Jurnal Turbin Gas
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Transcript of Jurnal Turbin Gas
ORIGINAL PAPER
A comprehensive comparison of mixing, mass transfer,Chinese hamster ovary cell growth, and antibodyproduction using Rushton turbine and marine impellers
Sandeepa Sandadi • Henrik Pedersen •
John S. Bowers • Dennis Rendeiro
Received: 4 November 2010 / Accepted: 17 February 2011 / Published online: 20 April 2011
� Springer-Verlag 2011
Abstract Large scale production of monoclonal anti-
bodies has been accomplished using bioreactors with dif-
ferent length to diameter ratios, and diverse impeller and
sparger designs. The differences in these physical attributes
often result in dissimilar mass transfer, mechanical stresses
due to turbulence and mixing inside the bioreactor that may
lead to disparities in cell growth and antibody production.
A rational analysis of impeller design parameters on cell
growth, protein expression levels and subsequent antibody
production is needed to understand such differences. The
purpose of this study was to examine the impact of Rushton
turbine and marine impeller designs on Chinese hamster
ovary (CHO) cell growth and metabolism, and antibody
production and quality. Experiments to evaluate mass
transfer and mixing characteristics were conducted to
determine if the nutrient requirements of the culture would
be met. The analysis of mixing times indicated significant
differences between marine and Rushton turbine impellers
at the same power input per unit volume of liquid (P/V).
However, no significant differences were observed
between the two impellers at constant P/V with respect to
oxygen and carbon dioxide mass transfer properties.
Experiments were conducted with CHO cells to determine
the impact of different flow patterns arising from the use of
different impellers on cell growth, metabolism and anti-
body production. The analysis of cell culture data did not
indicate any significant differences in any of the measured
or calculated variables between marine and Rushton tur-
bine impellers. More importantly, this study was able to
demonstrate that the quality of the antibody was not altered
with a change in the impeller geometry.
Keywords Impellers � CHO cells � Mass transfer �Mixing � Antibody production
Abbreviations
CHO Chinese hamster ovary
P Power (W)
V Volume (L)
DHFR Dihydrofolate reductase
Re Reynolds number (dimensionless)
IgG Immunoglobulin
HPLC High-performance liquid chromatography
H Liquid height in reactor (m)
T Reactor diameter (m)
DO Dissolved oxygen (%)
q Density (kg/m3)
P0 Power number (marine 0.4, Rushton 5)
N Agitation rate (rev/s)
D Impeller diameter (m)
n Number of impellers
l Viscosity (mPa s)
hm Mixing time (s)
eT Mean specific energy dissipation rate (W/kg)
kLaO Mass transfer coefficient for oxygen in culture
medium (h-1)
kLasO Surface mass transfer coefficient for oxygen (h-1)
S. Sandadi � J. S. Bowers � D. Rendeiro
BioProcess Development, Merck Research Laboratories,
1011 Morris Avenue, Union, NJ 07083, USA
H. Pedersen
Department of Chemical and Biochemical Engineering,
Rutgers, The State University of New Jersey,
98 Brett Road, Piscataway, NJ 08854, USA
Present Address:S. Sandadi (&)
BioPharmaceutical Development, Human Genome Sciences,
Inc., 14200 Shady Grove Road, Rockville, MD 20850, USA
e-mail: [email protected]
123
Bioprocess Biosyst Eng (2011) 34:819–832
DOI 10.1007/s00449-011-0532-0
vvh Volume of gas per volume of liquid per hour
slpm Standard liters per minute
ppm Parts per million
C* Saturation concentration of oxygen (%
dissolved oxygen)
CL Concentration of oxygen gas in bulk liquid (%
dissolved oxygen)
OUR Oxygen utilization rate (% dissolved oxygen/h)
Coxygen Concentration of oxygen (% dissolved oxygen)
CT Total inorganic carbon
kLaC Mass transfer coefficient for carbon dioxide (h-1)
kcorr Correction factor (dimensionless)
ANOVA Analysis of variance
X Total cell concentration (cells mL-1)
XV Viable cell concentration (cells mL-1)
l Specific growth rate of cells (day-1)
lmax Maximum specific growth rate of cells (day-1)
qP Specific product formation rate (pg/cell/day)
a Growth associated product rate constant
b Non-growth associated product rate constant
qAb Specific rate of antibody production (pg/cell/
day)
qL Specific rate of lactate production (pg/cell/day)
qN Specific rate of ammonia production (pg/cell/
day)
CFD Computational fluid dynamics
Introduction
Cultured mammalian cells have been widely used for the
production of protein therapeutics. Large-scale cultivation of
mammalian cells is usually undertaken in conventional
stirred tanks equipped with axial or radial flow impellers to
promote homogenous mixing of cells, gases and nutrients in
the vessel. The stirring action evenly distributes oxygen and
nutrients to the cells, prevents settling of cells at the bottom
of the vessel and helps to maintain uniform temperature
conditions inside the bioreactor. The selection of the
impeller determines the type of mixing imparted to the cul-
ture, i.e. radial or axial flow. Radial flow impellers are flat-
blade or disk-turbine impellers generally referred to as
Rushton turbines and are commonly used for fermentation of
cell lines that are not considered shear sensitive, including
yeast, bacteria and fungi. Axial flow impellers on the other
hand, are considered low-shear impellers and are generally
employed for animal cell cultivation. Marine and pitched-
blade impellers are the most commonly used axial flow
impellers. In a stirred-tank system, radial flow occurs when
fluid is pushed away from the axis of the impeller towards the
vessel wall. On the other hand, axial flow occurs when fluid is
pushed up or down along the axis or shaft of the impeller. The
orientation and direction of agitation of the impeller are also
important considerations when determining the type of
impeller to be used in the bioreactor [1].
The use of different impellers may result in diverse
circulation patters of the liquid and hence dissimilar mass
transfer characteristics. These differences may result in
inadequate supply of nutrients to the cells and eventually
result in cell damage and reduced antibody productivity.
