF2 was much lower in the clarified homogenate and substantially decreased the adsorbed phase driving force for mass transfer.

Separation of charge variants of a monoclonal antibody by overloaded ion exchange chromatography

A procedure for adjusting the content of charge variants of monoclonal antibody by ion exchange chromatography has been developed. The band splitting phenomenon was utilized to split the protein load into two parts, i.e., the flowthrough and bound fractions, which were either enriched or depleted with some of variants. The phenomenon was triggered by thermodynamic effects resulting from oversaturation of the resin binding sites at high column loadings as well as from kinetic effects arising from limited rates of mass transport. Cation exchange chromatography (CEX) and anion exchange chromatography (AEX) separations were examined, with the reverse order of the variant elution: acidic, main, basic in CEX, and basic, main, acidic in AEX, and the corresponding reverse enrichment tendency in the collected fractions. The separations were performed by pH gradient, whose course was simplified to two stages: isocratic loading and washing at mild pH to load and partly elute the protein, followed by a rapid pH change towards non-binding conditions to desorb the remains of the protein load. To improve yield of the operation, possibility of recycling of waste fractions was considered. To predict the process performance, a dynamic model was developed, which accounted for both adsorption kinetics and thermodynamics.

Analysis of complex protein elution behavior in preparative ion exchange processes using a colloidal particle adsorption model

A fundamental understanding of the protein retention mechanism in preparative ion exchange (IEX) chromatography columns is essential for a model-based process development approach. For the past three decades, the mechanistic description of protein retention has been based predominantly on the steric mass action (SMA) model. In recent years, however, retention profiles of proteins have been reported more frequently for preparative processes that are not consistent with the mechanistic understanding relying on the SMA model. In this work, complex elution behavior of proteins in preparative IEX processes is analyzed using a colloidal particle adsorption (CPA) model. The CPA model is found to be capable of reproducing elution profiles that cannot be described by the traditional SMA model. According to the CPA model, the reported complex behavior can be ascribed to a strong compression and concentration of the elution front in the lower unsaturated part of the chromatography column. As the unsaturated part of the column decreases with increasing protein load density, exceeding a critical load density can lead to the formation of a shoulder in the peak front. The general applicability of the model in describing preparative IEX processes is demonstrated using several industrial case studies including multiple monoclonal antibodies on different IEX adsorber systems. In this context, the work covers both salt controlled and pH-controlled protein elution.

Influence of the geometry of extra column volumes on band broadening in a chromatographic system. Predictions by computational fluid dynamics

A computational fluid dynamics method was used for prediction of flow behavior and band profiles of small- and macro-molecule compounds eluting in extra-column volumes (ECV) of an Äkta chromatographic system. The model compounds were: acetone, bovine serum albumin and an antibody. The construction of ECV was approximated by different types of geometries, starting from the simplest two-dimensional (2D) arrangement consisting of a straight capillary tube, and ending with a three-dimensional system (3D), which accounted for the flow path curvature of individual elements of ECV, including: injection loop capillary, multi-way valve, connecting capillary and detector cell. The accuracy of the model predictions depended on the flow path length and the eluent flowrate. 2D-geometry models reproduced pretty well the shapes of band profiles recorded at the lowest eluent flowrate used, but they failed for increased flowrates. The 3D-geometry model was found to be sufficiently accurate for all conditions investigated. It was exploited to analyze band broadening in the individual ECV elements. The simulation results revealed that the flow behavior in the injection loop capillaries strongly influenced the shape of band profiles, particularly at higher eluent velocities. This was attributed to the formation of Dean vertices triggered by centrifugal forces in curved parts of the eluent flow path.

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.

Implications of dispersion in connecting capillaries for separation systems involving post-column flow splitting

It is common practice in liquid chromatography to split the flow of the effluent exiting the analytical column into two or more parts, either to enable parallel detection (e.g., coupling the separation to two destructive detectors such as light scattering and mass spectrometry (MS)), or to accommodate flow rate limitations of a detector (e.g., electrospray ionization mass spectrometry). In these instances the user must make choices about split ratio and dimensions of connecting tubing that is used between the split point and the detector, however these details are frequently not mentioned in the literature, and rarely justified. In our own work we often split the effluent following the second dimension (²D) column in two-dimensional liquid chromatography systems coupled to MS detection, and we have frequently observed post ²D column peak broadening that is larger than we would expect to result from dispersion in the MS ionization source itself. For the present paper we describe a series of experiments aimed at understanding the impact of the split ratio and post-split connecting tubing dimensions on dispersion of peaks exiting an analytical column. We start with the simple idea - based on the principle of conservation of mass - that analyte peaks entering the split point are split into two parts such that the analyte mass (and thus peak volume) entering and exiting the split point is conserved, and directly related to the ratio of flow rates entering and exiting the split point. Measurements of peak width and variance after the split point show that this simple view of the splitting process - along with estimates of additional dispersion in the post-split tubing - is sufficient to predict peak variances at the detector with accuracy that is sufficient to guide experimental work (median error of about 10% over a wide range of conditions). We feel it is most impactful to recognize that flow splitting impacts apparent post-column dispersion not because anything unexpected happens in the splitting process, but because the split dramatically reduces the volume of the analyte peak, which then is more susceptible to dispersion in connecting tubing that would not cause significant dispersion under conditions where splitting is not implemented. These results will provide practitioners with a solid basis on which rational decisions about split ratios and dimensions of post-split tubing can be made.

