Undergraduate Thesis - Joel John

METABOLITE CONSUMPTION AND PRODUCTION
PATTERNS IN FED – BATCH AND PERFUSION CELL
CULTURES
A Graduate Project Report submitted to Manipal Academy of Higher Education
in partial fulfilment of the requirement for the award of the degree of
BACHELOR OF TECHNOLOGY
in
BIOTECHNOLOGY
Submitted by
Joel John
Under the guidance of
Dr. Neelima Boddapati Dr. Ramachandra Murty V
Lead Research Scientist & Professor
Wipro GE-Healthcare MIT, Manipal
DEPARTMENT OF BIOTECHNOLOGY
MANIPAL INSTITUTE OF TECHNOLOGY
(A Constituent College of Manipal Academy of Higher Education)
MANIPAL – 576104, KARNATAKA, INDIA
July 2019

ii
ACKNOWLEDGMENTS
Firstly, I offer my sincerest gratitude to my supervisor, Dr Neelima Boddapati, who has
encouraged me throughout my thesis with patience and knowledge while allowing me the
room to work as per my capabilities. I especially thank my manager Mr. Umesh Pai for
being the constant pillar of support and being accessible and willing to help me that
paved way for smooth research work.
This work would not have been possible without the tremendous support extended by
Mrs. Debalina Basak. I owe my most sincere gratitude to her for the exemplary guidance,
constant encouragement and careful monitoring throughout. I wish to express my sincere
thanks to Ms. Megha Biradar for her encouragement and friendly approach during my
tenure at GE. I would like to thank all the members of GE Healthcare Life Sciences team
for being me a constant source of inspiration and extending their support in all possible
ways for the successful completion of my project.
I would like to express my sincere gratitude to my guide Dr V. Ramachandra Murty, Dr
Divyashree M. S, and Ms. Archana M. Rao for their support and guidance, suggesting
changes and following up on my report. I express my heartfelt thanks to our beloved
H.O.D. Dr Ramananda Bhat, for his support via the department. I express my deep sense
of appreciation to all the faculty members and non-teaching staffs of Department of
Biotechnology, MIT.
I would like to express my greatest admiration for my parents for their support. I thank
all my friends for their help, discussions and useful suggestions. I have great pleasure to
acknowledge peace cottage, my roomie Mr. Aditya S. Pande and all that awesome
hangout spots of this city, in providing me the required space and ambience to enjoy and
successfully complete this thesis.
Finally, I thank all those who helped me directly or indirectly for the successful
completion of this thesis.

iii
ABSTRACT
The ever-increasing demand for biological derivatives like monoclonal antibodies (abs),
recombinant proteins, etc has driven the need for cost and time effective ways for
achieving higher titters with the acceptable quality of product in the biopharmaceutical
industry. A deep understanding of causes and effects of metabolites on key process
indicators and critical to quality attributes in large scale cultures will aid in achieving the
appropriate quantity and quality of the product. In the present study, CHO-S cells were
expanded in ReadyToProcess WAVE™ 25 single use bioreactor under
optimal/experimental process conditions to facilitate Fed-Batch and Perfusion cultures.
Fed batch cultures, FB08 and FB09 were maintained at optimal conditions; while in
FB10 and FB13 were maintained under sub-optimal conditions of temperature and
nutrient limitation, respectively. Both FB10 and FB13 exhibited lower viable cell
concentrations (VCC) than FB08 and FB09. The pH of the medium in FB 13 was
significantly higher on Day 0, indicating that the cells experienced pH stress from the
beginning of the culture. Hence, the lower cell counts in FB13 are more a consequence of
pH induced stress than nutrient limitation stress. The metabolite profiles of FB10 indicate
a slower metabolic rate anticipated due to the lack of optimum temperature for growth. In
contrast, FB13 exhibited higher metabolic rate and reached near zero concentrations for
both glucose and lactate. FB13 has exhibited a shorter longevity than other cultures as
expected due to the non-availability of glucose and glutamine as supplementation.
Perfusion mode of culture was conducted, to understand the metabolic-growth profiles
when cultured under a linear and non-linear perfusion feed strategy. Both the cultures
exhibited extended log-phase, similar cell counts and metabolite profiles, despite the
difference in their perfusion strategies.
The work done herein will act as a basis for understanding the metabolite consumption
and production trends under varied culture conditions. Further research is warranted to
generate good understanding of the interplay of the various metabolic pathways in
conditions of stress.
Keywords: Single-use bioreactor, fed-batch, perfusion, CHO-S cells, ReadyToProcess
WAVETM
25, XcellerexTM
XDR-10, UNICORNTM
.