Such processes can be a challenge to scale-up for com-
mercial manufacture. The use of optimal feeding strategies
and culture medium, in addition to appropriate bioreactors,
enhances the yield of the antibody product. Therefore, it is
imperative to develop a good understanding of the rela-
tionship between the physical and biological aspects of
production of monoclonal antibodies. Most of the efforts in
animal cell culture have been devoted to promoting the
chemical environment of the cells and culture media in
order to enhance antibody production [2–11]. However,
limited literature is available on the physical properties
involved with respect to animal cell cultivation, i.e. bio-
reactor geometry, sparger and impeller design [12–14]. The
goal of this work is to understand the effect of impeller
design on mass transfer, mixing and antibody production
by Chinese hamster ovary (CHO) cells.
Cell growth and antibody production rates are improved
using various physical and chemical characteristics of the
culture such as feeding concentrated nutrient mixtures,
maintaining optimal dissolved oxygen (DO) and pH levels
in the culture, temperature, agitation rates and osmolality
[9–11, 15, 16]. Consequently, an understanding of the how
process conditions affect cell growth and antibody pro-
duction may lead to improved process performance. These
processes are generally carried out in conventional stirred-
tank reactors (1–20,000 L scale) with aspect ratios of 1–3
and diverse impeller and sparger designs. The differences
in these physical attributes could result in dissimilar mass
transfer, mixing, and mechanical stresses due to turbulence
inside the bioreactor, which could lead to disparities in cell
growth and antibody production. In addition, the same
process may have to be scaled-up into different bioreactor
and impeller configurations, which makes the task even
more challenging. Considerable amount of work has been
reported in the literature to support the theory that animal
cells are much more sensitive to mechanical stresses and
changes in mixing conditions compared to microbial cells,
and hence limits were imposed on the operational condi-
tions for large scale cultivation of animal cells [17]. It was
therefore hypothesized to operate the reactors at very low
power, sufficient enough to keep the cells in suspension
and use low power number axial impellers to prevent any
shear damage to the cells. Cells were subjected to con-
trolled physical stress and morphological changes were
820 Bioprocess Biosyst Eng (2011) 34:819–832
123
observed, thus supporting the conclusion that animal cells
do not grow well under high intensity agitation conditions
[18]. However, contradictory studies were reported where
it was shown that animal cells could withstand high agi-
tation rates, but suffer shear damage due to disengaging
bubbles from gas sparging, and hence Pluronic F-68 was
added to culture media to protect cells from lethal damage
in bioreactors [18–22]. On the other hand, insufficient
liquid homogenization in the animal cell culture reactors
due to their low power operation was shown to cause pH
gradients, and inconsistent dispersion of nutrients and
gases in large scale operations [23]. Junker et al. [24]
discussed the use of flexible microbial fermenters for ani-
mal cell cultivation, in order to ensure existing facilities
could be employed for multiple cell types. This renewed
interest in ensuring flexible reactor design was also sup-
ported by work reported by Nienow [25] where the myth of
‘‘low shear’’ elephant ear impellers was investigated with
mixing studies and their implications on damage to
mycelia. It was reported that the ‘‘low shear’’ elephant ear
impellers have very similar characteristics as other axial
impellers. Nevertheless, there is not enough data reported
for animal cell culture systems, and the impact of different
flow patterns on cell behavior. The use of radial flow
(Rushton turbine) impellers compared to the axial flow
(marine) impellers for CHO cell cultivation was explored
in detail in this study. Since the main difference between
the impellers is in the flow patterns, it is important to
determine the mixing and mass transfer characteristics to
ensure the nutrient requirements of the culture will be met.
Mixing time is particularly important in cell culture
bioreactors because of the potential for pH gradients due to
nutrient feed additions or base additions to control pH [26].
Mixing time denotes the time required for the tank com-
position to achieve a specified level of homogeneity fol-
lowing the addition of a tracer pulse at a single point in the
vessel. The tracer may be a salt solution, acid or base, or a
heated or cooled pulse of liquid. The mixing time in the
vessel may be measured by continuously monitoring the
tracer concentration at one or multiple points in the vessel.
It has been shown that a difference in the reactor or agitator
geometry results in different circulation and mixing time
characteristics [27]. However, the consideration of a single
circulation or mixing time in an agitated tank is a con-
ceptual approximation. If the various parcels of fluid from
the impeller region are monitored, different paths will be
followed by different parcels, leading to different circula-
tion times.
Oxygen is a vital substrate in cell culture processes and
its low solubility in aqueous solutions makes the continu-
ous transfer of oxygen from the gas phase to the liquid
phase crucial for maintaining the oxidative metabolism of
cells. The oxygen requirement of animal cells is generally
low compared to microbial cells. CHO cells have been
reported to be viable when the dissolved oxygen levels are
between 5 and 80%. The type of sparger used determines
the mass transfer properties in the culture, especially if
other culture variables such as temperature, media com-
position, etc. remain the same. Two types of spargers are
generally used in cell culture bioreactors: drilled-tube or
ring spargers with 7–10 holes (0.5–1 mm diameter); and
sintered micro-porous or frit spargers with 10–20 lm pore
size. As the size of the bubbles emerging from the two
spargers is different, the mass transfer coefficients have
been shown to be different in each case [23]. One of the
recurring problems in industrial cell culture is the accu-
mulation of dissolved carbon dioxide in large-scale reac-
tors. High accumulation of dissolved carbon dioxide has
been shown to be detrimental to cell growth and antibody
production [28]. Hence, it is imperative to determine the
mass transfer coefficient for carbon dioxide gas in the
culture. The mass balance for carbon dioxide becomes
more complicated due to the presence of bicarbonate and
other buffers in general cell culture media. A relationship
between pH and total inorganic carbon can be used for this
determination [29].
It is essential to examine the impact of process control
parameters on antibody quality. Although product quality
is a critical aspect of monoclonal antibody production, very
limited literature is available in this area. It was recently
demonstrated that very low concentrations of essential
nutrients in culture media can lead to changes in the gly-
cosylation profiles of the final antibody produced [30, 31].
