A multiscale modeling method for therapeutic antibodies in ion exchange chromatography.

The development of biopharmaceutical downstream processes relies on exhaustive experimental studies. The root cause is the poorly understood relationship between the protein structure of monoclonal antibodies (mAbs) and their macroscopic process behavior. Especially the development of preparative chromatography processes is challenged by the increasing structural complexity of novel antibody formats and accelerated development timelines. This study introduces a multiscale in silico model consisting of homology modeling, quantitative structure-property relationships (QSPR), and mechanistic chromatography modeling leading from the amino acid sequence of a mAb to the digital representation of its cation exchange chromatography (CEX) process. The model leverages the mAbs' structural characteristics and experimental data of a diverse set of 21 therapeutic antibodies to predict elution profiles of two mAbs that were removed from the training data set. QSPR modeling identified mAb-specific protein descriptors relevant for the prediction of the thermodynamic equilibrium and the stoichiometric coefficient of the adsorption reaction. The consideration of two discrete conformational states of IgG4 mAbs enabled prediction of split-peak elution profiles. Starting from the sequence, the presented multiscale model allows in silico development of chromatography processes before protein material is available for experimental studies.

Integrated process model for the prediction of biopharmaceutical manufacturing chromatography and adjustment steps.

A fundamental process understanding of an entire downstream process is essential for achieving and maintaining the high-quality standards demanded for biopharmaceutical drugs. A holistic process model based on mechanistic insights could support process development by identifying dependencies between process parameters and critical quality attributes across unit operations to design a holistic control strategy. In this study, state-of-the-art mechanistic models were calibrated and validated as digital representations of a biopharmaceutical manufacturing process. The polishing ion exchange chromatography steps (Q Sepharose FF, Poros 50 HS) were described by a transport-dispersive model combined with a colloidal particle adsorption model. The elution behavior of four size variants was analyzed and included in the model. Titration curves of pH adjustments were simulated using a mean-field approach considering interactions between the protein of interest and other ions in solution. By including adjustment steps the important process control inputs ionic strength, dilution, and pH were integrated. The final process model was capable to predict online and offline data at manufacturing scale. Process variations at manufacturing scale of 94 runs were adequately reproduced by the model. Furthermore, the process robustness against a 20% input variation of concentration, size variant and ion composition, volume, and pH could be confirmed with the model. The presented model demonstrates the potential of the integrated approach for predicting manufacturing process performance across scales and operating units.

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.

In silico process characterization for biopharmaceutical development following the quality by design concept.

With the quality by design (QbD) initiative, regulatory authorities demand a consistent drug quality originating from a well-understood manufacturing process. This study demonstrates the application of a previously published mechanistic chromatography model to the in silico process characterization (PCS) of a monoclonal antibody polishing step. The proposed modeling workflow covered the main tasks of traditional PCS studies following the QbD principles, including criticality assessment of 11 process parameters and establishment of their proven acceptable ranges of operation. Analyzing effects of multi-variate sampling of process parameters on the purification outcome allowed identification of the edge-of-failure. Experimental validation of in silico results demanded approximately 75% less experiments compared to a purely wet-lab based PCS study. Stochastic simulation, considering the measured variances of process parameters and loading material composition, was used to estimate the capability of the process to meet the acceptance criteria for critical quality attributes and key performance indicators. The proposed workflow enables the implementation of digital process twins as QbD tool for improved development of biopharmaceutical manufacturing processes.

Modeling the impact of amino acid substitution in a monoclonal antibody on cation exchange chromatography.

A vital part of biopharmaceutical research is decision making around which lead candidate should be progressed in early-phase development. When multiple antibody candidates show similar biological activity, developability aspects are taken into account to ease the challenges of manufacturing the potential drug candidate. While current strategies for developability assessment mainly focus on drug product stability, only limited information is available on how antibody candidates with minimal differences in their primary structure behave during downstream processing. With increasing time-to-market pressure and an abundance of monoclonal antibodies (mAbs) in development pipelines, developability assessments should also consider the ability of mAbs to integrate into the downstream platform. This study investigates the influence of amino acid substitutions in the complementarity-determining region (CDR) of a full-length IgG1 mAb on the elution behavior in preparative cation exchange chromatography. Single amino acid substitutions within the investigated mAb resulted in an additional positive charge in the light chain (L) and heavy chain (H) CDR, respectively. The mAb variants showed an increased retention volume in linear gradient elution compared with the wild-type antibody. Furthermore, the substitution of tryptophan with lysine in the H-CDR3 increased charge heterogeneity of the product. A multiscale in silico analysis, consisting of homology modeling, protein surface analysis, and mechanistic chromatography modeling increased understanding of the adsorption mechanism. The results reveal the potential effects of lead optimization during antibody drug discovery on downstream processing.