iv
LIST OF TABLES
TABLE
NO
TABLE TITLE
PAGE
NO
1.1 Characteristics of Small Molecule Pharmaceuticals vs. Biologics 2
1.2 Biologics approved in India 3
3.1 List of reagents utilized and their source 16
3.2 Composition of Cell culture media and solutions 17
3.3
Process Design for carrying out fed-batch operations on WAVETM
25
bioreactor
19
3.4
Process Design for carrying out perfusion operations on WAVETM
25
bioreactor 20
3.5 Instruments used in the assessing the cell culture samples 21
4.1 Fed-batch (FB08) with 2% of Feed-A and 0.2 % of Feed-B feeding 39
4.2 Fed-batch (FB09) with 2% of Feed-A and 0.2 % of Feed-B feeding 40
4.3 Fed-batch (FB10) with 4% of Feed-A and 0.4% of Feed-B feeding 41
4.4 Fed-batch (FB13) with 2% of Feed-A and 0.2% of Feed-B feeding 42
4.5 Perfusion (PERF03) with linearized perfusion rate till Day 14 43
4.6 Perfusion (PERF04) with non-linear perfusion rate till Day 13 44
4.7 Specific Growth rate in Fed Batch culture (FB08) in Cellbag-5L 45
4.11 Specific Growth rate in Perfusion culture (PERF03) in Cellbag-2L 49
4.12 Specific Growth rate in Perfusion culture (PERF04) in Cellbag-2L 50

v
LIST OF FIGURES
FIGURE
NO
FIGURE TITLE
PAGE
NO
1.1 Biopharmaceutical Manufacturing Stages 4
1.2
Modes of operations of culturing in batch, fed-batch and continuous
operations.
5
1.3 Schematic representation of a Bioreactor system design process” 6
2.1
Operation principle (A) and kinetics (B) of cell growth, nutrient
consumption, and product formation during batch, fed-batch,
perfusion and continuous operations.
8
2.2
An enclosed chemostat depicting the influx of feed and efflux via
harvesting
10
2.3 Perfusion culture run in Cellbag-2L with internal floating filter 12
2.4 ReadyToProcess WAVE 25 (GE Healthcare, USA) 13
2.5 GE Xcellerex Disposable Reactor (XDR) (GE Healthcare, USA 13
2.6 Rocking motion with a WAVE Biosystem 14
2.7
Glucose and Glutamine metabolism via Glycolysis, Krebs and
Glutaminolysis
15
4.1
Metabolite Profiles of Fed Batch cultures FB08, FB09, FB10 and
FB13
23-24
4.2
Cell growth (a) and cell specific growth rate (b) profiles of FB08,
FB09, FB10 and FB13
25
4.3 pH and dissolved gases profile of FB08, FB09, FB10 and FB11 27
4.4 Glucose and lactate profiles of FB08, FB09, FB10 and FB11 28
4.5
Glutamine, glutamate and ammonium profiles of FB08, FB09, FB10
and FB13
29
4.6 Perfusion feed strategies of PERF03 and PERF04 30
4.7 Metabolite Profiles of Perfusion cultures PERF03 and PERF04 31
4.8 Metabolite Profiles of Perfusion cultures PERF03 and PERF04 32
4.9 pH and gas profiles of PERF03 and PERF04 32
4.10 Glucose and lactate trends for PERF03 and PERF0 33
4.11 Glutamine glutamate and ammonium trends for PERF03 and PERF04 34