In addition, it has also been shown that scale-up of cell
cultures and oxygen deprivation also affects the N-glyco-
sylation quality [32]. Hence, it is crucial to understand the
effect of both physical and chemical properties of culture
on protein quality. The purpose of this work was to
understand the impact of impellers on mixing, mass
transfer, antibody production and quality. This work was
intended to bridge the gap in understanding the relationship
between impellers with different flow patterns and their
effect on mass transfer, mixing and antibody production by
CHO cells.
Materials and methods
Bioreactor set-up
The bioreactors used in this study were 20 L Biostat
C-DCU (Sartorius-BBI, Bethlehem, PA) with 15 L work-
ing volume. The bioreactor dimensions are detailed in
Fig. 1. The reactors had an aspect ratio of 2.6 (H/T) and
were equipped with three marine or Rushton turbine
impellers (see Table 1). Gas supply to the reactors was
Bioprocess Biosyst Eng (2011) 34:819–832 821
123
accomplished using a drilled-tube sparger with 0.5 mm
holes. The dissolved oxygen and pH levels in the biore-
actors were monitored with calibrated probes (Broadley-
James Corp., Irvine, CA). pH control was accomplished
with base and carbon dioxide gas additions as needed.
Dissolved oxygen (DO) control was carried out using air
and oxygen cascade with a gas sparging rate of 0–3 slpm.
Constant power per unit volume for an ungassed system,
given by Eq. 1 was used in the study to determine the
agitation rates with both impellers.
P
V¼ nqP0N3D5
V: ð1Þ
Mixing time determination
The mixing studies were conducted using sodium phos-
phate dibasic buffer (1.8 mM) in two reactors. One reactor
was fitted with three marine impellers and the other was
fitted with three Rushton turbine impellers. Two probes
were set up at the top and bottom of the reactor and the
agitator was run at different power per unit volume values
(P/V) in order to determine the mixing time. Approxi-
mately 1 mL of 50% w/v sodium hydroxide was used to
increase pH and 1 mL glacial acetic acid was added to
decrease pH. Care was taken to ensure consistent injection
location and amount of acid and base injected each time. In
addition, the time of addition of the acid or base was also
maintained constant (\1 s). In each experiment, the change
in pH by 1–1.5 units was measured with both the top and
bottom pH probes. The response time of the pH probes
used was approximately 20 s. The time taken to reach 95%
of the difference between the initial and final pH values
was taken as the mixing time. The mixing times calculated
with both top and bottom probes were averaged to calculate
the characteristic mixing time. These experiments were
repeated (n = 3–5) for better accuracy. The experiments
were carried out at different agitation rates for both marine
and Rushton turbine impellers.
Mass transfer coefficients determination
The mass transfer coefficients for oxygen and carbon
dioxide were determined using the base medium (C5467,
SAFC Biosciences, Lenexa, KS) with no cells. Mass
transfer of oxygen and carbon dioxide in cell culture media
has been shown to be a strong function of media compo-
sition, agitation, sparging rates, and the presence of anti-
foam. The variables that were used were impeller type, gas
sparging rates, type of gas used for sparging and the
presence/absence of anti-foam as shown in Table 2. This
study was conducted using two bioreactors, each fitted with
three marine or Rushton turbine impellers, maintaining
constant P/V in all cases. The mass transfer coefficient for
oxygen was determined using the dynamic method by
introducing nitrogen or oxygen gas and measuring the
slope of decrease or increase in oxygen concentration in the
reactor [27]. The bioreactors were filled with culture
medium and equilibrated overnight with air sparging at a
Fig. 1 Schematic representation of Biostat C-DCU 20L bioreactor
Table 1 Dimensions of bioreactors used in the study
Description Value
Working volume (L) 15
Liquid height, H (m) 0.6
Tank diameter, T (m) 0.23
H/T (working) 2.6
Impeller Marine/Rushton
Number of impellers 3
Impeller diameter, D (m) Marine 0.095
Rushton turbine 0.085
Impeller diameter, D
Tank diameter, T
Marine 0.41
Rushton turbine 0.37
Power number (P0) Marine 0.4
Rushton turbine 5
Power (W) 0.26
Agitation (rpm) Marine 183
Rushton turbine 95
P/V (W/L) 0.018
Gas flow rate (vvh) 3–12
Reynolds number (Re) Marine 2.8 9 104
Rushton turbine 1.1 9 104
822 Bioprocess Biosyst Eng (2011) 34:819–832
123
low flow rate. Nitrogen and oxygen gases were sparged to
determine mass transfer coefficients for oxygen and carbon
dioxide gases in liquid by monitoring dissolved oxygen and
pH levels in the reactors continuously. The temperature
was maintained at 37 �C and pH was adjusted to 6.8 using
carbon dioxide gas each time. Medical antifoam C (Dow
Corning, NY) was used at a concentration of 100 ppm for
the experiments to test the effect of antifoam.
Cell culture experiments
A Chinese hamster ovary (CHO) dihydrofolate reductase
(DHFR)-deficient DXB-11 mutant cell line expressing a
recombinant IgG antibody was used in this study. The base
medium was a commercially available animal component-
free CHO medium (C5467, SAFC Biosciences, Lenexa,
KS) containing 4 g/L glucose. The cultures were propa-
gated in shake flasks or Wave� bags (GE Healthcare, Wave
Biotech, LLC, Bridgewater, NJ) at 37 �C with 7.5% CO2
overlay, using the base medium supplemented with 4 mM
L-glutamine. Seed cultures were passaged at split ratios of
1:3–1:5 in their exponential phase of growth to attain initial
cell densities around 0.4 9 106 cells mL-1. The bioreac-
tors were filled with 11.25 L of base medium and inocu-
lated with 3.75 L of culture. The base medium was also
supplemented with 4 mM L-glutamine and 100 ppm of
antifoam solution (Medical antifoam C, DOW Corning,
NY). Concentrated glucose and L-glutamine were fed in
bolus feeds during the culture, in order to maintain the
concentrations above 1 g/L for glucose and 0.1 g/L for
L-glutamine. The volume added in each case was negligible
compared to the total volume of the culture. Data previ-
ously generated using a 3 L scale Celligen bioreactor (New
Brunswick Scientific, Edison, NJ) with a marine impeller
was also used in the study. The total volume of the inoc-
ulum used in the 3 L scale bioreactor was 0.75 L, with
2.25 L of base medium. All the operating conditions were
maintained the same in the 3 L scale reactor as the 15 L
scale batches, including constant P/V.
