Steric Mass Action Model Research Articles

Mechanistic modeling of minute virus of mice surrogate removal by anion exchange chromatography in micro scale

Biopharmaceutical products are often produced in Chinese hamster ovary (CHO) cell cultures that are vulnerable to virus infections. Therefore, it is a regulatory requirement that downstream purification steps for biopharmaceuticals can remove viruses from feedstocks. Anion exchange chromatography (AEX) is one of the downstream unit operations that is most frequently used for this purpose and claimed for its capability to remove viruses. However, the impact of various process parameters on virus removal by AEX is still not fully understood. Mechanistic modeling could be a promising way to approach this gap, as these models require comparatively few experiments for calibration. This makes them a valuable tool to improve understanding of viral clearance, especially since virus spiking studies are costly and time consuming.In this study, we present how the virus clearance of a MVM mock virus particle by Q Sepharose FF resin can be described by mechanistic modeling. A lumped kinetic model was combined with a steric mass action model and calibrated at micro scale using three linear gradient experiments and an incremental step elution gradient. The model was subsequently verified for its capability to predict the effect of different sodium chloride concentrations, as well as residence times, on virus clearance and was in good agreement with the LRVs of the verification runs. Overall, models like this could enhance the mechanistic understanding of viral clearance mechanisms and thereby contribute to the development of more efficient and safer biopharmaceutical downstream processes.

Pore-blocking steric mass-action model for adsorption of bioparticles

The steric mass-action (SMA) model has been widely reported to describe the adsorption of proteins in different types of chromatographic adsorbents. Here in the present work, a pore-blocking steric mass-action model (PB-SMA) was developed for the adsorption of large-size bioparticles, which usually exhibit the unique pore-blocking characteristic on the adsorbent and thus lead to a fraction of ligands in the deep channels physically inaccessible to bioparticles adsorption, instead of being shielded due to steric hindrance by adsorbed bioparticles. This unique phenomenon was taken into account by introducing an additional parameter, Lin, which is defined as the inaccessible ligand densities in the physically blocked pore area, into the PB-SMA model. This fraction of ligand densities (Lin) will be deducted from the total ligand (Lt) for model development, thus the steric factor (σ) in the proposed PB-SMA will reflect the steric shielding effect on binding sites by adsorbed bioparticles more accurately than the conventional SMA model, which assumes that all ligands on the adsorbent have the same accessibility to the bioparticles. Based on a series of model assumptions, a PB-SMA model was firstly developed for inactivated foot-and-mouth disease virus (iFMDV) adsorption on immobilized metal affinity chromatography (IMAC) adsorbents. Model parameters for static adsorption including equilibrium constant (K), characteristic number of binding sites (n), and steric factor (σ) were determined. Compared with those derived from the conventional SMA model, the σ values derived from the PB-SMA model were dozens of times smaller and much closer to the theoretical maximum number of ligands shielded by a single adsorbed iFMDV, indicating the modified model was more accurate for bioparticles adsorption. The applicability of the PB-SMA model was further validated by the adsorption of hepatitis B surface antigen virus-like particles (HBsAg VLPs) on an ion exchange adsorbent with reasonably improved accuracy. Thus, it is considered that the PB-SMA model would be more accurate in describing the adsorption of bioparticles on different types of chromatographic adsorbents.

A model-based performance analysis of integrated chromatography-ultrafilter separation systems for monoclonal antibody (mAb) manufacturing