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LIST OF ABBREVIATIONS
% Percentage SS Stainless steel
°C Degree Celsius SU Single-use
µm Micrometer TCC Total cell concentration
C Carbon USP Upstream processing
CHO Chinese hamster ovary w/v Weight/ volume
CIP Clean-in-Place VCC Viable cell concentration
DCO2 Dissolved carbon dioxide
XDR XcellerxTM
XDR Cell culture
bioreactor systems
DMSO Dimethyl sulfoxide W25 WaveTM
25 Cell culture
bioreactor systems
DO Dissolved oxygen
DOOPT Dissolved oxygen optical sensor
DSP Downstream processing
G Gram
g/L Gram per liter
Gluc/Glc Glucose
Gln Glutamine
Glu Glutamate
HEK Human embryonic kidney
K+ Potassium ion
kg Kilogram
L Liter
Lac Lactate
M Molar
mAbs Monoclonal antibodies
mL Milliliter
mL/day Milliliter/day
mM Millimolar
mOsm Milliosmolale
N Nitrogen
Na+ Sodium ion
NaOH Sodium Hydroxide
NH4,+3 Ammonium Ions
pCO2 Partial pressure of carbon dioxide
pH Power of hydrogen
pHOPT pH Optical sensor
pO2 Partial pressure of oxygen
rDNA Recombinant DNA
rpm Revolutions per minute/ Rocks per
minute (For RTP W25)
SIP Steam-In-Place

vii
TRADEMARKS
All trademarks are the property of their respective owners. In lieu of putting a trademark
symbol in every occurrence of a trademark name, I hereby state that I am using the
names with no intention of infringement of the trademark.

viii
CONTENTS
ACKNOWLEDGEMENT …………………………………………………… ii
ABSTRACT …………………………………………………………. iii
LIST OF TABLES …………………………………………………………. iv
LIST OF FIGURES …………………………………………………………. v
ABBREVIATIONS …………………………………………………………. vi
TRADEMARKS …………………………………………………………. vii
CHAPTER 1 INTRODUCTION……………………………………………. 1
1.1 BIOPHARMACEUTICAL MANUFACTURING……………. 3
1.2 FACTORISED DESIGN OF BIOREACTOR SYSTEMS……. 5
1.3 SCOPE…………………………………………………………. 7
1.4 OBJECTIVES………………………………………………….. 7
CHAPTER 2 REVIEW OF LITERATURE.………………………………. 8
2.1 MODES OF OPERATIONS IN UPSTREAM BIOPROCESS.. 8
2.1.1 BATCH CULTURE…………………………………………… 9
2.1.2 FED-BATCH CULTURE……………………………………... 9
2.1.3 CONTINOUS CULTURES – CHEMOSTAT………………... 10
2.1.4 PERFUSION CULTURES……………………………………. 11
2.2 SINGLE USE BIOREACTORS FROM GE HEALTHCARE... 13
2.3 METABOLIC PROFILES IN MAMMALIAN CULTURES… 14
CHAPTER 3 MATERIALS AND METHODS…………………................. 16
3.1 REAGENTS AND SOURCES………………………………... 16
3.2 CELL CULTURE MEDIA AND SOLUTIONS……………… 17
3.3 STORAGE OF CELLS………………………………………... 18
3.4 REVIVAL AND MAINTENANCE OF CELLS……………… 18
3.5 CULTURE OF CELLS IN ReadyToProcess WAVETM
25…… 18
3.5.1 FED-BATCH MODE OF CULTURING……………………... 21
3.5.2 PERFUSION MODE OF CULTURING……………………… 21
3.6 COMPUTATION OF CELL GROWTH KINETICS AND
METABOLIC PROFILES……………………….……………. 22
3.6.1 TO COMPUTE SPECIFIC GROWTH RATES………………. 22
3.6.2 TO COMPUTE CONSUMPTION-GENERATION PROFILE. 22

ix
CHAPTER 4 RESULTS……………………...…………………................... 23
4.1 FED-BATCH CULTURE TO ReadyToProcess WAVETM
25.. 23
4.2 PERFUSION CULTURE TO ReadyToProcess WAVETM
25... 30
CHAPTER 5 DISCUSSION AND FUTURE SCOPE……………………... 35
5.1 DISCUSSION…………………………………………………. 35
5.2 FUTURE SCOPE……………………………………………… 37
REFERENCES……………………………………………………...................... 38
ANNEXURES…………………………………………………………………… 39
PROJECT DETAILS…………………………………………………………… 51