The impact of Rushton turbine and marine impellers on
CHO cells was determined by conducting experiments in
multiple reactors. Each bioreactor was fitted with three
marine or Rushton turbine impellers and the experiments
were conducted at constant P/V. The bioreactor operating
conditions have been detailed in Table 3. Samples were
analyzed to determine the viable and total cell counts by
CedexTM (Innovatis AG, Bielefeld, Germany), glucose/
lactate, and L-glutamine/L-glutamate by YSI 2700 SelectTM
(YSI Inc., Yellow Springs, OH), pH/pO2/pCO2 by
ABL5TM (Radiometer America Inc., Westlake, OH), NH4?
by Nova BioProfile 100 PlusTM (Nova Biomedical Corp.,
Waltham, MA), and osmolality by Advanced Micro-
OsmometerTM (Advanced Instruments, Norwood, MA).
The bioreactor batches were harvested by adding phos-
phate buffer, and then the cells were removed by centri-
fugation at 8,000 rpm for 30 min. The centrate obtained
from centrifugation was then 0.22-lm filtered and stored at
4 �C. The stored filtrate was purified by reversed-phase
chromatography to assess the quantity of the antibody
produced [11]. Data analysis was carried out using SAS
JMP� (version 7.0.2, SAS Institute, Cary, NC) software.
Antibody quality assessment
The quality of the final antibody produced was assessed by
first purifying all the batches on a Protein A chromatog-
raphy column. This method is generally used to purify the
monoclonal antibodies from clarified cell culture broth.
The liquid chromatography system (AKTATM Explorer
100, GE Healthcare, Piscataway, NJ) was employed with a
Millipore column (18 cm 9 1.6 cm, Millipore, Bedford,
MA), filled with resin (MabSelectTM, GE Healthcare, Pis-
cataway, NJ), at a flow rate of 12 mL/min. Antibody
concentrations were monitored with UV absorbance
at 280 nm. The bound antibody was eluted using 0.1 M
acetic acid. The pool thus obtained from the protein A
chromatography step was then used for further antibody
quality analysis using size-exclusion, ion-exchange and
Table 2 Design for the mass transfer experiments
Variable Levels
Impeller Rushton turbine, marine
Gases Oxygen, nitrogen, air
Sparge rates (vvh) 3, 12
Antifoam (ppm) 0, 100
P/V Constant
Table 3 Description of the operating conditions used for cell culture
experiments
Description Operating conditions
Temperature (�C) 37
pH 6.8
pH control 1 N sodium hydroxide/
carbon dioxide addition
Agitation (rpm) 95 (Rushton turbine)/183 (marine)
Dissolved oxygen (%) 60
Dissolved oxygen control Air/oxygen gas cascade (0–3 slpm)
Pressure (psi) 5
Gas sparging rate (slpm) 0–3 slpm
Gas sparging mode On-demand
Sparge gases Air, oxygen, and carbon dioxide
Volume of media (L) 11.25
Volume of inoculum (L) 3.75
Bioprocess Biosyst Eng (2011) 34:819–832 823
123
reversed-phase chromatography. The reversed-phase chro-
matography system (Agilent 1100 system, Palo Alto, CA)
was equipped with an R2/10 Poros column (30 mm 9
2.1 mm, Applied Biosystems, Cambridge, MA). The col-
umn temperature was maintained at 70 �C. The flow rate
was set at 0.1 mL/min until the column temperature sta-
bilized at 70 �C, and then set to 2 mL/min during all gradient
segments. Solution A was 0.2% trifluoroacetic acid in water,
and solution B was 0.2% acetic acid in aqueous acetonitrile
(90:10). The detection was carried out at 280 nm by either a
photo-diode array detector or a multi-wavelength detector
using 5–100 lL injections depending on the titer of the
samples [11]. The linear range for the assay was 0.2–2.5 lg
of antibody and the assay variability was 3%. The size-
exclusion chromatography system included a Toso Haas
TSK 3000SWXL column (7.8 mm 9 300 mm, Tosoh Biosep
LLC, Montgomeryville, PA), with 20 mM acetate buffer and
150 mM sodium chloride, at a flow rate of 1 mL/min. Ion-
exchange chromatography was accomplished using a Dionex
ProPac WCX column (4 mm 9 250 mm, Sunnyvale, CA),
with a flow rate of 1 mL/min.
Results
Mixing and mass transfer
Mixing time determination
Impeller effectiveness or liquid homogenization in the
bioreactors has generally been measured in terms of mixing
time (hm). The relationship between mixing times and
reactor geometry has been explained using turbulence flow
models, which take into account mean specific energy
dissipation rates. It has been shown that the mixing time is
inversely proportional to the mean specific energy dissi-
pation rate (eT) [33].
hm / eTð Þ�1=3 D
T
� ��1=3
/ P
qV
� ��1=3 D
T
� ��1=3
: ð2Þ
The relationship between mixing times and P/V is
shown in Fig. 2. It can be seen that the mixing times were
higher for the same P/V with Rushton turbine impellers
when compared to marine impellers. The vertical line
represents the value of P/V chosen for the cell culture
experiments based on previous data. Linear regression fits
were used to estimate the correlation between mixing times
and reactor geometry. Table 4 depicts the values of
intercepts and slopes obtained from the linear regression
fits to the data in Fig. 2. The slopes of the lines although
not equal to Eq. 2 (-0.333) were not significantly different
from each other as shown in Table 4. However, the
intercept in each case was significantly different from each
other. The difference in mixing times may be attributed to
the formation of stagnant mixing zones with the use of
multiple Rushton turbine impellers [34–36]. The use of
multiple impellers leads to high velocity in the impeller
region and stagnant regions near the wall, causing an
uneven distribution in the energy dissipation rates. Similar
results were recently demonstrated with computational
fluid dynamics (CFD) analysis in reactors mounted with
multiple radial or axial impellers, leading to different fluid
patterns and homogenization efficiencies [37]. These
results further demonstrate that the simple relationship
between mixing times and reactor geometry may not be
sufficient to describe the complex mixing patterns in
the bioreactors and their consequence on liquid
homogenization, spatial variations in pH, temperature,
dissolved oxygen, etc.