Robust and accurate modelling of bioprocess systems offers the opportunity to visualise strategies for rapid-scale up of production platforms from benchtop to industrial scale, but few studies investigate how mechanistic and hybrid models can be used to design integrated bio-manufacturing. This is especially true for downstream purification technologies used to separate mAbs from culture by-products, e.g. host cell proteins. Polishing chromatography (cation-exchange mode) is commonly used to remove these by-products, but optimal bind and elution operation of these columns is complex. Ultrafiltration is typically applied in conjunction with diafiltration post-polishing chromatography in order to obtain suitable final product titers and excipient concentrations. This study presents a combination of dynamic models to probe batch polishing chromatography and ultrafiltration operating strategies achieving industrial specifications for recovery yield and mAb titer. A series of elution and filtration strategies are implemented, resulting in a total of 40 flowsheets explored. A steric mass action model with 7 pH-dependent parameters is employed to simulate scale-up polishing chromatography column behaviour. Moreover, a published gel layer ultrafiltration model based on Darcy’s law is implemented to purify the outlet of the polishing chromatography column. Strategies that are successful in achieving the target 90% recovery yield and 100 g L−1 concentration specifications are compared via a comprehensive analysis, to deduce the operational protocols which offer minimised salt consumption and pressure drop whilst respecting design criteria.

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 mgbsAb/mLresin. 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 mgbsAb/mLresin.

Parameter-by-parameter method for steric mass action model of ion exchange chromatography: Simplified estimation for steric shielding factor

Mechanistic models play a crucial role in the process development and optimization of ion-exchange chromatography (IEC). Recent researches in steric mass action (SMA) model have heightened the need for better estimation of nonlinear parameter, steric shielding factor σ. In this work, a straightforward approach combination of simplified linear approximation (SLA) and inverse method (IM) was proposed to initialize and further determine σ, respectively. An existed, unique, and positive σ can be derived from SLA. Compared with linear approximation (LA) developed in our previous study, σ of the multi-component system can be calculated easily without solving the complex system of linear equations, leading to a time complexity reduction from O(n3) to O(n). The proposed method was verified first in numerical experiments about the separation of three charge variants. The calculated σ was more reasonable than that of LA, and the error of elution profiles with the parameters estimated by SLA+IM was only one-sixth of that by LA in numerical experiments. Moreover, the error accumulation effect could also be reduced. The proposed method was further confirmed in real-world experiments about the separation of monomer-dimer mixtures of monoclonal antibody. The results gave a lower error and better physical understanding compared to LA. In conclusion, SLA+IM developed in the present work provides a novel and straightforward way to determine σ. This simplification would help to save the effort of calibration experiments and accelerate the process development for the multi-component IEC separation.

Parameter-by-parameter method for steric mass action model of ion exchange chromatography: Theoretical considerations and experimental verification

Ion exchange chromatography (IEC) is one of the most widely-used techniques for protein separation and has been characterized by mechanistic models. However, the time-consuming and cumbersome model calibration hinders the application of mechanistic models for process development. A new methodology called "parameter-by-parameter method (PbP)" was proposed with mechanistic derivations of the steric mass action (SMA) model of IEC. The protocol includes four steps: (1) first linear regression (LR1) for characteristic charge; (2) second linear regression (LR2) for equilibrium coefficient; (3) linear approximation (LA) for shielding factor; (4) inverse method (IM) for kinetic coefficient. Four SMA parameters could be one-by-one determined in sequence, reducing the number of unknown parameters per species from four to one, and predicting almost consistent retention. Numerical single-component experiments were investigated firstly, and the PbP method showed excellent agreement between experiments and simulations. The effects of loadings on the PbP and Yamamoto methods were compared. It was found that the PbP method had higher accuracy and robustness than the Yamamoto method. Moreover, a five-experiment strategy was suggested to implement the PbP method, which is straightforward to reduce the cost of calibration experiments. Finally, a real-world multi-component separation was challenged and further confirmed the feasibility of the PbP method. In general, the proposed method can not only reliably estimate the SMA parameters with comprehensive physical understanding but also accurately predict retention over a wide range of loading conditions.

