Jurnal Turbin Gas

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ORIGINAL PAPER A comprehensive comparison of mixing, mass transfer, Chinese hamster ovary cell growth, and antibody production 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 Ó 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/m 3 ) P 0 Power number (marine 0.4, Rushton 5) N Agitation rate (rev/s) D Impeller diameter (m) n Number of impellers l Viscosity (mPa s) h m Mixing time (s) e T Mean specific energy dissipation rate (W/kg) k L a O Mass transfer coefficient for oxygen in culture medium (h -1 ) k L a sO 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

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Transcript of Jurnal Turbin Gas

Page 1: 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

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DOI 10.1007/s00449-011-0532-0

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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.

References

1. Mirro R, Kevin V (2009) Which impeller is right for your cell-

line? vol 7. BioProcess International, USA

2. Schroder M, Matischak K, Friedl P (2004) Serum- and protein-

free media formulations for the Chinese hamster ovary cell line

DUKXB11. J Biotechnol 108(3):279–292

3. Urlaub G, Chasin LA (1980) Isolation of Chinese hamster cell

mutants deficient in dihydrofolate reductase activity. Proc Natl

Acad Sci USA 77(7):4216–4220

4. Eagle H (1955) Nutrition needs of mammalian cells in tissue

culture. Science 122(3168):501–514

5. Barnes D, Sato G (1980) Methods for growth of cultured cells in

serum-free medium. Anal Biochem 102(2):255–270

6. Bettger WJ, Ham RG (1982) Advances in nutritional research.

Plenum Press, New York

7. Barnes D (1985) Nutritional and hormonal requirements of

mammalian cells in culture. World Rev Nutr Diet 45:167–197

8. Blanch HW, Clark DS (1997) Biochemical engineering. Marcel

Dekker, New York

9. Bibila TA, Ranucci CS, Glazomitsky K, Buckland BC, Aunins

JG (1994) Monoclonal-antibody process-development using

medium concentrates. Biotechnol Prog 10(1):87–96

10. Hu WS, Aunins JG (1997) Large-scale mammalian cell culture.

Curr Opin Biotechnol 8(2):148–153

11. Sandadi S, Ensari S, Kearns B (2005) Heuristic optimization of

antibody production by Chinese hamster ovary cells. Biotechnol

Prog 21(5):1537–1542

12. Meier S (2005) Scaleup/scaledown and mixing in industrial cell

culture reactors. Biochemical engineering XIV, Harrison Hot

Springs, BC

13. Oh SKW, Nienow AW, Alrubeai M, Emery AN (1989) The

effects of agitation intensity with and without continuous sparg-

ing on the growth and antibody-production of hybridoma cells.

