Modeling of bispecific antibody elution in mixed-mode cation-exchange chromatography

Application of mechanistic modelling in membrane and fiber chromatography for purification of biotherapeutics - A review

Mechanistic modelling is a simulation tool which has been effectively applied in downstream bioprocessing to model resin chromatography. Membrane and fiber chromatography are newer approaches that offer higher rates of mass transfer and consequently higher flow rates and reduced processing times. This review describes the key considerations in the development of mechanistic models for these unit operations. Mass transfer is less complex than in resin columns, but internal housing volumes can make modelling difficult, particularly for laboratory-scale devices. Flow paths are often non-linear and the dead volume is often a larger fraction of the overall volume, which may require more complex hydrodynamic models to capture residence time distributions accurately. In this respect, the combination of computational fluid dynamics with appropriate protein binding models is emerging as an ideal approach.

Isotherm model discrimination for multimodal chromatography using mechanistic models derived from high-throughput batch isotherm data

In this work, we have examined an array of isotherm formalisms and characterized them based on their relative complexities and predictive abilities with multimodal chromatography. The set of isotherm models studied were all based on the stoichiometric displacement framework, with considerations for electrostatic interactions, hydrophobic interactions, and thermodynamic activities. Isotherm parameters for each model were first determined through twenty repeated fits to a set of mAb - Capto MMC batch isotherm data spanning a range of loading, ionic strength, and pH as well as a set of mAb - Capto Adhere batch data at constant pH. The batch isotherm data were used in two ways-spanning the full range of loading or consisting of only the high concentration data points. Predictive ability was defined through the model's capacity to capture prominent changes in salt gradient elution behavior with respect to pH for Capto MMC or unique elution patterns and yield losses with respect to gradient slope for Capto Adhere. In both cases, model performance was quantified using a scoring metric based on agreement in peak characteristics for column predictions and accuracy of fit for the batch data. These scores were evaluated for all twenty isotherm fits and their corresponding column predictions, thereby producing a statistical distribution of model performances. Model complexity (number of isotherm parameters) was then considered through use of the Akaike information criterion (AIC) calculated from the score distributions. While model performance for Capto MMC benefitted substantially from removal of low protein concentration data, this was not the case for Capto Adhere; this difference was likely due to the qualitatively different shapes of the isotherms between the two resins. Surprisingly, the top-performing (high accuracy with minimal number of parameters) isotherm model was the same for both resins. The extended steric mass action (SMA) isotherm (containing both protein-salt and protein-protein activity terms) accurately captured both the pH-dependent elution behavior for Capto MMC as well as loss in protein recovery with increasing gradient slope for Capto Adhere. In addition, this isotherm model achieved the highest median score in both resin systems, despite it lacking any explicit hydrophobic stoichiometric terms. The more complex isotherm models, which explicitly accounted for both electrostatic and hydrophobic interaction stoichiometries, were ill-suited for Capto MMC and had lower AIC model likelihoods for Capto Adhere due to their increased complexity. Interestingly, the ability of the extended SMA isotherm to predict the Capto Adhere results was largely due to the protein-salt activity coefficient, as determined via isotherm parameter sensitivity analyses. Further, parametric studies on this parameter demonstrated that it had a major impact on both binding affinity and elution behavior, therein fully capturing the impact of hydrophobic interactions. In summary, we were able to determine the isotherm formalisms most capable of consistently predicting a wide range of column behavior for both a multimodal cation-exchange and multimodal anion-exchange resin with high accuracy, while containing a minimized set of model parameters.

Protein association on multimodal chromatography media

The phenomenon of protein-protein association on multimodal chromatography resins was described for two different case study examples. The adsorption pattern of single-component solutions of calcium-rich alpha-lactalbumin (aLaCa) and calcium-depleted alpha-lactalbumin (aLa) and their mixtures with bovine serum albumin was determined on a multimodal anion-exchange chromatography medium. In single-component solutions, both aLaCa and aLa exhibited identical adsorption behavior at low resin loadings, whereas at high loadings the adsorption strength of aLa markedly exceeded that of alaCa. In binary mixtures, the adsorption of BSA enhanced at high concentrations of aLa or aLaCa in the adsorbed phase. The unusual adsorption patterns observed were attributed to the tendency of the proteins for molecular association in the adsorbed phase in single and binary solutions. The phenomena was examined for different pH of the solution: pH 6, 7, 8, and different solvent environments: phosphate buffer (PB), bis tris buffer (BT), 100 mM NaCl in BT and bis tris propane buffer (BTP). The strongest effect was observed for PB and for 100 mM NaCl in BT. Its occurrence was also evidenced for other case study example, i.e., adsorption of single-component solutions and binary mixtures of a monoclonal antibody (mAb) and lysozyme (LYZ) on a multimodal cation-exchange chromatography medium. The enhancement of adsorption of mAb was observed at high concentrations of LYZ in the adsorbed phase. To quantify the underlying effects, a mechanistic model was used, which accounted for both protein association and exclusion resulting from attractive and repulsive protein-protein iterations in the adsorbed phase.