Mass transfer coefficients determination
Oxygen transfer can be described by the mass transfer
model for a sparingly soluble gas into a liquid with the
following equation.
dCOxygen
dt¼ kLaOðC� �CLÞþ kLasOðC� �CLÞ�OUR: ð3Þ
Since there are no cells in the reactor, the oxygen
utilization rate (OUR) term can be removed from the
equation. For larger bioreactors, surface oxygen transfer is
Fig. 2 Relationship between mixing times and power per unit
volume for marine and Rushton turbine impellers. The lines represent
linear regression fits for the data. The vertical line indicates the value
of P/V chosen for the cell culture experiments in this study. The data
for the marine impellers are shown using closed circles, whereas the
Rushton turbine impeller data are depicted using open circles. The
shaded areas represent 95% confidence intervals around the linear
regression fits for the data
824 Bioprocess Biosyst Eng (2011) 34:819–832
123
much smaller than sparger oxygen transfer and hence
can be neglected in the above equation. Thus, the equation
reduces to a simpler form and the mass transfer
coefficient for oxygen (kLaO) is determined from the
slope of ln(C* - CL) and time. To determine the oxygen
mass transfer coefficient for each bioreactor, nitrogen was
sparged to reduce the dissolved oxygen to less than 10% of
saturation with air. Air or oxygen was then sparged until
the dissolved oxygen was over 90%.
dCO2
dt¼ kLaOðC� � CLÞ ð4Þ
lnðC� � CLÞ ¼ kLaOt þ constant: ð5Þ
For carbon dioxide gas transfer there were no probes
present in the reactor and hence an indirect method was
adopted to determine this behavior. In the media
commonly used for cell culture, pH is maintained by
carbon dioxide–bicarbonate and other buffers. There are
several reactions that fully describe the behavior of the
carbon dioxide–bicarbonate buffer system, but in the pH
range 6.5–8.0, the reactions can be summarized in one
combined reaction [29].
CO2ðgÞ ! CO2ðlÞ þH2O�!slow
�fast
H2CO3 !fast
HCO�3 þHþ: ð6Þ
The equilibrium expression for this reaction can be written
as below, where K is the equilibrium constant.
K ¼HCO�3� �
Hþ½ �CO2½ � ð7Þ
The total inorganic carbon concentration (CT) in the
medium is the sum of CO2 concentration and HCO3-
concentration, by neglecting carbonate and carbonic acid
concentrations.
CT½ � ¼ CO2½ � þ HCO�3� �
: ð8Þ
A balance of total inorganic carbon in the reactor yields the
following equation, where kLaC is the mass transfer
coefficient for carbon dioxide [38]:
d CT½ �dt¼ � kLaCð Þ CO2½ �: ð9Þ
Combining Eqs. 7 and 8, and using a mass balance for
[H?] and [HCO3-] when no other buffers are present in the
system, the total inorganic carbon concentration is given by
Eq. 10.
CT½ � ¼ 1þ K
Hþ½ �
� �CO2½ � ¼ CO2½ �010pH0 10�pH þ K
� �:
ð10Þ
Differentiating Eq. 10 yields the following relation:
dCT
dt¼ 2:303½CO2�
dpH
dt: ð11Þ
The mass transfer coefficient for carbon dioxide (kLaC) can
be defined using the following equation, obtained by
equating Eqs. 9 and 11.
kLaC ffi 2:303kcorr
dpH
dt; ð12Þ
where kcorr is the correction factor taking into account
other buffers present in the base medium [38]. The
changes in pH in the culture medium as a function of
time were used to estimate the mass transfer coefficient
for carbon dioxide gas with the above equation. The
variables tested were sparge gas, sparge rate, impeller
type and the presence/absence of antifoam at constant
P/V. The kLaO values were in the range 1.5–5 (1 h-1) and
kLaC in the range 1–2 (1 h-1) in all cases. The values of
kLaO could not be estimated for air as the dissolved
oxygen levels were close to 100% during these experi-
ments, and hence the data were insufficient to calculate
values of kLaO with air sparging. On the other hand, there
was a significant change in pH during these experiments;
and therefore the values of kLaC could be estimated with
air sparging.
The results were analyzed using analysis of variance
(ANOVA) as shown in Table 5. It can be concluded based
on the ANOVA results that the sparge rate of the gases had
a very strong influence on the mass transfer coefficients for
both oxygen and carbon dioxide at constant P/V. A weak
impact of impeller type on the mass transfer coefficients
was observed for both oxygen and carbon dioxide gases at
constant P/V. The values of both kLaO and kLaC were
higher with the use of marine impellers when compared to
Rushton turbine impellers at the same P/V. There was no
significant effect of either the sparge gas used or the
addition of anti-foam on kLaO and kLaC. Cell culture media
Table 4 Relationship between mixing times (s) and P/V (W/L) for marine and Rushton turbine impellers
Impeller Term Estimate Std. error t ratio Prob [ |t| Lower 95% Upper 95%
Marine Intercept 2.36 0.12 20.33 \.0001 2.13 2.60
Log(P/V) -0.27 0.02 -13.13 \.0001 -0.32 -0.23
Rushton turbine Intercept 3.33 0.07 45.95 \.0001 3.18 3.47
Log(P/V) -0.21 0.02 -11.02 \.0001 -0.25 -0.17
Bioprocess Biosyst Eng (2011) 34:819–832 825
123
generally contain Pluronic F-68 as a common additive,
and hence it may be inferred that the impact of additional
anti-foam did not impact the mass transfer properties of the
culture. However, the impact of adding anti-foam to the
culture media in the absence of Pluronic should be inves-
tigated further, in order to clearly understand the effect of
anti-foam on the mass transfer properties of the culture.
