Protein adsorption equilibrium and kinetics in multimodal cation exchange resins

Zhu, Mimi; Carta, Giorgio

doi:10.1007/s10450-015-9735-z

Cited by 48 publications

(16 citation statements)

References 35 publications

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“…The ligand density

Λ

is another critical parameter that defines the adsorption of the compounds to the resin and is thus needed for the calculation of the isotherm (Eqs and ). Data for it is available in literature: For POROS 50 HS, the ligand density per adsorber skeleton was reported to be 0.276 M with acid–base titration; for Capto MMC, the ligand density per particle volume was reported as 0.128 M …”

Section: Resultsmentioning

confidence: 99%

“…The total intraparticle porosity for a resin with two pore types was than calculated as

ɛ_{p} = ɛ_{p, 1} + ɛ_{p, 2}

where

n = 1

represents the macropores and

n = 2

the micropores. The overall

K_{D}

for both pores is defined as:

K_{normalD} = ɛ_{normalp, 1} K_{normalD, 1} + ɛ_{normalp, 2} K_{normalD, 2}

…”

Section: Methodsmentioning

confidence: 99%

“…The ligand density K is another critical parameter that defines the adsorption of the compounds to the resin and is thus needed for the calculation of the isotherm (Eqs 4 and 5). Data for it is available in literature: For POROS 50 HS, the ligand density per adsorber skeleton was reported to be 0.276 M with acid-base titration 31 ; for Capto MMC, the ligand density per particle volume was reported as 0.128 M. 25 Isocratic Chromatography. Each fraction of interest was analyzed with isocratic experiments at different salt concentrations on RoboColumns containing the respective resin (1, 2 and 3 on POROS 50HS; 4 and 5 on Capto MMC).…”

Section: High-throughput Isocratic Experimentsmentioning

confidence: 99%

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Chromatographic parameter determination for complex biological feedstocks

Pirrung

Cruz

Hanke

et al. 2018

Biotechnology Progress

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The application of mechanistic models for chromatography requires accurate model parameters. Especially for complex feedstocks such as a clarified cell harvest, this can still be an obstacle limiting the use of mechanistic models. Another commonly encountered obstacle is a limited amount of sample material and time to determine all needed parameters. Therefore, this study aimed at implementing an approach on a robotic liquid handling system that starts directly with a complex feedstock containing a monoclonal antibody. The approach was tested by comparing independent experimental data sets with predictions generated by the mechanistic model using all parameters determined in this study. An excellent agreement between prediction and experimental data was found verifying the approach. Thus, it can be concluded that RoboColumns with a bed volume of 200 μL can well be used to determine isotherm parameters for predictions of larger scale columns. Overall, this approach offers a new way to determine crucial model input parameters for mechanistic modelling of chromatography for complex biological feedstocks. © 2018 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 34:1006–1018, 2018

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“…The ligand density

Λ

Section: Resultsmentioning

confidence: 99%

“…The total intraparticle porosity for a resin with two pore types was than calculated as

ɛ_{p} = ɛ_{p, 1} + ɛ_{p, 2}

where

n = 1

represents the macropores and

n = 2

the micropores. The overall

K_{D}

for both pores is defined as:

K_{normalD} = ɛ_{normalp, 1} K_{normalD, 1} + ɛ_{normalp, 2} K_{normalD, 2}

…”

Section: Methodsmentioning

confidence: 99%

Section: High-throughput Isocratic Experimentsmentioning

confidence: 99%

See 1 more Smart Citation

Chromatographic parameter determination for complex biological feedstocks

Pirrung

Cruz

Hanke

et al. 2018

Biotechnology Progress

View full text Add to dashboard Cite

show abstract

“…For chemisorption one can develop more complex kinetic schemes, but these are system dependent and are beyond the scope of this contribution. Furthermore, as diffusion in the stagnant liquid in the macropores is relatively slow, the shrinking core model has been shown to describe well, for example, ion-exchange from concentrated solutions (Phelps and Ruthven 2001) and protein adsorption in porous particles (Zhu and Carta 2016) and is a very relevant limiting case to consider. The uptake curves obtained from the two mechanisms become mathematically very similar when dealing with very sharp isotherms, i.e.…”

Section: Introductionmentioning

confidence: 99%

“…the limit of the rectangular isotherm (Teo and Ruthven 1986;Ruthven 2000;Do 1998). Therefore, to confirm which mechanism is relevant imaging of carefully cut beads can be used to determine if the shrinking core model applies (Phelps and Ruthven 2001;Zhu and Carta 2016;Dominguez et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Kinetics of liquid phase batch adsorption experiments

Brandani

2020

Adsorption

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Batch adsorption experiments are carried out by adding a known amount of adsorbent to a liquid solution at a known initial concentration and following the evolution in time of the concentration of the adsorbate. This is a very common method to obtain equilibrium and kinetic information in liquid systems, but in most cases kinetic results are analysed on the basis of empirical models. Two phenomenological models based on macropore diffusion in beads and shrinking core kinetics are used to generate data that are then interpreted with the widely used unconstrained linear regression methods. The results show that for both cases R2 values close to unity are obtained leading to the incorrect interpretation of the mechanism of mass transport. It is recommended that batch adsorption experiments should be analysed using phenomenological models to obtain physical parameters that are applicable to other systems and to reduce the experiments required to characterise fully the kinetics of adsorption.

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

Vecchiarello

Timmick

Cramer

2021

Biotech & Bioengineering

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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. Nullproducing CCFs were fractionated using linear salt gradients at constant pH on a set of multimodal resins. Fractions were then analyzed by ultraperformancereversed 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.

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Protein adsorption equilibrium and kinetics in multimodal cation exchange resins

Cited by 48 publications

References 35 publications

Chromatographic parameter determination for complex biological feedstocks

Chromatographic parameter determination for complex biological feedstocks

Kinetics of liquid phase batch adsorption experiments

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

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