Purification of hydrophobic complex antibody formats using a moderately hydrophobic mixed mode cation exchange resin

Immunoglobulins of complex formats possess great potential for increased biopharmaceutical efficacy. However, challenges arise during their purification as the removal of numerous product-related impurities typically requires several expensive chromatographic steps. Additionally, many complex antibody formats have a high hydrophobicity which impairs the use of conventional mixed mode chromatography. In the present study, both of these challenges were addressed through the development of an innovative mixed mode resin with 2-amino-4methylpentanoic acid ligands that combines weak cation exchange with moderate hydrophobic interactions. Supported by high throughput partition coefficient screens for identification of preferable pH and salt concentration ranges in bind and elute mode, this mixed mode resin successfully demonstrated efficient impurity separation from an extremely hydrophobic bispecific antibody with a single unit operation. High purity (>97%) was obtained as a result of significant reduction of product-related impurities as well as process-related host cell proteins (>3 log scale), while maintaining satisfactory recovery (70%). This also supports that highly hydrophobic antibody formats can be efficiently purified using a resin with moderate hydrophobic characteristics. Studies involving additional antibodies possessing different formats and a wide range of hydrophobicity confirmed the broad applicability of the new resin. In view of its high selectivity and robust operating ranges, as well as the elimination of the need for an additional column step, the novel resin enables simplified downstream processing and economic manufacturing of complex antibody formats.

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.

Chromatographic and adsorptive behavior of a bivalent bispecific antibody and associated fragments

The elution and adsorptive behavior of a bivalent bispecific antibody (BiSAb), comprising an IgG1 framework with a scFv domain genetically fused to each heavy chain C-terminus via flexible linkers, and of two associated fragments were studied on two cation exchange chromatography media - ProPac WCX-10, which is pellicular and suitable for analytical use, and Nuvia HR-S, which is macroporous and suitable for preparative and process scale uses. Both fragments were identified by MS as missing one of the two scFv domains and its flexible linker, but one of them also contains an additional C-terminal lysine. The separation of these fragments on both resins occurs as a result of differences in non-specific ligand-protein interactions that are modulated by the salt concentration. For the ProPac WCX-10 column, complex, multipeak elution behaviors are observed, since, as a result of the linker flexibility, both the intact molecule and the fragments appear to exist in multiple binding configurations with each scFv domains either collapsed onto the IgG framework or extended away from it. With a residence time of 2.5 min and at 21 °C, two peak elution is observed for the fragments which contain a single linked scFv and three peak elution for the intact molecule which contains two linked scFvs. This behavior is affected by residence time, temperature, and hold time. Increasing the residence time to 25 min or increasing temperature to 40°C results in elution of a single, merged peak for each of the protein species. For Nuvia HR-S, the broader peaks, obtained as a result of mass transfer limitations, tend to obscure the multipeak elution behavior. Nevertheless, even for this resin, the effects of configurational flexibility are still manifested at the single-particle scale and affect the evolution of the patterns of protein binding within individual resin particles as evident from confocal microscopy observations.

Ten years in the making: application of CrossMab technology for the development of therapeutic bispecific antibodies and antibody fusion proteins

Bispecific antibodies have recently attracted intense interest. CrossMab technology was described in 2011 as novel approach enabling correct antibody light-chain association with their respective heavy chain in bispecific antibodies, together with methods enabling correct heavy-chain association using existing pairs of antibodies. Since the original description, CrossMab technology has evolved in the past decade into one of the most mature, versatile, and broadly applied technologies in the field, and nearly 20 bispecific antibodies based on CrossMab technology developed by Roche and others have entered clinical trials. The most advanced of these are the Ang-2/VEGF bispecific antibody faricimab, currently undergoing regulatory review, and the CD20/CD3 T cell bispecific antibody glofitamab, currently in pivotal Phase 3 trials. In this review, we introduce the principles of CrossMab technology, including its application for the generation of bi-/multispecific antibodies with different geometries and mechanisms of action, and provide an overview of CrossMab-based therapeutics in clinical trials.

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.