Estimating and leveraging protein diffusion on ion-exchange resin surfaces

Mixed-mode size-exclusion silica resin for polishing human antibodies in flow-through mode

The polishing step in the downstream processing of therapeutic antibodies removes residual impurities from Protein A eluates. Among the various classes of impurities, antibody fragments are especially challenging to remove due to the broad biomolecular diversity generated by a multitude of fragmentation patterns. The current approach to fragment removal relies on ion exchange or mixed-mode adsorbents operated in bind-and-gradient-elution mode. However, fragments that bear strong similarity to the intact product or whose biophysical features deviate from the ensemble average can elude these adsorbents, and the lack of a chromatographic technology enabling robust antibody polishing is recognized as a major gap in downstream bioprocessing. Responding to this challenge, this study introduces size-exclusion mixed-mode (SEMM) silica resins as a novel chromatographic adsorbent for the capture of antibody fragments irrespective of their biomolecular features. The pore diameter of the silica beads features a narrow distribution and is selected to exclude monomeric antibodies, while allowing their fragments to access the pores where they are captured by the mixed-mode ligands. The static and dynamic binding capacity of the adsorbent ranged respectively between 30-45 and 25-33 gs of antibody fragments per liter of resin. Selected SEMM-silica resins also demonstrated the ability to capture antibody aggregates, which adsorb on the outer layer of the beads. Optimization of the SEMM-silica design and operation conditions - namely, pore size (10 nm) and ligand composition (quaternary amine and alkyl chain) as well as the linear velocity (100 cm/h), ionic strength (5.7 mS/cm), and pH (7) of the mobile phase - afforded a significant reduction of both fragments and aggregates, resulting into a final antibody yield up to 80% and monomeric purity above 97%.

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.

Predictive mechanistic modeling of loading and elution in protein A chromatography

Protein A chromatography is an enabling technology in current manufacturing processes of monoclonal antibodies (mAbs) and mAb derivatives, largely due to its ability to reduce the levels of process-related impurities by several orders of magnitude. Despite its widespread application, the use of mathematical modeling capable of accurately predicting the full protein A chromatographic process, including loading, post-loading wash and elution stages, has been limited. This work describes a mechanistic modeling approach utilizing the general rate model (GRM), the capabilities of which are explored and optimized using two isotherm models. Isotherm parameters were estimated by inverse-fitting simulated breakthrough curves to experimental data at various pH values. The parameter values so obtained were interpolated across the relevant pH range using a best-fit curve, thus enabling their use in predictive modeling, including of elution over a range of pH. The model provides accurate predictions (< 3% mean error in 10% dynamic binding capacity predictions and ∼ 5% mean error in elution mass and pool volume predictions, both on scale-up) for various residence times, buffer conditions and elution schemes and its effectiveness for use in scale-up and process development is shown by applying the same parameters to larger columns and a wider range of residence times.

Model based process optimization of an industrial chromatographic process for separation of lactoferrin from bovine milk

Model based process development using predictive mechanistic models is a powerful tool for in-silico downstream process development. It allows to obtain a thorough understanding of the process reducing experimental effort. While in pharma industry, mechanistic modeling becomes more common in the last years, it is rarely applied in food industry. This case study investigates risk ranking and possible optimization of the industrial process of purifying lactoferrin from bovine milk using SP Sepharose Big Beads with a resin particle diameter of 200 µm, based on a minimal number of lab-scale experiments combining traditional scale-down experiments with mechanistic modeling. Depending on the location and season, process water pH and the composition of raw milk can vary, posing a challenge for highly efficient process development. A predictive model based on the general rate model with steric mass action binding, extended for pH dependence, was calibrated to describe the elution behavior of lactoferrin and main impurities. The gained model was evaluated against changes in flow rate, step elution conditions, and higher loading and showed excellent agreement with the observed experimental data. The model was then used to investigate the critical process parameters, such as water pH, conductivity of elution steps, and flow rate, on process performance and purity. It was found that the elution behavior of lactoferrin is relatively consistent over the pH range of 5.5 to 7.6, while the elution behavior of the main impurities varies greatly with elution pH. As a result, a significant loss in lactoferrin is unavoidable to achieve desired purities at pH levels below pH 6.0. Optimal process parameters were identified to reduce water and salt consumption and increase purity, depending on water pH and raw milk composition. The optimal conductivity for impurity removal in a low conductivity elution step was found to be 43 mS/cm, while a conductivity of 95 mS/cm leads to the lowest overall salt usage during lactoferrin elution. Further increasing the conductivity during lactoferrin elution can only slightly lower the elution volume thus can also lead to higher total salt usage. Low flow rates during elution of 0.2 column volume per minute are beneficial compared to higher flow rates of 1 column volume per minute. The, on lab-scale, calibrated model allows predicting elution volume and impurity removal for large-scale experiments in a commercial plant processing over 106 liters of milk per day. The successful model extrapolation was possible without recalibration or detailed knowledge of the manufacturing plant. This study therefore provides a possible pathway for rapid process development of chromatographic purification in the food industries combining traditional scale-down experiments with mechanistic modeling.