1
CHAPTER 1
INTRODUCTION
Today, the pharmaceutical giants and medical world focuses on providing its end users
with the most advanced therapies at hand. It has been proven that biologics provides the
most apt therapeutic approach towards this cause. Previously, the pharmaceutical markets
used to dwell around synthetically and chemically prepared drug derivatives which is
applicable to more than 90% of commercially marketed drugs. Biologics or
biopharmaceuticals are drug products derived or semi synthesized from biological sources,
that emerged out to be the most advanced therapy medicinal product as coined by EMA
(European Medicines Agency). Today, due to the recent advancements in the field of
Bioprocess engineering and Unit operations development in both upstream and
downstream processes, these biological derivatives are synthesised to include vaccines,
recombinant therapeutic proteins, and other semi synthesizers as well. Biologics are
synthesised within a biological environment. Bioreactor systems provide an ideal
environment to promote growth of cells to achieve high productivity titers. The complexity
of biologics in comparison to synthetic drugs has been summarised in Table 1.1. Over the
years the price of synthetic medicines has been optimized through extensive research, the
same is deemed to enhance the productivity of biologics through advancements in
bioprocesses and single use systems.
Biologics are considered today as a prominent derivative of the therapeutic revolution,
leading to massive productions of therapeutic products with a superior on-target efficiency,
lower risk or side effects and an ability to cure the disease instead of mere symptom
suppression which contrasts with the conventional synthetic and chemically defined
therapeutics (Lybecker, 2016). Most of the biopharmaceuticals are cumbersome to be
identified or characterized and tend to be heat liable and highly susceptible to microbial
contamination. In this manner, it is important to utilize aseptic standards throughout
manufacturing stages, in contrast to most customary commercially available drugs.
Most of the biologics are manufactured via recombinant DNA (rDNA) technology where
cells are genetically engineered to synthesize the protein of interest. Biologics include
therapeutic; fusion proteins, vaccines, and monoclonal antibodies (mAbs) which have led
to an epitome shift in treatment of diseases like diabetes, cancer, blood and blood related

2
disorders, allergies, hormone related disorders, cardiovascular diseases, major autoimmune
disorders such as rheumatoid arthritis; it is also employed in gene and cell therapy
treatment. (Lybecker, 2016; Agrawal, 2015).
Examples of leading biological agents used within the biopharmaceutical market includes:
Trastuzumab (Herceptin), Etanercept (Enbrel), Bevacizumab (Avastin), Rituximab
(Rituxan), and Adalimumab (Humira) (Lybecker, 2016) (Table 1.2).
Table 1.1: Characteristics of Small Molecule Pharmaceuticals vs. Biologics
Source: http://lawarencepress.com/ojs/index.php/JPBMS/article/view/225/html_103

3
Table 1.2: Biologics approved in India
Source: http://lawarencepress.com/ojs/index.php/JPBMS/article/view/225/html_103
1.1 BIOPHARMACEUTICAL MANUFACTURING
The production of biologics requires expression systems available (such as microbial,
insect, animal and plant cells), of which the mammalian cells are most apt for
biopharmaceutical production since mammalian cells undergo Post Translational
Modifications, such as glycosylation, which are essential for functions of biological
significance, i.e to target protein (Yang and Butler, 2000). Out of the 58
biopharmaceuticals approved between 2006 to 2010, 32 of them were produced from
mammalian cells (Kim et al., 2011). The most commonly cultured mammalian cell lines
include Chinese hamster ovary (CHO) and its GS-variants, human embryonic kidney
(HEK)-293, baby hamster kidney (BHK), mouse myeloma-derived NS0, and Vero.
Approximately 70% of the recombinant therapeutic production is carried out by CHO cells
owing to its ability to express a wide variety of recombinant proteins, robust nature,
immense adaptability and ease of maintenance (Kim et al., 2011).
Biopharmaceutical manufacturing or bioprocessing is predominantly structured into
upstream and downstream processes (Fig 1.1). Upstream processing is the initiated by
culturing cells and it includes all the steps related to inoculum and media development,
improvement of inoculum by genetic engineering process and optimization of cell growth
kinetics which play a key role for the product development. This is followed by the