Application of the Steric Mass Action formalism for modeling under high loading conditions: Part 2. Investigation of high loading and column overloading effects

The application of a model-based approach for industrial chromatography development requires the capability of the model to describe protein elution under high loading and overloading conditions. In a previous work, an extensive dataset was created to model the elution behavior of a bispecific antibody (bsAb) on the strong cation exchange resin POROS™ XS. Thereby, the pH-dependence of the model parameters in the Steric Mass Action (SMA) model could be examined and described over a pH range of 4.5 to 8.9. However, discrepancies between simulated and experimental data were observed under high loading and overloading conditions, particularly in the lower pH range (pH 4.5 to 5.3) and in the higher pH range (pH 6.0 to 9.0). In this work, these discrepancies are studied by performing new experiments which show that these differences were primarily not caused by limitations of the SMA model. At lower pH values, overloading phenomena such as protein breakthrough during the loading phase, additional peaks, and peak shoulders occurred. The application of various experiments performed with different Na+ concentrations and different loading times during sample loading revealed that intraparticle diffusion effects and conformational changes of the bsAb are responsible for these overloading phenomena at low pH. The applied lumped rate mass transfer model is not adequate and should be extended to consider these effects. At higher pH, the assumption of describing the bsAb's elution behavior with only one simulated species was insufficient to predict complex peak shapes that arise because of multi-component elution of the bsAb's charge variants. The extension of the model to a simple multi-component system consisting of two variants allowed the prediction of a majority of the complex elution profiles.

Application of the Steric Mass Action formalism for modeling under high loading conditions: Part 1. Investigation of the influence of pH on the steric shielding factor

In ion exchange chromatography, the Steric Mass Action (SMA) formalism is frequently used to simulate sorption processes at low and high column load conditions. To apply the SMA model for describing protein elution over wide ranges of pH, it is necessary to use pH-dependent model parameters. In the past, some publications have already described the pH-dependence of the characteristic protein charge and the equilibrium constant, while the influence of pH on the steric shielding factor has been mostly neglected. In this work, the pH-dependences of all relevant model parameters, including the shielding factor, were investigated, described, and implemented into the SMA model. Therefore, the elution behavior of a bispecific monoclonal antibody on the strong cation exchange resin POROS™ XS was modeled over broad ranges of pH, salt concentrations, and protein concentrations. Linear gradient elution experiments were performed to generate an extensive data set by using increasing column loadings from 0.5 up to 75.0 mgbsAb/mLresin. By using an inverse peak fitting method, shielding factors were estimated at various pH values ranging from 4.5 to 8.9. The results showed that an increasing buffer pH resulted in strongly increasing shielding factors. A semi-empirical correlation describing the shielding factor as a function of pH was established and implemented into the SMA formalism. This approach led to precise prediction of protein elution behavior using a single-component simulation. This was demonstrated by accurate simulation of linear salt, pH and dual gradient elution experiments conducted under high loading conditions.

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.

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.

Precision analysis for the determination of steric mass action parameters using eight tobacco host cell proteins

Plants are advantageous as biopharmaceutical manufacturing platforms because they allow the economical and scalable upstream production of proteins, including those requiring post-translational modifications, but do not support the replication of human viruses. However, downstream processing can be more labor-intensive compared to fermenter-based systems because the product is often mixed with abundant host cell proteins (HCPs). Modeling chromatographic separation can minimize the number of process development experiments and thus reduce costs. An important part of such modeling is the sorption isotherm, such as the steric mass action (SMA) model, which describes the multicomponent protein–salt equilibria established in ion-exchange systems. Here we purified ten HCPs, including 2-Cys-peroxiredoxin, from tobacco (Nicotiana tabacum and N. benthamiana). For eight of these HCPs, we obtained sufficient quantities to determine the SMA binding parameters (KSMA and ν) under different production-relevant conditions. We studied the parameters for 2-Cys-peroxiredoxin on Q-Sepharose HP in detail, revealing that pH, resin batch and buffer batch had little influence on KSMA and ν, with coefficients of variation (COVs) less than 0.05 and 0.21, respectively. In contrast, the anion-exchange resins SuperQ-650S, Q-Sepharose FF and QAE-550C led to COVs of 0.69 for KSMA and 0.05 for ν, despite using the same quaternary amine functional group as Q-Sepharose HP. Plant cultivation in summer vs winter resulted in COVs of 0.09 for KSMA and 0.02 for ν, revealing a small impact compared to COVs of 17.15 for KSMA and 0.20 for ν when plants were grown in different settings (climate-controlled phytotron vs greenhouse). We conclude that plant cultivation can substantially affect protein properties and the resulting SMA parameters. Accordingly, plant growth but also protein purification and characterization for chromatography model building should be tightly controlled and well documented.