Table 6 depicts the parameter estimates for the impact of
sparge rate of the gases on kLaO and kLaC. The values were
obtained by fitting linear regression lines to the mass
transfer coefficients, separately for oxygen and carbon
dioxide gases. In addition, the linear regression fits were
also done separately for marine and Rushton turbine
impellers, and the values obtained for the slopes and
intercepts were not significantly different in each case, for
both gases. The relationship derived between kLa (1 h-1)
and sparge rate (vvh) of gases in this study, at constant P/V,
is shown in Eq. 13.
kLa / ðvvhÞa; ð13Þ
where the value of ‘‘a’’ was estimated as 0.1 for marine
impellers and 0.09 for Rushton turbine impellers, for both
oxygen and carbon dioxide gases.
The strong impact of sparge rate on the mass transfer
properties in the bioreactor signifies the importance of
understanding the effect of gas sparging rates on cell cul-
ture behavior (see Fig. 3a, b). In addition, the type of
impeller used also impacted the fluid mass transfer prop-
erties in the bioreactor to a less significant degree com-
pared to the gas sparge rates.
Cell culture and antibody quality
Cell culture experiments
The cell culture experiments using Rushton turbine and
marine impellers were conducted using the methodology
detailed in ‘‘Materials and methods’’ section at constant P/
V. The error bars shown in all the panels in Fig. 4 represent
95% confidence intervals around the mean values obtained
for marine (n = 3) and Rushton turbine (n = 6) impellers,
calculated at each sampling time point. The results
obtained with the cell culture batches are shown in Fig. 4a
for viable cell density. The viable cell density profiles for
both marine and Rushton turbine impellers overlapped at
all the sampling time points, with higher variability
observed in the results with Rushton turbine impellers than
with marine impellers. Panel b depicts the results obtained
for final antibody concentration for all the batches. In this
case too, the profiles for antibody concentration coincided
for both marine and Rushton turbine impellers at all the
sampling time points. The measured values for the limiting
substrates; glucose and L-glutamine are shown in panels c
and d, respectively. As specified before, concentrated
glucose and L-glutamine were fed in four bolus feeds
Table 5 Analysis of variance for the mass transfer coefficients cal-
culated for oxygen and carbon dioxide gases as a function of the
variables tested
Parameter Source df Sum of
squares
Mean
square
F ratio Prob [ F
kLaO Model 4 24.77 6.19 19.99 \0.0001
Sparge rate 1 22.80 22.80 73.62 \0.0001
Impeller 1 1.76 1.76 5.67 0.04
Sparge gas 1 0.11 0.11 0.34 0.57
Antifoam 1 0.11 0.11 0.34 0.57
Error 11 3.41 0.31
Total 15 28.17
kLaC Model 5 8.18 1.64 64.89 \0.0001
Sparge rate 1 6.98 6.98 276.91 \0.0001
Impeller 1 0.20 0.20 7.85 0.01
Sparge gas 2 0.07 0.04 1.46 0.27
Antifoam 1 0.10 0.10 4.05 0.06
Error 14 0.35 0.03
Total 19 8.54
Table 6 Parameter estimates for the mass transfer coefficients for oxygen and carbon dioxide gases as a function of sparge rate of gases for
marine and Rushton turbine impellers
Variable Term Estimate Std. error t ratio Prob [ |t| Lower 95% Upper 95%
Marine Log kLaO Intercept 0.322 0.084 3.84 0.009 0.117 0.527
Sparge rate (vvh) 0.101 0.010 10.52 \.0001 0.077 0.124
Rushton turbine Log kLaO Intercept 0.168 0.153 1.09 0.316 -0.207 0.542
Sparge rate (vvh) 0.092 0.017 5.25 0.002 0.049 0.135
Marine Log kLaC Intercept -0.342 0.063 -5.42 0.001 -0.487 -0.196
Sparge rate (vvh) 0.101 0.008 12.71 \.0001 0.083 0.119
Rushton turbine Log kLaC Intercept -0.399 0.072 -5.53 0.001 -0.565 -0.233
Sparge rate (vvh) 0.091 0.009 10.04 \.0001 0.070 0.112
826 Bioprocess Biosyst Eng (2011) 34:819–832
123
during the culture, in order to maintain the concentrations
above 1 g/L for glucose and 0.1 g/L for L-glutamine. The
volume added in each case was negligible compared to the
total volume of the culture. High variability was observed
in the glucose concentrations as indicated by the 95%
confidence intervals in panel c, which may be attributed to
the differences in substrate consumption rates. Neverthe-
less, the profiles for glucose overlapped for both impellers
at all the time points. Similarly, it can be seen in panel d
that the L-glutamine concentration values coincided for
both marine and Rushton turbine impellers at all the sam-
pling time points. The variability observed with L-gluta-
mine was lower as the concentration of L-glutamine was
maintained at a low value (*1 mM).
The accumulation of lactate and ammonia in cell culture
media has been shown to be detrimental to cell growth and
antibody production [39–41]. The two by-products lactate
and ammonia are shown in panels e and f, respectively. The
profiles for lactate concentration coincided for both marine
and Rushton turbine impellers, at all the sampling time
points. However, the mean lactate values were observed to
be higher for marine impeller batches, when compared to
those obtained with Rushton turbine impellers. Neverthe-
less, the 95% confidence intervals overlapped for both
impellers. Panel f depicts the profiles for ammonia con-
centration with both impellers. Although the 95% confi-
dence intervals overlapped for all batches, the mean values
of ammonia concentration were observed to be higher with
Rushton turbine impellers when compared to marine
impellers.