Introduction and clearance of beta-glucan in the downstream processing of monoclonal antibodies.

ß-Glucan process-related impurities can be introduced into biopharmaceutical products via upstream or downstream processing or via excipients. This study obtained a comprehensive process-mapping dataset for five monoclonal antibodies to assess ß-glucan introduction and clearance during development and production runs at various scales. Overall, 198 data points were available for analysis. The greatest ß-glucan concentrations were found in the depth-filtration filtrate (37-2,745 pg/ml). Load volume correlated with ß-glucan concentration in the filtrate, whereas flush volume was of secondary importance. Cation-exchange chromatography significantly cleared ß-glucans. Furthermore, ß-glucan leaching from the Planova 20N virus removal filter was reduced by increasing the flush volume (1 vs. 10 L/m2 ). ß-glucan concentrations after filter flush with 10 L/m2 were consistently <10 pg/ml. No or only limited ß-glucan clearance was attained via ultrafiltration/diafiltration (UF/DF). However, during the first run with monoclonal antibody (mAb) 4, ß-glucan concentration in the UF/DF retentate was 10.8 pg/mg, potentially due to ß-glucan leaching from the first run with a regenerated cellulose membrane. Overall, ß-glucan levels in the final mAb drug substance were 1-12 pg/mg. Assuming high doses of 1,000-5,000 mg, a ß-glucan contamination at 20 pg/mg would translate to 20-100 ng/dose, which is below the previously suggested threshold for product safety (≤500 ng/dose).

Cross-scale quality assessment of a mechanistic cation exchange chromatography model.

Cation exchange chromatography (CEX) is an essential part of most monoclonal antibody (mAb) purification platforms. Process characterization and root cause investigation of chromatographic unit operations are performed using scale down models (SDM). SDM chromatography columns typically have the identical bed height as the respective manufacturing-scale, but a significantly reduced inner diameter. While SDMs enable process development demanding less material and time, their comparability to manufacturing-scale can be affected by variability in feed composition, mobile phase and resin properties, or dispersion effects depending on the chromatography system at hand. Mechanistic models can help to close gaps between scales and reduce experimental efforts compared to experimental SDM applications. In this study, a multicomponent steric mass-action (SMA) adsorption model was applied to the scale-up of a CEX polishing step. Based on chromatograms and elution pool data ranging from laboratory- to manufacturing-scale, the proposed modeling workflow enabled early identification of differences between scales, for example, system dispersion effects or ionic capacity variability. A multistage model qualification approach was introduced to measure the model quality and to understand the model's limitations across scales. The experimental SDM and the in silico model were qualified against large-scale data using the identical state of the art equivalence testing procedure. The mechanistic chromatography model avoided limitations of the SDM by capturing effects of bed height, loading density, feed composition, and mobile phase properties. The results demonstrate the applicability of mechanistic chromatography models as a possible alternative to conventional SDM approaches.

Straightforward method for calibration of mechanistic cation exchange chromatography models for industrial applications.

Mechanistic modeling of chromatography processes is one of the most promising techniques for the digitalization of biopharmaceutical process development. Possible applications of chromatography models range from in silico process optimization in early phase development to in silico root cause investigation during manufacturing. Nonetheless, the cumbersome and complex model calibration still decelerates the implementation of mechanistic modeling in industry. Therefore, the industry demands model calibration strategies that ensure adequate model certainty in a limited amount of time. This study introduces a directed and straightforward approach for the calibration of pH-dependent, multicomponent steric mass action (SMA) isotherm models for industrial applications. In the case investigated, the method was applied to a monoclonal antibody (mAb) polishing step including four protein species. The developed strategy combined well-established theories of preparative chromatography (e.g. Yamamoto method) and allowed a systematic reduction of unknown model parameters to 7 from initially 32. Model uncertainty was reduced by designing two representative calibration experiments for the inverse estimation of remaining model parameters. Dedicated experiments with aggregate-enriched load material led to a significant reduction of model uncertainty for the estimates of this low-concentrated product-related impurity. The model was validated beyond the operating ranges of the final unit operation, enabling its application to late-stage downstream process development. With the proposed model calibration strategy, a systematic experimental design is provided, calibration effort is strongly reduced, and local minima are avoided.

