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@ARTICLE{Kumar:276293,
author = {Kumar, Vijesh and Leweke, Samuel and von Lieres, Eric and
Rathore, Anurag S.},
title = {{M}echanistic {M}odeling of {I}on-{E}xchange {P}rocess
{C}hromatography of {C}harge {V}ariants of {M}onoclonal
{A}ntibody {P}roducts},
journal = {Journal of chromatography / A},
volume = {1426},
issn = {0021-9673},
address = {New York, NY [u.a.]},
publisher = {Science Direct},
reportid = {FZJ-2015-06754},
pages = {140–153},
year = {2015},
abstract = {Ion-exchange chromatography (IEX) is universally accepted
as the optimal method for achieving process scale separation
of charge variants of a monoclonal antibody (mAb)
therapeutic. These variants are closely related to the
product and a baseline separation is rarely achieved. The
general practice is to fractionate the eluate from the IEX
column, analyze the fractions and then pool the desired
fractions to obtain the targeted composition of variants.
This is, however, a very cumbersome and time consuming
exercise. A mechanistic model that is capable of simulating
the peak profile will be a much more elegant and effective
way to make a decision on the pooling strategy. This paper
proposes a mechanistic model, based on the general rate
model, to predict elution peak profile for separation of the
main product from its variants. The proposed approach uses
inverse fit of process scale chromatogram for estimation of
model parameters using the initial values that are obtained
from theoretical correlations. The packed bed column has
been modeled along with the chromatographic system
consisting of the mixer, tubing and detectors as a series of
dispersed plug flow and continuous stirred tank reactors.
The model uses loading ranges starting at $25\%$ to a
maximum of $70\%$ of the loading capacity and hence is
applicable to process scale separations. Langmuir model has
been extended to include the effects of salt concentration
and temperature on the model parameters. The extended
Langmuir model that has been proposed uses one less
parameter than the SMA model and this results in a
significant ease of estimating the model parameters from
inverse fitting. The proposed model has been validated with
experimental data and has been shown to successfully predict
peak profile for a range of load capacities (15–28 mg/mL),
gradient lengths (10–30 CV), bed heights (6–20 cm), and
for three different resins with good accuracy (as measured
by estimation of residuals). The model has been also
validated for a two component mixture consisting of the main
mAb product and one of its basic charge variants. The
proposed model can be used for optimization and control of
preparative scale chromatography for separation of charge
variants.},
cin = {IBG-1},
ddc = {540},
cid = {I:(DE-Juel1)IBG-1-20101118},
pnm = {581 - Biotechnology (POF3-581)},
pid = {G:(DE-HGF)POF3-581},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000367276100016},
doi = {10.1016/j.chroma.2015.11.062},
url = {https://juser.fz-juelich.de/record/276293},
}