The dependence of cell growth or product formation on
the type of impeller used can be evaluated by comparing
the specific growth and specific antibody production rates
between the different cultures. The mass balance for an
ideal batch reactor can be applied for the systems used in
this study. The rates of cell growth and product formation
are described in terms of viable (XV) and total cell density
(X), and concentration of product (P) formed with liquid
volume V as follows:
d
dtXVð Þ ¼ rXV ¼ lXV
d
dtPVð Þ ¼ rPV ¼ qPXV V;
ð14Þ
where l is the specific growth rate of cells, and qP is the
specific product formation rate.
Assuming the specific rates remain constant between
sampling times, they are calculated by separating the
variables in Eq. 14.
l ¼R X2V2
X1V1dðXVÞR t2
t1ðXVÞdt
qP ¼R P2V2
P1V1dðPVÞR t2
t1ðXVVÞdt
ð15Þ
In order to compare product formation kinetics of different
batches, the simplest stoichiometric connection defined
between product formation and cell growth was chosen.
Using Leudeking-Piret kinetics [8], specific product
formation rate, qP is expressed as a linear function of
specific growth rate, l,
qP ¼ alþ b; ð16Þ
where a and b are growth and non-growth-associated
production rate constants, respectively. The dependence of
specific antibody production rate on specific growth rate is
depicted in Fig. 5a, and it is evident that the slope of the
Fig. 3 Linear regression fits for a mass transfer coefficient for
oxygen gas (kLaO) with sparge rate of gases, and b mass transfer
coefficient for carbon dioxide gas (kLaC) with sparge rate of gases.
The data for the marine impellers are shown using closed circles,
whereas the Rushton turbine impeller data are depicted using opencircles
Bioprocess Biosyst Eng (2011) 34:819–832 827
123
fitted line is not significantly different from zero
(P [ 0.05). Therefore, the specific antibody production
rates for all batches were non-growth associated and their
averages are depicted in Table 7. The values of specific
antibody production rates were not significantly different
when compared between marine and Rushton turbine
impellers using a two-sided t test as shown in Table 7.
The dependence of specific lactate and ammonia pro-
duction rates on specific growth rate is shown in Fig. 5b, c,
respectively. Unlike specific antibody production rates, the
specific lactate and ammonia production rates were growth
associated and the estimates for a and b are shown in
Table 7. The parameter estimates in this case were not
significantly different when compared between marine and
Rushton turbine impellers (two-sided t test, P [ 0.05). In
summary, the cell culture experiments with marine and
Rushton turbine impellers did not indicate any significant
differences in any measured or calculated parameters.
Antibody quality assessment
The quality of the antibody is a primary concern with the
large scale manufacture of biopharmaceuticals. The thera-
peutic efficacy of the antibodies depends on the formation
of complexes with target molecules and subsequent acti-
vation of effector mechanisms that result from structural
characteristics of the antibody. In particular, the antibody
undergoes several post-translational modifications inside
the cell which determine the biological half-life and the
efficacy of the product. Hence, it is vital to ensure con-
sistent quality of the antibody produced. In general, the
structural characteristics of the antibody, i.e. surface charge
homogeneity and aggregation are used as indicators of
consistent antibody quality.
The cell culture batches produced with marine and
Rushton turbine impellers were purified using affinity-
chromatography on a Protein A column. The antibody
Fig. 4 Results using marine
and Rushton turbine impellers
for a viable cell density,
b antibody concentration,
c glucose, d L-glutamine,
e lactate, and f ammonia. The
error bars represent 95%
confidence intervals around the
mean values obtained for each
impeller, calculated at each time
point. The data for the marine
impellers (n = 3) are shown
using closed circles, whereas
the Rushton turbine impeller
data (n = 6) are depicted using
open circles
828 Bioprocess Biosyst Eng (2011) 34:819–832
123
pools obtained from the Protein A column were used for
further quality assessment. Visual observation of the pools
from the protein A column step did not indicate any dif-
ferences in the appearance, color or turbidity of the sam-
ples in all cases. The recovery of the antibody from the
protein A column was *85–87% for both marine and
Rushton turbine impellers. Initial quality of the antibody
produced was determined using reversed-phase chroma-
tography, and the purity of the product obtained was 99%
for batches with both marine and Rushton turbine impel-
lers. The antibody pools were also assessed for any insol-
uble aggregates by measuring the UV absorbance at
320 nm wavelength on a UV spectrophotometer. The
measured absorbance (320 nm) was 0.014 AU for both
marine and Rushton turbine impellers, indicating the
absence of any insoluble aggregation of the antibody in all
cases.
Size-exclusion chromatography is typically used as a
tool to measure any soluble aggregation or clipped frag-
ments of the antibody produced. Aggregation is one of the
degradation pathways for antibodies and hence is of critical
importance in a process. The results obtained with the size-
exclusion chromatography column have been detailed in
Table 8. The results indicate insignificant soluble aggre-
gates (%pre-peak \1%) or clipped fragments of the anti-
body (%post-peak *2%). The purity of the antibody
attained in both cases with marine and Rushton turbine
impellers was 98%. Ion-exchange chromatography is a
separation based on the surface charge of the protein.
Surface charge variation may generally occur during stor-
age of the antibody and is considered an indicator of the
presence of a degradation pathway for the antibody. In this
case, the surface charge variation between the two types of
impellers was not significant, i.e. the acidic and basic
variants observed were not different as shown in Table 9.