Diffusion coefficients and MSD measurements on curved membranes and porous media

We study some geometric aspects that influence the transport properties of particles that diffuse on curved surfaces. We compare different approaches to surface diffusion based on the Laplace-Beltrami operator adapted to predict concentration along entire membranes, confined subdomains along surfaces, or within porous media. Our goal is to summarize, firstly, how diffusion in these systems results in different types of diffusion coefficients and mean square displacement measurements, and secondly, how these two factors are affected by the concavity of the surface, the shape of the possible barriers or obstacles that form the available domains, the sinuosity, tortuosity, and constrictions of the trajectories and even how the observation plane affects the measurements of the diffusion. In addition to presenting a critical and organized comparison between different notions of MSD, in this review, we test the correspondence between theoretical predictions and numerical simulations by performing finite element simulations and illustrate some situations where diffusion theory can be applied. We briefly reviewed computational schemes for understanding surface diffusion and finally, discussed how this work contributes to understanding the role of surface diffusion transport properties in porous media and their relationship to other transport processes.

Anti-Langmuir elution behavior of a bispecific monoclonal antibody in cation exchange chromatography: Mechanistic modeling using a pH-dependent Self-Association Steric Mass Action isotherm

The objective of this scientific work was to model and simulate the complex anti-Langmuir elution behavior of a bispecific monoclonal antibody (bsAb) under high loading conditions on the strong cation exchange resin POROS™ XS. The bsAb exhibited anti-Langmuirian elution behavior as a consequence of self-association expressed both in uncommon retentions and peak shapes highly atypical for antibodies. The widely applied Steric Mass Action (SMA) model was unsuitable here because it can only describe Langmuirian elution behavior and is not able to describe protein-protein interactions in the form of self-association. For this reason, a Self-Association SMA (SAS-SMA) model was applied, which was extended by two activity coefficients for the salt and protein in solution. This model is able to describe protein-protein interactions in the form of self-dimerization and thus can describe anti-Langmuir elution behavior. Linear gradient elution (LGE) experiments were carried out to obtain a broad dataset ranging from pH 4.5 to 7.3 and from 50 to 375 mmol/L Na⁺ for model parameter determination. High loading LGE experiments were conducted with an increasing load from 0.5 up to 75.0 mg_bsAb/mL_resin. Thereby, pH-dependent empirical correlations for the activity coefficient of the solute protein, for the equilibrium constant of the self-dimerization process and for the shielding factor could be set up and ultimately incorporated into the SAS-SMA model. This pH-dependent SAS-SMA model was thus able to simulate anti-Langmuir behavior over extended ranges of pH, counterion concentration, and column loading. The model was confirmed by experimental verification of simulated linear pH gradient elutions up to a load of 75.0 mg_bsAb/mL_resin.

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.

