Simulation model for overloaded monoclonal antibody variants separations in ion-exchange chromatography

Guélat, Bertrand; Ströhlein, Guido; Lattuada, Marco; Delegrange, Lydia; Valax, Pascal; Morbidelli, Massimo

doi:10.1016/j.chroma.2012.06.081

Cited by 56 publications

(28 citation statements)

References 32 publications

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“…Although the B value is not identical to the protein net charge of the protein, the pH dependence of parameter B follows the protein titration curve. The pH dependence of B can be modeled using purely empirical correlations or correlations based on a protein net charge model . The empirical correlations resulted in a reasonable good description of the pH dependence of B although the titration curve behavior cannot be approximated by these empirical correlations.…”

Section: Resultsmentioning

confidence: 99%

“…Nonstoichiometric ion‐exchange models based on a plane–sphere geometry with homogeneous charge density on the stationary phase and the protein neglect such binding orientations. These rather simple models have provided comparable predictions of trends in adsorption equilibrium for the more detailed models because of Boltzmann‐weighted averaging of the configuration‐dependent energies .…”

Section: Resultsmentioning

confidence: 99%

“…The large number of parameters of our net charge based approach precludes the determination of the B –pH based on this limited salt gradient data set. A net charge model in which all basic amino acids are summed up to a single p K a parameter can be used, but fails at pH values above pH 7 (data not shown).…”

Section: Resultsmentioning

confidence: 99%

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Modeling of salt and pH gradient elution in ion-exchange chromatography

2014

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The separation of proteins by internally and externally generated pH gradients in chromatofocusing on ion-exchange columns is a well-established analytical method with a large number of applications. In this work, a stoichiometric displacement model was used to describe the retention behavior of lysozyme on SP Sepharose FF and a monoclonal antibody on Fractogel SO3 (S) in linear salt and pH gradient elution. The pH dependence of the binding charge B in the linear gradient elution model is introduced using a protein net charge model, while the pH dependence of the equilibrium constant is based on a thermodynamic approach. The model parameter and pH dependences are calculated from linear salt gradient elutions at different pH values as well as from linear pH gradient elutions at different fixed salt concentrations. The application of the model for the well-characterized protein lysozyme resulted in almost identical model parameters based on either linear salt or pH gradient elution data. For the antibody, only the approach based on linear pH gradients is feasible because of the limited pH range useful for salt gradient elution. The application of the model for the separation of an acid variant of the antibody from the major monomeric form is discussed.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Modeling of salt and pH gradient elution in ion-exchange chromatography

2014

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“…In both cases, the model parameters are regressed to a limited number of experimental measurements. For ion exchange chromatography several isotherm models are available including Langmuir [1][2][3][4][5], steric mass action (SMA) [6][7][8], and statistical thermodynamic (ST) models [9][10][11]. Similarly, various rate models are available including models that assume the adsorption is kinetically limited, lumped rate models based on a linear driving force approximation, and the general rate model that describes the detailed mechanisms associated with diffusional mass transfer [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Systematic interpolation method predicts protein chromatographic elution from batch isotherm data without a detailed mechanistic isotherm model

Creasy

Barker

Yan

et al. 2015

Biotechnology Journal

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A method is developed to predict protein chromatographic behavior from batch isotherm using a a systematic empirical interpolation (EI) scheme and without relying on a mechanistic description of the dependence of protein binding on protein and salt concentration. Coupled with a lumped kinetic model with rate parameters determined from HETP measurements for non-binding conditions, the EI scheme is used to numerically predict the column behavior. For two experimental cation exchange systems considered in this work, lysozyme on SP-Sepharose-FF and a monoclonal antibody on POROS XS, predictions based on the EI scheme are in excellent agreement with experimental elution profiles under highly overloaded conditions without using any adjustable parameters. A qualitative study of the sensitivity of predicting protein elution profiles to the precision, granularity, and extent of the batch adsorption data is conducted. Based on the results for a hypothetical system, whose properties are comparable to those found in practice for protein cation exchange chromatography the results of this show that the interpolation scheme is relatively insensitive, requiring only that the ranges of protein and salt concentrations in the experimental dataset overlap those under which the protein actually elutes from the column and along with a 10% measurement precision.

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“…In addition to the capability of mechanistic models in downstream process development, they have also been used for monitoring of biopharmaceuticals and their impurities. For example, monoclonal antibodies and their variants have been modeled in size exclusion chromatography, cation exchange chromatography, and hydrophobic interaction chromatography . The agreement of these mechanistic models with experimental data demonstrates their potential as monitoring tools.…”

Section: Introductionmentioning

confidence: 99%

Model‐based monitoring of industrial reversed phase chromatography to predict insulin variants

Roch

Sellberg

Andersson

et al. 2019

Biotechnology Progress

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Downstream processing in the manufacturing biopharmaceutical industry is a multistep process separating the desired product from process‐ and product‐related impurities. However, removing product‐related impurities, such as product variants, without compromising the product yield or prolonging the process time due to extensive quality control analytics, remains a major challenge. Here, we show how mechanistic model‐based monitoring, based on analytical quality control data, can predict product variants by modeling their chromatographic separation during product polishing with reversed phase chromatography. The system was described by a kinetic dispersive model with a modified Langmuir isotherm. Solely quality control analytical data on product and product variant concentrations were used to calibrate the model. This model‐based monitoring approach was developed for an insulin purification process. Industrial materials were used in the separation of insulin and two insulin variants, one eluting at the product peak front and one eluting at the product peak tail. The model, fitted to analytical data, used one component to simulate each protein, or two components when a peak displayed a shoulder. This monitoring approach allowed the prediction of the elution patterns of insulin and both insulin variants. The results indicate the potential of using model‐based monitoring in downstream polishing at industrial scale to take pooling decisions.

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Simulation model for overloaded monoclonal antibody variants separations in ion-exchange chromatography

Cited by 56 publications

References 32 publications

Modeling of salt and pH gradient elution in ion-exchange chromatography

Modeling of salt and pH gradient elution in ion-exchange chromatography

Systematic interpolation method predicts protein chromatographic elution from batch isotherm data without a detailed mechanistic isotherm model

Model‐based monitoring of industrial reversed phase chromatography to predict insulin variants

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