Mechanistic modeling based process development for monoclonal antibody monomer-aggregate separations in multimodal cation exchange chromatography

This study demonstrates how multimodal cation exchange chromatographic systems can be successfully employed to purify an IgG4 monomer from three distinct aggregate species. In addition, the steric mass action model is shown to be capable of facilitating the development of effective bind/elute processes for aggregate removal. A variety of multimodal anion and cation exchange resin materials and conditions were initially screened for both selectivity and recovery of the product. While the multimodal anion exchangers exhibited significant recovery issues, the Capto MMC and MMC ImpRes resin systems were observed to have good recoveries and some selectivity for these challenging separations under linear gradient conditions. Mechanistic modeling was then explored as a means to expedite the development of a bind/elute process for decreasing the aggregate content of this challenging monoclonal antibody mixture. The retention behavior of the monomer and the higher molecular weight species under different linear gradient conditions were used to estimate the SMA parameters of the proteins on both the Capto MMC and MMC ImpRes systems. A range of simulations were then carried out to determine an efficient bind/elute process for the removal of higher molecular weight species while also obtaining a good yield of the monomer in both resin systems. Finally, bind/elute experiments were carried out under the suggested simulation conditions for each resin system and were shown to be in good agreement with the theoretical predictions, with purities and yields of 99% and 78.6% for Capto MMC and 99.3% and 87.9% for Capto MMC ImpRes, respectively. The simple approach described in this paper presents a rapid and useful method for model-based process development of antibody monomer-aggregate separations with multimodal cation exchange chromatography.

Multi‐state steric mass action model applied to binding of mAb on tentacle resins under high loading conditions

Multi‐state steric mass action model applied to binding of mAb on tentacle resins under high loading conditions

Mechanistic Modeling of Reversed-Phase Chromatography of Insulins within the Temperature Range 10-40 °C.

In the many published theories on the retention in reversed-phase chromatography (RPC), the focus is generally on the effect of the concentration of the mobile phase modulator(s), although temperature is known to have a significant influence both on the retention and on the selectivity between the adsorbates. The aim of this study was to investigate and model the combined effects of the temperature and the modulator concentrations on RPC of three insulin variants. KCl and ethanol were used as mobile phase modulators, and the experiments were performed on two different adsorbents, with C18 and C4 ligands. The temperature dependence was investigated for the interval 10–40 °C and at two different concentrations of each modulator. The model is derived from the expression for the adsorption equilibrium, which assumes that ethanol is adsorbed to the ligands and displaced by the insulin molecules, similar to the displacement of counterions in the steric mass-action model for ion-exchange chromatography. A good model fit to the new linear-range retention data was achieved by only adding and calibrating three parameters for the temperature dependence of the equilibrium. We found that a lower temperature results in a longer retention time for all adsorbates, adsorbents, and modulator concentrations used in this study, indicating that the adsorption process is enthalpy-driven. A comparison of the different contributions to the temperature dependence revealed that the large contribution from the equilibrium constant is dampened by the significant contributions of the opposite sign from the changes in activity coefficients of insulins and ethanol. Neglect of these effects when comparing different adsorbents and modulators might yield incorrect conclusions because the equilibrium constant varies with both, whereas the activity coefficients should be independent of the adsorbent. As expected, the conditions that promote higher retention also give a higher selectivity between the adsorbates. Nonetheless, in relation to its effect on the retention, the influence of the KCl concentration on the selectivity was significantly stronger than that of the temperature or that of the ethanol concentration.

