Quantifying orthogonality and separability: A method for optimizing resin selection and design

DOE-based process optimization for development of efficient methods for purification of recombinant hepatitis B surface antigen from Pichia pastoris feedstock using Capto adhere resin

Background

The multimodal chromatography resins, such as Capto adhere, are considered good candidates to be utilized in downstream processing due to their high capacity and selectivity; however, their multimodal interactions lead to an intricacy in the adsorption-desorption patterns and systematic characterization of conditions for process steps is necessary.

Methods

Capto adhere, a strong ion exchanger with multimodal functionality, was used in this study for the final aim of recombinant hepatitis B surface antigen (rHBsAg) purification from Pichia pastoris (P. pastoris) industrial feedstock. Optimization of various parameters was done using the design of experiments (DOE) approach to determine the best binding and non-binding conditions.

Results

Maximum rHBsAg binding on Capto adhere occurred in 20 mM sodium acetate, pH 4.5, and a binding capacity of about 0.75 mg/ml was achieved, which was much higher than rHBsAg binding capacity of other resins reported so far. In elution optimization investigations, it was revealed that 1 M arginine (buffered in 50 mM sodium phosphate, pH 6.5) was the most efficient eluting agent. The binding and elution optimal conditions were utilized for further purification of rHBsAg from P. pastoris industrial feedstock in bind-elute mode, and the recovery and purity of the obtained rHBsAg were about 60% and 100%, respectively. Following optimization in the flow-through purification mode, the target protein recovery was significantly increased (up to 97%) and the target protein purity of more than 95% was achievable. SEC-HPLC analysis showed that the obtained retention times for the purified rHBsAg were similar to those reported previously.

Conclusions

These results suggest that Capto adhere under such optimized conditions can be considered as a good candidate for efficient purification of rHBsAg from P. pastoris industrial feedstock in downstream processing.

A batch screening technique for the calculation of chromatographic separability

This paper employs a high-throughput parallel batch (microtiter plate) adsorption screen with sequential salt step increases to rapidly generate protein elution profiles for multiple resins at different pHs using a protein library. The chromatographic set used in this work includes single mode, multimodal anion-exchange (MMA), and multimodal cation-exchange (MMC) resins. The protein library consists of proteins with isoelectric points ranging from 5.1 to 11.4 with varying hydrophobicities as determined by their retention on hydrophobic interaction chromatography. The batch sequential experiments are carried out using one protein at a time with a wide set of resins at multiple pH conditions, thus enabling simple microtiter plate detection. A mathematical formulation is then used to determine the first moment of the distributions from each chromatogram (sequential step elution) generated in the parallel batch experiments. Batch data first moments (expressed in salt concentration) are then compared to results obtained from column linear salt gradient elution, and the techniques are shown to be consistent. In addition, first moment data are used to calculate one-resin separability scores, which are a measure of a resin's ability, at a specified pH, to separate the entire set of proteins in the library from one another. Again, the results from the batch and column experiments are shown to be comparable. The first moment data sets were then employed to calculate the two-resin separability scores, which are a measure of the ability of two resins to synergistically separate the entire set of proteins in the library. Importantly, these results based on the two-resin separability performances derived from the batch and column experiments were again shown to be consistent. This approach for rapidly screening large numbers of chromatographic resins and mobile phase conditions for their elution behavior may prove useful for enabling the rapid discovery of new chromatographic ligands and resins.

Mechanistic model-based characterization of size-exclusion-mixed-mode resins for removal of monoclonal antibody fragments

Although antibody fragments are a critical impurity to remove from process streams, few platformable purification techniques have been developed to this end. In this work, a novel size-exclusion-mixed-mode (SEMM) resin was characterized with respect to its efficacy in mAb fragment removal. Inverse size-exclusion chromatography showed that the silica-based resin had a narrow pore size distribution and a median pore radius of roughly 6.2 nm. Model-based characterization was carried out with Chromatography Analysis and Design Toolkit (CADET), using the general rate model and the multicomponent Langmuir isotherm. Model parameters were obtained from fitting breakthrough curves, performed at multiple residence times, for a mixture of mAb, aggregates, and an array of fragments (varying in size). Accurate fits were obtained to the frontal chromatographic data across a range of residence times. Model validation was then performed with a scaled-up column, altering residence time and feed composition from the calibration run. Accurate predictions were obtained, thereby illustrating the model's interpolative and extrapolative capabilities. Additionally, the SEMM resin achieved 90% mAb yield, 37% aggregate removal, 29% [Formula: see text] removal, 54% Fab/Fc removal, 100% Fc fragments removal, and a productivity of 72.3 g mAbL×h. Model predictions for these statistics were all within 5%. Simulated batch uptake experiments showed that resin penetration depth was directly related to protein size, with the exception of the aggregate species, and that separation was governed by differential pore diffusion rates. Additional simulations were performed to characterize the dependence of fragment removal on column dimension, load density, and feed composition. Fragment removal was found to be highly dependent on column load density, where optimal purification was achieved below 100 mg protein/mL column. Furthermore, fragment removal was dependent on column volume (constant load mass), but agnostic to whether column length or diameter was changed. Lastly, the dependence on feed composition was shown to be complex. While fragment removal was inversely related to fragment mass fraction in the feed, the extent depended on fragment size. Overall, the results from this study illustrated the efficacy of the SEMM resin in fragment and aggregate removal and elucidated relationships with key operational parameters through model-based characterization.