4
downstream process where the relevant material from upstream is processed to meet purity
and quality requirements. Downstream processes involve cell disruption (centrifugation,
ultrasonication), if necessary, purification (filtration, chromatography) and polishing. At
the end of downstream process, we obtain the product free from cells, media, metabolites
and other impurities.
Fig 1.1: Biopharmaceutical Manufacturing Stages
Source: https://doi.org/10.1016/B978-0-08-100623-8.00024-4
The modes of operations in upstream bioprocessing to achieve an improved productivity
are quite diversified. For example, Mammalian cell culturing can be achieved via different
operation modes, and are generally classified as batch, fed-batch, continuous and perfusion
cultures (Fig 1.2). Of the varied modes of process operations, the batch operation is the
most established, least complex; expensive bioreactor operation mode where all the media
and cells are added to the reactor at the start of operation and the product is harvested once
its maximum concentration is reached (Larroche et al., 2016). Whereas in fed-batch
operation, additional nutrients such as feed concentrates are supplemented to the culture to
overcome growth limitations; extend the culture runtime and achieve higher cell densities.
Commercially fed batch operations are considered commercially feasible due to the above-
mentioned prospects (Larroche et al., 2016) In a continuous culture mode of operation,
there is a constant supply of media to the culture which is accompanied by constant
removal of culture thereby maintaining a steady state in the bioreactor, (Estes and Langer,
2017). Perfusion operation is a type of continuous operation where the cells and the
product are retained within the bioreactor with the help of a retention device
internally/externally (Fig 1.2).

5
Fig 1.2: Modes of operations of culturing in batch, fed-batch and continuous
operations.
Source: DOI: 10.1016/j.procbio.2016.09.032
1.2 FACTORISED DESIGN OF BIOREACTOR SYSTEMS
A concatenation of decisions based on fundamental concepts of biochemistry,
metabolomics and marketing paves the way into the selection and design of a cell culture
system, the harmony of understandings between these fields contributes to the design of
this optimal biological environment – aiming at maximizing productivity rates while
beguiling costs. A key concern to be dealt with while designing a compatible bioreactor
system lies at achieving optimal cell concentrations, kLa kinetics and specific rate of heat
evolution. At a biopharmaceutical productivity scale, the system designs are pinned at
achieving the required commercial objectives, necessarily fulfilling the market-product
needs. The price of a bioreactor relies on the operational costs going hand in hand with the
equipment amortization, and on extremities the costs in association with the legal &
regulatory approvals. A series of biochemical, physiological constraints regarding the cells
in culture, linked with the market-customer requirements creates a network of decisions,
that leads to the design of a biosystem as shown below (Fig 1.3).

6
Fig 1.3: Schematic representation of a Bioreactor system design A network of decisions
from a biological; engineering; process design; and market aspects, which in compliance, gives rise to an
optimal design of a bioreactor system.
Source: (Asenjo, Merchuk, 2010)

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1.3 SCOPE
Over the past decades, large scale analysis has been conducted by on various supplements;
and feed strategies that could aid and influence the mammalian cells to achieve a
substantial viable cell density which aids us in estimating the cell lines’ volumetric
productivity. Today, studies have concluded that certain physical parameters like
Temperature, pressure, pH etc. under optimum operating conditions helps to attain this
required productivity levels. To understand the reason behind achieving the productivity
levels, its crucial to also study the metabolic cycles leading to the consumption/generation
of metabolites within the culture media, including the metabolites that are supplemented,
promoting higher cell counts, prolonging cellula viability , higher titers and most
importantly, a biologically stable product. Excessive supplementation is known to generate
overflow metabolites that in turn alter the culture viability and hampers with the
volumetric productivity, which are undesirables in biopharmaceutical manufacturing.
1.4 OBJECTIVES
i. Analysing cell count and metabolite profiles achieved by fed-batch mode of
operation under optimal and experimental conditions of growth.
ii. Analysing cell count and metabolic profiles achieved by perfusion under linear and
non-linear perfusion feed strategies