Conclusions
The main objective of this study was to characterize the
performance of Rushton turbine and marine impellers with
respect to mixing, mass transfer, CHO cell growth and
antibody production and quality. The mixing and mass
transfer properties of the culture were determined as a
function of the different flow patterns arising from the use
of axial flow marine and radial flow Rushton turbine
impellers. Liquid homogenization studies were conducted
by measuring pulse changes in pH at the top and bottom of
the bioreactor. The mixing times were observed to be
different between marine and Rushton turbine impellers at
the same P/V; however, the slopes of the linear fits to the
data were not significantly different for both impellers. The
differences in the mixing times at constant P/V may be
attributed to the formation of stagnant mixing zones with
the use of multiple Rushton turbine impellers reported
previously [34]. The use of multiple impellers leads to high
velocity in the impeller region and stagnant regions near
the wall, causing an uneven distribution in the energy
dissipation rates. Similar results were recently demon-
strated with CFD analysis in reactors mounted with mul-
tiple radial or axial impellers, leading to different fluid
patterns and homogenization efficiencies [37]. In addition,
impeller spacing may impact the distribution of power in
the case of multiple impellers and will have to be inves-
tigated further. The mass transfer properties of the culture
were determined as a function of sparge gas, sparge rate,
Fig. 5 Relationship between specific growth rate (l) of the cells and
a specific antibody production rate (qAb), b specific lactate production
rate (qL), and c specific ammonia production rate (qN). The data for
the marine impellers are shown using closed circles, whereas the
Rushton turbine impeller data are depicted using open circles
Bioprocess Biosyst Eng (2011) 34:819–832 829
123
impeller type and the presence/absence of antifoam at
constant P/V. The kLaO values were in the range 1.5–5
(1 h-1) and kLaC in the range 1–2 (1 h-1) in all cases,
which were in agreement with those reported in the liter-
ature for CHO cell cultivation [29, 38]. A strong impact of
gas sparge rate was observed along with a weak impact of
impeller type on the mass transfer coefficients for both
oxygen and carbon dioxide gases at constant P/V.
Considerable amount of work has been reported in the
literature to support the theory that animal cells are much
more sensitive to shear and changes in mixing conditions
compared to microbial cells, and hence limits were
imposed on the operational conditions for large scale cul-
tivation of animal cells [17]. It was therefore hypothesized
to operate the reactors at very low power, sufficient enough
to keep the cells in suspension and use low power number
axial impellers to prevent any shear damage to the cells. On
the other hand, insufficient liquid homogenization in the
animal cell culture reactors due to their low power
operation was shown to cause pH gradients, and inconsis-
tent dispersion of nutrients and gases in large scale oper-
ations [23]. Various methods have been described in this
study to determine the effect of changing the flow char-
acteristics in the bioreactor with different types of impel-
lers, on the biological performance of the culture. The
results for CHO cell growth, metabolism and antibody
production were not significantly different for the two
types of impeller configurations tested for all the measured
and calculated parameters. The quality of the antibody was
examined using detailed analysis, and it was observed that
antibody quality was similar in all cases for both marine
and Rushton turbine impellers, and there was no apparent
effect of changing the flow characteristics in the bioreac-
tors on antibody purity or degradation. More detailed
analysis on the quality of the antibody can be conducted to
ensure that the glycosylation profiles are not different with
changes in the flow patterns in the bioreactor. Nevertheless,
the analysis conducted in this work suggests that the
resulting product will display similar quality. In addition, a
deterministic model was constructed separately for both
marine and Rushton turbine impellers and the parameters
estimated were not significantly different in both cases
[42].
This study was therefore able to present a comprehen-
sive comparison of the performance of marine and Rushton
turbine impellers with respect to CHO cell growth and
antibody production, and more importantly the impact on
the quality of the final antibody produced, which had not
been reported earlier. Although the mixing efficiency was
significantly different between the two impellers, no dis-
parity was observed with respect to mass transfer proper-
ties, CHO cell growth, metabolism, antibody production
and antibody quality between marine and Rushton turbine
impellers. This study also supports the validity of using
constant power per unit volume (P/V) as a scale-translation
Table 7 Estimation of parameters for cell culture experiments using marine and Rushton turbine impellers
Impeller Parameter Term Estimate Std. error t ratio Prob [ |t| Lower 95% Upper 95%
Marine lmax (1 day-1) – 0.50 0.04 – – 0.39 0.61
qAb (pg/cell/day) b 15.5 2.8 5.53 \.0001 9.7 21.3
qL (pg/cell/day) a 101.4 19.8 5.1 \.0001 60.3 142.5
b 511.0 83.6 6.1 \.0001 337.7 684.3
qN (pg/cell/day) a 1.0 0.7 1.5 0.153 -0.4 2.5
b 17.3 3.0 5.8 \.0001 11.1 23.5
Rushton turbine lmax (1 day-1) – 0.41 0.03 – – 0.35 0.47
qAb (pg/cell/day) a 14.9 1.8 8.09 \.0001 11.2 18.5
qL (pg/cell/day) a 119.8 17.2 7.0 \.0001 85.6 154.1
b 317.1 82.6 3.8 0.0003 152.4 481.9
qN (pg/cell/day) a 1.0 0.5 1.9 0.068 -0.1 2.0
b 17.1 2.5 6.8 \.0001 12.1 22.1
Table 8 Size-exclusion chromatography results
Description % Pre-peaks
(high molecular
weight)
% Main peak
(% purity)
% Post-peaks
(low molecular
weight)
Marine 0.2 97.5 2.3
Rushton turbine 0.6 97.8 1.6
Table 9 Ion-exchange chromatography results
Description % Pre-peaks
(acidic variants)
% Main peak
(antibody)
% Post-peaks
(basic variants)
Marine 20.7 54.9 24.4
Rushton turbine 17.5 55.3 27.1
830 Bioprocess Biosyst Eng (2011) 34:819–832
123
criterion during the manufacture of animal cell culture
processes across diverse reactor configurations and manu-
facturing facilities. It can be concluded that maintaining a
consistent macro and micro environment for cells in the
bioreactor is more critical to ensure reliable reproducibility
of a cell culture process and the resulting antibody. In
addition, the type of impeller used may not influence the
culture process parameters, provided that the same envi-
ronment is maintained for cells in the bioreactor. Further
studies to determine the influence of changing the energy
dissipation rates in the bioreactor, with different impeller
combinations on animal cell culture characteristics will be
able to provide valuable data to support the development of
multi-product facilities with flexible bioreactors.
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