A case study of the mechanism of unfolding and aggregation of a monoclonal antibody in ion exchange chromatography

A mechanistic model for describing unfolding of a monoclonal antibody (mAb) in ion exchange chromatography has been developed. The model reproduced retention behavior characteristic for conformational changes of antibodies upon adsorption, including: multi-peak elution, aggregate formation, and recovery reduction. Two competitive paths in the adsorption mechanism of the unfolded protein were assumed: refolding in the adsorbed phase to the native form followed by its desorption, or direct desorption followed by instantaneous aggregation in the liquid phase. The reduction in recovery of the eluted protein was attributed to spreading of the unfolded protein on the adsorbent surface, which enhanced the binding affinity. The model was formulated based on the analysis of retention behavior of a model mAb that was eluted in pH gradients on a strong cation exchange resin. The pH profile was found to be distorted in the presence of the protein, which was ascribed to dissociation of ionizable groups of the protein in the adsorbed phase. Since the protein retention was strongly pH dependent, that phenomenon was also accounted for in mathematical modeling. A series of independent experiments was designed to evaluate the model parameters that quantified the process thermodynamics and kinetics: the Henry constants of the native, unfolded, spread and aggregated forms of the protein along with underlying kinetic coefficients. The model was efficient in reproducing the retention pattern of the protein and the aggregate content in eluting band profiles. After proper calibration, the model can potentially be used to quantify protein unfolding and elution in other ion exchange systems.

Effects of negative and positive cooperative adsorption of proteins on hydrophobic interaction chromatography media

The adsorption behavior of the model proteins: alpha-Lactalbumin, Bovine Serum Albumin, Lysozyme, and a monoclonal antibody, in single component and in binary mixtures, was investigated on two different hydrophobic interaction chromatography resins using both static and dynamic methods. A kinetic model of the adsorption process was developed, which accounted for protein unfolding and intermolecular interactions in the adsorbed phase. The latter incorporated positive cooperative interactions, resulting from preferred and multilayer adsorption on the adsorbent surface, as well as negative cooperative interactions attributed to exclusion effects due to size exclusion and repulsion. Cooperative adsorption resulted in negative or positive deviations from the Langmuir model for both single and multicomponent isotherms. The model was used to assess possible contributions of different adsorption mechanisms of proteins and their structurally different forms to the overall adsorption pattern, as well as to simulate chromatographic band profiles under different loading conditions. For proteins with unstable structure, the overall adsorption isotherm was dominated by binding of unfolded species at low surface coverage and by positive cooperative adsorption at high surface coverage. Furthermore, regardless of structural stability, exclusion effects influenced strongly adsorption equilibrium, particularly at low surface coverages. In case of chromatographic elution, i.e. under dynamic conditions, unfolding, negative cooperative adsorption, and kinetic effects governed the retention behavior and determined peak shapes, whereas the effect of positive cooperative adsorption was negligible.

Prediction uncertainty assessment of chromatography models using Bayesian inference

Mechanistic modeling of chromatography has been around in academia for decades and has gained increased support in pharmaceutical companies in recent years. Despite the large number of published successful applications, process development in the pharmaceutical industry today still does not fully benefit from a systematic mechanistic model-based approach. The hesitation on the part of industry to systematically apply mechanistic models can often be attributed to the absence of a general approach for determining if a model is qualified to support decision making in process development. In this work a Bayesian framework for the calibration and quality assessment of mechanistic chromatography models is introduced. Bayesian Markov Chain Monte Carlo is used to assess parameter uncertainty by generating samples from the parameter posterior distribution. Once the parameter posterior distribution has been estimated, it can be used to propagate the parameter uncertainty to model predictions, allowing a prediction-based uncertainty assessment of the model. The benefit of this uncertainty assessment is demonstrated using the example of a mechanistic model describing the separation of an antibody from its impurities on a strong cation exchanger. The mechanistic model was calibrated at moderate column load density and used to make extrapolations at high load conditions. Using the Bayesian framework, it could be shown that despite significant parameter uncertainty, the model can extrapolate beyond observed process conditions with high accuracy and is qualified to support process development.