8
CHAPTER 2
REVIEW OF LITERATURE
2.1 MODES OF OPERATIONS IN UPSTREAM BIOPROCESS
Initial stages of biopharmaceutical manufacturing are oriented towards culturing of cells
in discontinuous modes (batch, fed-batch) and continuous modes (chemostat, perfusion)
(Fig 2.1 (A)). Each mode of operation provides vivid data profiles for cell growth,
metabolite production/consumption and primarily product synthesis.
Fig 2.1: Operation principle (A) and kinetics (B) of cell growth, nutrient
consumption, and product formation during batch, fed-batch, perfusion and
continuous operations.
Source: https://www.slideshare.net/yongkangbirdnest/lecture-5-bioprocess-technology-operation-mode-and-
scale
Batch and fed-batch modes rule the biopharmaceutical industry even though continuous
modes have been effectively employed for commercial production of several
biopharmaceuticals. Batch and fed-batch processes are conducted over small scale
frameworks like flasks or bags, or in suspension reactors for bigger scale, whereas
perfusion process is preferably cultured in bags or larger scale bioreactors.

9
2.1.1 BATCH CULTURE
Batch processing, both upstream and downstream, has been the predominant bioprocessing
paradigm for a long time (Langer and Rader, 2014). Cell growth and viability in a batch
culture are facilitated without further addition of supplements during the culture period.
The cells display stages of lag-phase, exponential phase, stationary phase and death phase
as per Monods’ Kinetics. Substrate restraint, metabolite inhibition and apoptosis are
known to reduce cell viability and induce cell death. Compressed Air or oxygen for
aeration, CO2 or base for pH-control and anti-foam agents are additionally added to the
process. Batch processes are typically begun with an initial cell density of approx. 0.1-0.2
E6/mL and is operational for a period of 1–2 weeks. On comparison to fed-batch and
continuous cultures, these cultures are simple, reliable and often applied in lab as well as in
industrial scale during the initial stages of seed train. Batch cultures are subjected to a
determined volume of media, as a result over the course of the culture the media turn to be
infeasible and this hinders its productivity (Fig 2.1 ). However, higher substrate
concentrations may induce substrate inhibition or a high cell specific substrate uptake rate
prompting overflow metabolism.
2.1.2 FED-BATCH CULTURE
The application of fed-batch processes, product yields can be significantly enhanced by the
addition of surplus nutrients by supplementing nutrients as per a suitable feeding strategy
(Fig 2.1 (B)) (Po¨rtner 2015). The reactor vessel is first filled to 1/3 or 1/2 of the total
reactor capacity and started as batch culture, once the substrate is expanded or has reached
growth limiting values, there is an addition of nutrients like glucose, amino acids and
vitamins with trace elements are supplemented as per media requirements. These nutrients
are usually in their concentrated forms to avoid substantial dilution. Potential issues arising
due to metabolic fluxes during cultivation, exponential cell growth and an increase in
demand for nutrients and oxygen can be overcome with by conducting suitable feed
strategies based on the fundamental knowledge on cell growth which otherwise leads to
risks of underfeeding or overfeeding of the highly concentrated supplement medium
leading to formation of overflow metabolites which could largely affect volumetric

10
productivity of the culture. Apart from the high cell densities that are achieved through
fed-batch process, there is also an accumulation of metabolites, chiefly lactate, which are
detrimental to growth and productivity. This is subsidized via the substitution of glucose
by its derivatives like mannose or galactose, or by utilizing synthetically defined feeds,
optimization of feed media by metabolic flux analysis, increasing copper concentration,
limiting glucose levels to avoid overflow metabolism, implementation of pH control to
mitigate the effects lactate accumulation (Po¨rtner, 2015). These strategies involve greater
effort of control and appropriate equipment. Fed-batch culture are advantageous due to its
benefits like extended growth phase, achievable higher cell densities (1-10 E6/mL) and a
better volumetric productivity.
2.1.3 CONTINUOUS CULTURES – CHEMOSTAT
A continuous culture portrays an unceasing influx and efflux of feed and spent/harvest
media respectively, thereby achieving steadfast supply of nutrients into the culture vessel
(Fig 2.1 (B), Fig 2.2).
Fig 2.2: An enclosed chemostat depicting the influx of feed and efflux via harvesting
Source: https://en.wikipedia.org/wiki/Chemostat