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

The increasing demand for cost-efficient manufacturing of biopharmaceuticals has been the main driving force for the development of novel chromatography resins, which resulted in the development of multimodal or mixed-mode chromatographic resins. Most of them combine electrostatic and hydrophobic functionalities and are designed to deliver unique selectivity and increased binding capacities also at increased ionic strength. However, the mechanism of the protein-resin interaction in mixed-mode chromatography is still not fully understood. The performance of protein separations in mixed-mode chromatography is consequently difficult to predict. In this work, we present a model combining both salt and pH dependence to characterize and to predict protein retention in mixed-mode chromatography. The model parameters are determined based on simple linear pH gradient elution experiments at different ionic strengths and they are directly transferable for the prediction of salt-induced elution at fixed pH. Validity of the model is demonstrated for a bispecific antibody and its product-related impurities.

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.

Solvent modulation strategy for superior antibody monomer/aggregate separation in cation exchange chromatography.

Cation exchange chromatography (CEX) is an integral part of many downstream processes for monoclonal antibodies (mAbs). However, in some cases CEX methods with standard mobile phase conditions do not lead to a sufficient removal of soluble antibody aggregates. The addition of neutral polymers such as polyethylene glycol (PEG) to the mobile phase can improve the separation of proteins in IEC remarkably. The applicability of this solvent modulation technique is limited by protein precipitation at higher PEG concentrations. To overcome this limitation solubility enhancers like polyols and amino acids can be added to the mobile phase. These additives are known to inhibit PEG-induced protein precipitation in solution. This new solvent modulation strategy was tested with three different mAbs on two different CEX resins in the presence of PEG in combination with various solubility enhancers. In order to assess the general applicability of this method, mAbs were selected that show major differences with respect to their sensitivity to PEG-induced precipitation and monomer/aggregate resolution performance that is achieved by CEX under standard conditions. For all three mAbs precipitation could be prevented without elimination of the positive PEG-effect. The addition of solubility enhancers gives access to improved separation at elevated PEG concentrations and high protein loadings without running into precipitation issues. Our data indicate that this method is generically applicable and leads to a superior antibody monomer/aggregate separation.

Solvent modulated linear pH gradient elution for the purification of conventional and bispecific antibodies: Modeling and application.

Classical ion-exchange chromatography using a linear salt gradient to elute the adsorbed protein at fixed pH is the most common method to separate product-related impurities during downstream processing of biopharmaceuticals. Linear pH gradient elution provides a useful alternative by separating proteins in a linear pH gradient at fixed salt concentration. Although linear pH gradient elution provides excellent selectivity, it is rarely encountered in industrial purification processes. Here, a stoichiometric displacement model is used to characterize pH gradient elution based on simple linear gradient elution experiments. Protein retention behavior is described with respect to the pH dependencies of the characteristic binding charge and the equilibrium constant of the ion exchange reaction. Furthermore, the influence of solvent composition using PEG as a mobile phase modifier is investigated. Validity and applicability of the model are demonstrated for the purification of a conventional monoclonal antibody from soluble aggregates and for a novel bispecific antibody format containing a unique product-related impurity profile. pH step elution protocols are derived from model calculations without further optimization experiments necessary.

Mechanism of improved antibody aggregate separation in polyethylene glycol-modulated cation exchange chromatography.

Ion-exchange chromatography is used in biopharmaceutical downstream processes to reduce product-related impurity levels. Because protein aggregate levels can be considered as a critical quality attribute, the removal of aggregated protein species is of primary importance. The addition of polyethylene glycol (PEG) to the mobile phase in ion-exchange chromatography was found to significantly improve the chromatographic separation of monomers from aggregates. In this work, linear gradient elution experiments with monomeric and aggregated samples of a monoclonal antibody were performed on a strong cation exchange resin at different PEG concentrations to investigate the underlying effects responsible for the observed selectivity improvement. PEG is well known to be excluded from a surface layer volume around the protein and the stationary phase; thus, enhancing adsorption of the preferentially hydrated protein to the hydrated stationary phase. The exclusion volume depends on the accessible surface area of the protein leading to a stronger influence of PEG on larger protein species and thus an improved separation of monomer and aggregates. This hypothesis could be consolidated comparing the distribution equilibrium in PEG solution to that in water by calculating equilibrium constants and transfer free energies using the chromatographic data from the linear gradient elution experiments performed at different pH values.