Separation of monoclonal antibody monomer-dimer mixtures by gradient elution with ceramic hydroxyapatite
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作者:
Wang, Yiran
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Univ Virginia, Dept Chem Engn, Charlottesville, VA 22903 USA
Bristol Myers Squibb, Devens, MA USAUniv Virginia, Dept Chem Engn, Charlottesville, VA 22903 USA
Wang, Yiran
[1
,2
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Carta, Giorgio
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Univ Virginia, Dept Chem Engn, Charlottesville, VA 22903 USAUniv Virginia, Dept Chem Engn, Charlottesville, VA 22903 USA
Carta, Giorgio
[1
]
机构:
[1] Univ Virginia, Dept Chem Engn, Charlottesville, VA 22903 USA
Modeling the chromatographic separations of proteins at manufacturing scale is important since downstream processing costs are often dominant. At such scales, the columns are highly overloaded heightening the challenge of predicting performance. In this work, the separation of a monoclonal antibody monomer-dimer mixture is conducted by gradient elution chromatography with ceramic hydroxyapatite (CHT) columns Type I and Type II under overloaded conditions. Phosphate gradients are shown to be preferable over sodium chloride gradients since the latter result in undesirable pH transitions generated within the column itself. Using sodium phosphate gradients separation is obtained with both CHT types, achieving approximately 90% recovery at 99% monomer purity starting with a mixture containing 30% dimer at total protein loads up to 30 mg/mL. Because of its higher binding capacity, even higher loadings can be obtained with CHT Type I without monomer breakthrough. A hybrid model is developed to describe the separation. The model, based on an empirical description of two-component, competitive isotherms at low sodium phosphate concentration coupled with the stoichiometric displacement model at higher sodium phosphate concentrations, is in good agreement with the experiments using the linear driving force (LDF) approximation to describe adsorption/desorption kinetics. The same LDF rate coefficient predicts the separation at loadings between 0.8 and 30 mg/mL. The model developed in this work can be used as a general tool to optimize operating conditions, understand what factors limit performance, and compare different operating modes. (c) 2020 Elsevier B.V. All rights reserved.
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Indian Inst Technol Delhi, Sch Interdisciplinary Res, New Delhi, IndiaIndian Inst Technol Delhi, Sch Interdisciplinary Res, New Delhi, India
Anupa, Anupa
Bansode, Vikrant
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Indian Inst Technol Delhi, Dept Chem Engn, New Delhi, IndiaIndian Inst Technol Delhi, Sch Interdisciplinary Res, New Delhi, India
Bansode, Vikrant
Kateja, Nikhil
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Indian Inst Technol Delhi, Dept Chem Engn, New Delhi, IndiaIndian Inst Technol Delhi, Sch Interdisciplinary Res, New Delhi, India
Kateja, Nikhil
Rathore, Anurag S.
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Indian Inst Technol Delhi, Dept Chem Engn, New Delhi, India
Indian Inst Technol, Dept Chem Engn, New Delhi 110016, IndiaIndian Inst Technol Delhi, Sch Interdisciplinary Res, New Delhi, India