Multi-state steric mass action model and case study on complex high loading behavior of mAb on ion exchange tentacle resin

Tentacle resins for IEX are increasingly applied in preparative chromatography for their higher selectivity and higher capacities in comparison to IEX resins without tentacles. However, tentacle resins are often observed to cause unusual elution behavior of monoclonal antibodies under high loading conditions. Understanding this elution behavior is important for a quality by design approach, as it is now mandated by regulatory agencies. A model-based analysis of load, wash and gradient elution is performed for a monoclonal antibody (mAb) on Fractogel SO3−. Four experiments with increasing loaded mass show complex peak shapes and formation of a shoulder under overloaded conditions. We hypothesize that the observed peak shapes are caused by mAbs binding in multiple states on the tentacle ion-exchange resin. A new multi-state SMA binding model is used for testing this hypothesis. A two-state binding model is found to quantitatively reproduce all four experiments. An in-depth analysis reveals that the shoulder formation under overloaded conditions can be explained by multi-state binding that particularly manifests in rapid but weak re-adsorption of eluting molecules near the column end. The introduced multi-state SMA model combines features of the so-called spreading model (multiple bound states) and of the standard SMA model (salt dependency). It is by no means limited to ion-exchange chromatography on tentacle resins, but the same concept can be applied for studying systems that are based on other physical mechanisms. The new model can potentially improve mechanistic understanding and facilitate quantitative simulation of various phenomena, such as caused by reorientation, reconformation or unfolding of bound species. Similar concepts can be applied for studying surface-induced aggregation and denaturation.

Model-Based Investigation on the Mass Transfer and Adsorption Mechanisms of Mono-Pegylated Lysozyme in Ion-Exchange Chromatography.

Recent studies highlighted the potential of PEGylated proteins to improve stabilities and pharmacokinetics of protein drugs. Ion-exchange chromatography (IEX) is among the most frequently used purification methods for PEGylated proteins. However, the underlying physical mechanisms allowing for a separation of different PEGamers (proteins with a varying number of attached PEG molecules) are not yet fully understood. In this work, mechanistic chromatography modeling is applied to gain a deeper understanding of the mass transfer and adsorption/desorption mechanisms of mono-PEGylated proteins in IEX. Using a combination of the general rate model (GRM) and the steric mass action (SMA) isotherm, simulation results in good agreement with the experimental data are achieved. During linear gradient elution of proteins attached with PEG of different molecular weight, similar peak heights, and peak shapes at constant gradient length are observed. A superimposed effect of increased desorption rate and reduced diffusion rate as a function of the hydrodynamic radius of PEGylated proteins is identified to be the reason of this anomaly. That is why the concept of the diffusion-desorption-compensation effect is proposed. In addition to the altered elution orders, PEGylation results in a considerable decrease of maximum binding capacity. By using the SMA model in a kinetic formulation, the adsorption behavior of PEGylated proteins in the highly concentrated state is described mechanistically. An exponential increase in the steric hindrance effect with increasing PEG molecular weight is observed. This suggests the formation of multiple PEG layers in the interstitial space between bound proteins and an associated shielding of ligands on the adsorber surface to be the cause of the reduced maximum binding capacity. The presented in silico approach thus complements the hitherto proposed theories on the binding mechanisms of PEGylated proteins in IEX.