Behavior of weakly adsorbing protein impurities in flow-through ion-exchange chromatography

Flow-through ion-exchange chromatography is frequently used in polishing biotherapeutics, but the factors that contribute to impurity persistence are incompletely understood. A large number of dilute impurities may be encountered that exhibit physicochemical diversity, making the flow-through separation performance highly sensitive to process conditions. The analysis presented in this work develops two novel correlations that offer transferable insights into the chromatographic behavior of weakly adsorbing impurities. The first, based on column simulations and validated experimentally, delineates the relative contributions of thermodynamic, transport, and geometric properties in dictating the initial breakthrough volumes of dilute species. The Graetz number for mass transfer was found to generalize the transport contributions, enabling estimation of a threshold in the equilibrium constant below which impurity persistence is expected. Impurity adsorption equilibria are needed to use this correlation, but such data are not typically available. The second relationship presented in this work may be used to reduce the experimental burden of estimating adsorption equilibria as a function of ionic strength. A correlation between stoichiometric displacement model parameters was found by consolidating isocratic retention data for over 200 protein-pH-resin combinations from the extant literature. Coupled with Yamamoto's analysis of linear gradient elution data, this correlation may be used to estimate retentivity approximately from a single experimental measurement, which could prove useful in predicting host-cell protein chromatographic behavior.

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.

Advanced score system and automated search strategies for parameter estimation in mechanistic chromatography modeling

Least squares estimation of unknown parameters from measurement data is a well-established standard method in chromatography modeling but can suffer from critical disadvantages. The description of real-world systems is generally prone to unaccounted mechanisms, such as dispersion in external holdup volumes, and systematic measurement errors, such as caused by pump delays. In this scenario, matching the shape between simulated and measured chromatograms has been found to be more important than the exact peak positions. We have therefore developed a new score system that separately accounts for the shape, position and height of individual peaks. A genetic algorithm is used for optimizing these multiple objectives. Even for non-conflicting objectives, this approach shows superior convergence in comparison to single-objective gradient search, while conflicting objectives indicate incomplete models or inconsistent data. In the latter case, Pareto optima provide important information for understanding the system and improving experiments. The proposed method is demonstrated with synthetic and experimental case studies of increasing complexity. All software is freely available as open source code (https://github.com/modsim/CADET-Match).

Kinetic investigation of protein adsorption into polyelectrolyte brushes by quartz crystal microbalance with dissipation: The implication of the chromatographic mechanism

With the growing concerns of polymer-grafted ion-exchange chromatography, the importance of protein adsorption on charged polymer-grafted surfaces cannot be stressed enough. However, a full understanding in adsorption in polymer brushes is still a great challenge due to the lack of in situ characterization technique. In this work, we use quartz crystal microbalance with dissipation to in situ investigate adsorption kinetics of γ-globulin and recombinant human lactoferrin on poly(3-sulfopropyl methacrylate) (pSPM) sensors prepared via atom transfer radical polymerization. With an increase of chain length and grafting density, great increasing amounts of proteins on pSPM-grafted sensors revealed that protein underwent a transition from monolayer to multilayer adsorption. It was attributed to direct protein binding into charged brushes, in which more binding sites involved and more coupled water lost. However, such a strong binding and rigid structure of proteins limited the protein transport in pSPM brushes and "chain delivery" effect. With an increase in grafting density, moreover, denser brushes hindered adjustment in protein conformation in pSPM brushes and further exacerbated protein transport in pSPM brushes. Furthermore, the influence of buffer pH and salt concentration further validated the ion exchange characteristics of protein adsorption into pSPM brushes. The research provided a variety of in situ evidence of protein binding and conformation evolution in pSPM brushes and elucidated mechanism of protein adsorption in pSPM brushes.