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.

A framework for calculating orthogonal selectivities in multimodal systems directly from cell culture fluid

This paper presents a straightforward approach for measuring and quantifying orthogonality directly in complex cell culture fluids (CCFs) without the requirement for tracking the retention behaviors of large sets of proteins. Null-producing CCFs were fractionated using linear salt gradients at constant pH on a set of multimodal resins. Fractions were then analyzed by ultraperformance-reversed phase liquid chromatography and the resulting chromatograms provided host cell protein (HCP) "fingerprints." Using these fingerprints, an inner product vector-based approach was employed to quantify the degree of orthogonality between pairs of resins and operating conditions for these large HCP protein sets. To compare resin orthogonality behavior in different expression systems, the Chinese hamster ovary and Pichia pastoris null-producing CCFs were examined. Orthogonality in multimodal systems was found to strongly depend on the expression system and the HCPs being screened. We also identified several unexpected pairs of multimodal resins within the same family that exhibited significant orthogonality. Furthermore, "self-orthogonality" was evaluated between resins operated at different pHs, and important operating regimes were identified for maximizing orthogonal selectivities. The framework developed in this paper for calculating orthogonality without the need for labor-intensive HCP tracking has important implications for efficient process development and resin/operating condition selection for both monoclonal antibody (mAb) polishing steps and non-mAb processes. In addition, this study provides a tool to unlock the untapped potential of multimodal resins by aiding in their rational selection and incorporation. Finally, the orthogonality framework here can facilitate the development of sets of next-generation multimodal resins specifically designed to provide highly orthogonal and efficient separations tailored for different expression systems.

Evaluation of guanidine-based multimodal anion exchangers for protein selectivity and orthogonality

In this paper, we examined the chromatographic behavior of a new class of guanidine-based multimodal anion exchange resins. The selectivities and protein recoveries on these resins were first evaluated using linear gradient chromatography with a model acidic protein library at pH 5, 6 and 7. While a single-guanidine based resin exhibited significant recovery issues at high ligand density, a bis-guanidine based resin showed high recoveries of all but two of the proteins evaluated in the study. In addition, the bis-guanidine resin showed a more pH dependent selectivity pattern as compared to the low density single-guanidine resin. The salt elution range for the low density single-guanidine and bis-guanidine resins was also observed to vary from 0.250 to 0.621 M and 0.162 to 0.828 M NaCl, respectively. A QSAR model was then developed to predict the elution behavior of these proteins on the guanidine prototypes at multiple pH with overall training and test scores of 0.88 and 0.85, respectively. In addition, molecular dynamics simulations were performed with these ligands immobilized on a self-assembled monolayer (SAM) to characterize their conformational preferences and to gain insight into the molecular basis of their chromatographic behavior. Finally, a recently developed framework was employed to evaluate the separability of the bis-guanidine resin as well as its orthogonality to the multimodal cation exchanger, Nuvia cPrime. This evaluation was carried out using a second model protein library which included both acidic and basic proteins. The results of this analysis indicated that the bis-guanidine prototype exhibited both higher pair separability (0.73) and pair enhancement (0.42) as compared to the less hydrophobic commercial Nuvia aPrime 4A with pair separability and enhancement factors of 0.57 and 0.22, respectively. The enhanced selectivity and orthogonality of this new multimodal anion exchange ligand may offer potential opportunities for bioprocessing applications.

Behavior of Water Near Multimodal Chromatography Ligands and Its Consequences for Modulating Protein-Ligand Interactions

Multimodal chromatography is a powerful approach for purifying proteins that uses ligands containing multiple modes of interaction. Recent studies have shown that selectivity in multimodal chromatographic separations is a function of the ligand structure and geometry. Here, we performed molecular dynamics simulations to explore how the ligand structure and geometry affect ligand-water interactions and how these differences in solution affect the nature of protein-ligand interactions. Our investigation focused on three chromatography ligands: Capto MMC, Nuvia cPrime, and Prototype 4, a structural variant of Nuvia cPrime. First, the solvation characteristics of each ligand were quantified via three metrics: average water density, fluctuations, and residence time. We then explored how solvation was perturbed when the ligand was bound to the protein surface and found that the probability of the phenyl ring dewetting followed the order: Capto MMC > Prototype 4 > Nuvia cPrime. To explore how these differences in dewetting affect protein-ligand interactions, we calculated the probability of each ligand binding to different types of residues on the protein surface and found that the probability of binding to a hydrophobic residue followed the same order as the dewetting behavior. This study illustrates the role that wetting and dewetting play in modulating protein-ligand interactions.