J Biotechnol 12(1):45–61

14. Oh SKW, Nienow AW, Alrubeai M, Emery AN (1992) Further-

studies of the culture of mouse hybridomas in an agitated bio-

reactor with and without continuous sparging. J Biotechnol

22(3):245–270

15. Moran EB, McGowan ST, McGuire JM, Frankland JE, Oyebade

IA, Waller W, Archer LC, Morris LO, Pandya J, Nathan SR,

Smith L, Cadette ML, Michalowski JT (2000) A systematic

approach to the validation of process control parameters for

monoclonal antibody production in fed-batch culture of a murine

myeloma. Biotechnol Bioeng 69(3):242–255

16. Sandadi S, Ensari S, Kearns B (2006) Application of fractional

factorial designs to screen active factors for antibody production

by Chinese hamster ovary cells. Biotechnol Prog 22(2):595–600

17. Varley J, Birch J (1999) Reactor design for large scale suspension

animal cell culture. Cytotechnology 29(3):177–205

18. Mardikar SH, Niranjan K (2000) Observations on the shear

damage to different animal cells in a concentric cylinder vis-

cometer. Biotechnol Bioeng 68(6):697–704

19. Mollet M, Ma NN, Zhao Y, Brodkey R, Taticek R, Chalmers JJ

(2004) Bioprocess equipment: characterization of energy dissi-

pation rate and its potential to damage cells. Biotechnol Prog

20(5):1437–1448

20. Meier SJ, Hatton TA, Wang DIC (1999) Cell death from bursting

bubbles: role of cell attachment to rising bubbles in sparged

reactors. Biotechnol Bioeng 62(4):468–478

21. Murhammer DW, Goochee CF (1990) Sparged animal-cell bio-

reactors—mechanism of cell-damage and Pluronic F-68 protec-

tion. Biotechnol Prog 6(5):391–397

22. Mollet M, Godoy-Silva R, Berdugo C, Chalmers JJ (2007) Acute

hydrodynamic forces and apoptosis: a complex question. Bio-

technol Bioeng 98(4):772–788

23. Nienow AW (2006) Reactor engineering in large scale animal

cell culture. Cytotechnology 50(1–3):9–33

24. Junker BH, Hunt G, Burgess B, Aunins J, Buckland BC (1994)

Modified microbial fermenter performance in animal-cell culture

and its implications for flexible fermenter design. Bioprocess Eng

11(2):57–63

25. Nienow A (2008) Mixing studies with elephant ear impellers: are

they low shear agitators? AIChE Annual Meeting, Philadelphia

26. Nienow AW, Langheinrich C, Stevenson NC, Emery AN, Clay-

ton TM, Slater NKH (1996) Homogenisation and oxygen transfer

rates in large agitated and sparged animal cell bioreactors: some

implications for growth and production. Cytotechnology

22(1–3):87–94

27. Bailey JE, Ollis DF (1986) Biochemical engineering fundamen-

tals, 2nd edn. McGraw-Hill, New York

28. Mostafa SS, Gu XJ (2003) Strategies for improved dCO(2)

removal in large-scale fed-batch cultures. Biotechnol Prog

19(1):45–51

29. Aunins JG, Henzler H-J (1993) Aeration in cell culture bioreac-

tors. In: Stephanopoulos G (ed) Biotechnology: a multi-volume

comprehensive treatise. VCH Verlag, Weinheim

30. Wong DCF, Wong KTK, Goh LT, Heng CK, Yap MGS (2005)

Impact of dynamic online fed-batch strategies on metabolism,

productivity and N-glycosylation quality in CHO cell cultures.

Biotechnol Bioeng 89(2):164–177

31. Nam JH, Zhang F, Ermonval M, Linhardt RJ, Sharfstein ST

(2008) The effects of culture conditions on the glycosylation of

secreted human placental alkaline phosphatase produced in Chi-

nese hamster ovary cells. Biotechnol Bioeng 100(6):1178–1192

32. Goochee CF, Monica T (1990) Environmental-effects on protein

glycosylation. BioTechnology 8(5):421–427

33. Nienow AW (1997) On impeller circulation and mixing effec-

tiveness in the turbulent flow regime. Chem Eng Sci

52(15):2557–2565

34. Gogate PR, Beenackers AA, Pandit AB (2000) Multiple-impeller

systems with a special emphasis on bioreactors: a critical review.

Biochem Eng J 6(2):109–144

35. Hari-Prjitno D et al (1998) Gas–liquid mixing studies with mul-

tiple up- and down-pumping hydrofoil impellers: power charac-

teristics and mixing time can. J Chem E 76:1056–1068

36. Nienow A (1996) Gas liquid mixing studies: a comparison of

Rushton turbines with some modern impellers. Chem Eng Res

Des Trans I Chem E Part A 74:417–423

37. Xia JY, Wang YH, Zhang SL, Chen N, Yin P, Zhuang YP, Chu J

(2009) Fluid dynamics investigation of variant impeller

Bioprocess Biosyst Eng (2011) 34:819–832 831

123

Page 14: Jurnal Turbin Gas

combinations by simulation and fermentation experiment. Bio-

chem Eng J 43(3):252–260

38. Bowers JS (2008) Sparger and surface gas transfer for cell culture

bioreactors. AIChE Annual Meeting, Philadelphia

39. Ozturk SS, Riley MR, Palsson BO (1992) Effects of ammonia

and lactate on hybridoma growth, metabolism, and antibody-

production. Biotechnol Bioeng 39(4):418–431

40. Ozturk SS, Palsson BO (1990) Effects of ammonia and lactate on

cell-growth, metabolism and monoclonal-antibody production.

Abstracts of Papers of the American Chemical Society 200:

6-Biot

41. Patel SD, Papoutsakis ET, Winter JN, Miller WM (2000) The

lactate issue revisited: novel feeding protocols to examine inhi-

bition of cell proliferation and glucose metabolism in hemato-

poietic cell cultures. Biotechnol Prog 16(5):885–892

42. Sandadi S (2009) Ph.D. Dissertation. Rutgers University,

Piscataway

832 Bioprocess Biosyst Eng (2011) 34:819–832

123

Page 15: Jurnal Turbin Gas

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