Experimental investigation and mass transfer modelling of 3D printed monolithic cation exchangers

3D printing has recently found application in chromatography as a means to create ordered stationary phases with improved separation efficiency. Currently, 3D printed stationary phases are limited by the lack of 3D printing materials suitable for chromatographic applications, and require a strict compromise in terms of desired resolution, model size and the associated print time. Modelling of mass transfer in 3D printed monoliths is also fundamental to understand and further optimise separation performance of 3D printed stationary phases. In this work, a novel 3D printing material was formulated and employed to fabricate monolithic cation exchangers (CEXs) with carboxyl functionalities. CEXs were printed with ligand densities of 0.7, 1.4, 2.1 and 2.8 mmol/g and used in batch adsorption experiments with lysozyme as model protein. All CEXs demonstrated high binding strength towards lysozyme, with maximum binding capacities of up to 108 mg/mL. The experimental results were described using mass transfer models based on lumped pore diffusion and lumped solid diffusion mechanisms adapted to reflect the complex geometry of the 3D printed monoliths. An exact 3D model as well as less computationally demanding 1D and 2D approximations were evaluated in terms of their quality to capture the experimental trend of batch adsorption kinetic data. Overall, the model results indicate that mass transfer in the fabricated CEXs is mostly controlled by pore diffusion at high protein concentrations in the mobile phase, with solid diffusion becoming important at low protein concentrations. Also, the kinetic data were approximated equally well by both the full 3D model as well as the 2D approximation, indicating leaner mathematical models of lower dimensionality can be employed to describe mass transfer in complex three dimensional geometries. We believe this work will help spur the development of 3D printable materials for separations and aid in the development of quantitative platforms to evaluate and optimise the performance of 3D printed monoliths.

Recent advances in protein chromatography with polymer-grafted media

The strategy of using polymer-grafted media is effective to create protein chromatography of high capacity and uptake rate, giving rise to an excellent performance in high-throughput protein separation due to its high dynamic binding capacity. Taking the scientific development and technological innovation of protein chromatography as the objective, this review is devoted to an overview of polymer-grafted media reported in the last five years, including their fabrication routes, protein adsorption and chromatography, mechanisms behind the adsorption behaviors, limitations of polymer-grafted media and chromatographic operation strategies. Particular emphasis is placed on the elaboration and discussion on the behaviors of ion-exchange chromatography (IEC) with polymer-grafted media because IEC is the most suitable chromatographic mode for this kind of media. Recent advances in both the theoretical and experimental investigations on polymer-grafted media are discussed by focusing on their implications to the rational design of novel chromatographic media and mobile phase conditions for the development of high-performance protein chromatography. It is concluded that polymer-grafted media are suitable for development of IEC and mixed-mode chromatography with charged and low hydrophobic ligands, but not for hydrophobic interaction chromatography with high hydrophobic ligands and affinity chromatography with ligands that have single binding site on the protein.

Developments and opportunities in continuous biopharmaceutical manufacturing

Today's biologics manufacturing practices incur high costs to the drug makers, which can contribute to high prices for patients. Timely investment in the development and implementation of continuous biomanufacturing can increase the production of consistent-quality drugs at a lower cost and a faster pace, to meet growing demand. Efficient use of equipment, manufacturing footprint, and labor also offer the potential to improve drug accessibility. Although technological efforts enabling continuous biomanufacturing have commenced, challenges remain in the integration, monitoring, and control of traditionally segmented unit operations. Here, we discuss recent developments supporting the implementation of continuous biomanufacturing, along with their benefits.

Retention and diffusion characteristics of oligonucleotides in a solid phase with polymer grafted anion-exchanger

In the chromatographic separation process of oligonucleotides (ONs), mechanistic understanding of their binding and diffusion processes is of significant importance to determine operating conditions in a fast and robust way. In this work, we determined the number of binding sites and the diffusivities of ONs in a polymer grafted anion exchange chromatography through linear gradient experiments (LGE) being carried out at selected four to five gradient slopes. Synthetic poly (T)s with length ranging from 3 to 90-mer were employed as a model of an antisense oligonucleotide with typical lengths of 10 - 30 bases. Comparison of the retention was also conducted between the grafted anion exchanger with a conventional ligand and an anion monolith disk. For the ONs up to 50 bases, the number of binding sites determined can be correlated with the length of ONs, and the grafted resin showed a better diffusion and narrower peak width compared to the nongrafted one. The retention behavior became similar for porous media when the longer ONs (> 50mer) were applied. The results obtained suggest that antisense ONs can be separated with grafted ligands without sacrificing mass transfer properties.