ACS Award In Separations Science & Technology: Steven M. Cramer

AWARDS ACS Award In Separations Science & Technology: Steven M. Cramer ShareShare onFacebookTwitterWechatLinked InRedditEmail C&EN, 2016, 94 (1), pp 34–43January 4, 2016Cite this:C&EN 94, 1, 34-43Sponsor: Waters Corp. Citation: For contributions to a molecular-level understanding, adsorption isotherm formalisms, and the development and application of chromatographic bioprocesses for the purification of biopharmaceuticals. Current position: William Weightman Walker Professor of Polymer Engineering, Rensselaer Polytechnic Institute Education: B.S., biomedical engineering, Brown University; M.S., Ph.D., chemical engineering, Yale University Cramer on what inspires him:“The creative process of solving a research problem or coming up with a new research idea is similar to the process of jazz improvisation or writing a musical piece. In both, you need to input sufficient information and then make room for the ideas to spring up from the intuition or subconscious mind. For me this can occur during a walk in nature, playing music, exercising, dreaming, or having an animated discussion with my students or colleagues.” What his colleagues say:“His original paper on the steric mass action model for ion exchange is one of the most influential papers in the field and represented a turning point in the industry where accurate models could then be employed to develop, optimize, and control large-scale ion exchange protein purification processes.”—Robin D. Rogers, McGill University

Application of linear pH gradients for the modeling of ion exchange chromatography: Separation of monoclonal antibody monomer from aggregates.

The mobile phase pH is a key parameter of every ion exchange chromatography process. However, mechanistic insights into the pH influence on the ion exchange chromatography equilibrium are rare. This work describes a mechanistic model capturing salt and pH influence in ion exchange chromatography. The pH dependence of the characteristic protein charge and the equilibrium constant is introduced to the steric mass action model based on a protein net charge model considering the number of amino acids interacting with the stationary phase. This allows the description of the adsorption equilibrium of the chromatographed proteins as a function of pH. The model parameters were determined for a monoclonal antibody monomer, dimer, and a higher aggregated species based on a manageable set of pH gradient experiments. Without further modification of the model parameters the transfer to salt gradient elution at fixed pH is demonstrated. A lumped rate model was used to predict the separation of the monoclonal antibody monomer/aggregate mixture in pH gradient elution and for a pH step elution procedure-also at increased protein loadings up to 48 g/L packed resin. The presented model combines both salt and pH influence and may be useful for the development and deeper understanding of an ion exchange chromatography separation.

Determination of adsorption isotherm parameters for minor whey proteins by gradient elution preparative liquid chromatography

Ion-Exchange Chromatography (IEC) techniques have been extensively investigated in protein purification processes, due to the more selective and milder separation steps. To date, existing studies of minor whey proteins fractionation in IEC have primarily been conducted as batch uptake studies, which require more experimental search space, time and materials. In this work, the selected resin's (SP Sepharose FF) equilibrium and dynamic binding capacity were first investigated. Next, adsorption of the pure binary mixture of lactoperoxidase and lactoferrin was studied to calibrate steric mass action (SMA) model using a simplified approach with data from single column experiments. The calibrated model was then verified by performing factorial-design based experiments for various process operating conditions assessing process performance on a larger bed height column. The model predicted results demonstrated a realistic agreement with the experiments providing reproducible column elution profile and reduced experimental work. Finally, whey protein isolate was used to evaluate model parameters in real conditions. Results obtained herein are suitable for future large scale applications.

Calibration‐free inverse modeling of ion‐exchange chromatography in industrial antibody purification

The identification of optimal process parameters for the isolation of a target component from multicomponent mixtures is especially challenging in industrial applications. With constantly increasing time‐to‐market pressure, screening a large parameter space is not feasible and design‐of‐experiment approaches with few experiments might fail due to dynamic and nonlinear reactions to small parameter changes. Model‐based optimization can determine optimal operating conditions, once the model has been calibrated to the specific process step. In this work, parameters for the steric mass action model were estimated for the target protein and three impurities of an industrial antibody cation‐exchange purification step using only chromatograms at different wavelengths and additional fraction analyses with size exclusion chromatography. Information on the molar or mass concentrations in the feed are not available. The model‐based optimization results coincide with conventional chromatogram‐based optimization.