11
On inspection of the harvest line, its observed that the harvest contains the cells along with
the plummeted media composition. Its assumed to achieve steady state: a constant growth
rate, with a constant maintenance of culture parameter, via homogenous mixing within the
bioreactor. The cell density, substrate and product concentrations are proportional to the
dilution rate which is determined by the ﬂow rates for media influx and efflux. The
incremental dilution rate leads to an increasing cell density. At critical dilution rates (Dcrit),
the maximum growth rate is said to be theoretically achievable. If the dilution rate is
increased beyond the Dcrit, the cell density decreases as the cells are unable to compensate
for the wash-out. Substrate concentration increases proportionally with dilution rate and
reaches maximum close to the Dcrit (Po¨rtner, 2015). The accumulation of waste
metabolites is minimized by continuous cultures which are detrimental to the culture’s
growth and productivity. The prominent disadvantage of continuous process is the
extensive amount of media requirement and potential underutilization of the supplemented
media. To overcome the underutilization of media and increase the volumetric productivity
of the culture, a variant of chemostat - perfusion culture is practiced.
2.1.4 PERFUSION CULTURES
Perfusion cultures are preferred by pharmaceutical manufacturers as a strategy to reduce
costs while increasing quality and productivity. Perfusion cultures are driven by its
outcome of quality, flexibility, and cost savings within biopharmaceutical industries. In the
2000s, perfusion technologies were restricted to manufacturing of recombinant blood-
clotting factors and enzymes which were found to be highly unsteady within fed-batch
systems. Perfusion was implemented for biologics which were toxic to the synthesizing
cell line thereby hindering production in fed-batch conditions (Lehr and Lyons, 2016).
Perfusion like chemostat process involves the simultaneous removal of spent media and
product, parallelly complemented with fresh media while retaining cells inside the
bioreactor with a help of an interfacing filtration unit (e.g. microfiltration (Fig 2.3), spin
filters, centrifuges among others) to the suspension culture (Po¨rtner, 2015). The volume of
suspension culture in the bioreactor is maintained at steady levels. Cell concentrations as
high as 50-100 E6/mL can be achieved by maintaining high specific productivities .

12
Biosciences lab, Wipro GE Healthcare Life Sciences ©
Fig 2.3: Perfusion culture run in Cellbag-2L with internal floating filter
The main purpose of carrying out perfusion culture is to sustain long-term continuous
cultures by achieving a high cell density and viability lasting for a long period of time. The
high volumetric perfusion rates, between 1–10 vessel volumes per day facilitates in
reducing the residence time of product within the reactor. This ephemeral retention time at
steady-state conditions delivers a more homogeneous product quality properties (Po¨rtner,
2015).
Over a chemostat configuration the perfusion process demands additional equipment like
the retention devices, pumps for feeding, harvesting, culture re-circulation, storage tanks
for feed and harvest. The quantity of media required to finish a moderate to long duration
culture run can be excessive. Process development and characterization can be more
unpredictable. Another possible disadvantage of continuous cultivations is its likelihood
for variability over the duration of the culture such as genetic instability, i.e. mutations that
might diminish product synthesis.
Continuous processing requires more process knowledge, equipment and technological
advances than incremental manufacturing. Successful implementation of continuous
processing by industries requires successful integration and coordination of every
component process involved with the next process.

13
2.2 SINGLE-USE BIOREACTORS FROM GE HEALTHCARE, USA
There are two platforms of single-use bioreactors from GE Healthcare: ReadyToProcess
WAVE™ 25 (Fig 2.4) and Xcellerex™ (Fig 2.5). WAVE 25 follows a horizontal rocking
platform, whereas the XDR-10 has a more conventional vertical cylindrical design.
Fig 2.4: ReadyToProcess WAVE 25 (GE Healthcare, USA): Cellbag-50 L DOOPT II and
pHOPT, rocker, gas mixer and DO/pH controller (ReadyToProcess™ CBCU), peristaltic pump,
UNICORN™ software.
Source:http://cellculturedish.com/2013/12/raising-bar-rocking-bioreactors-introducing-readytoprocess-wave-
25-system/
Fig 2.5: GE Xcellerex Disposable Reactor (XDR) (GE Healthcare, USA): XDR vessel
containing a XDR-10 Pro PLUS Bag with frame-mounted I/O cabinet and Wonderware™ software.
Source:https://www.gelifesciences.com/en/au/shop/cell-culture-and-fermentation/stirred-tank-
bioreactors/stirred-tank-bioreactor-systems/xcellerex-xdr-10-single-use-stirred-tank-bioreactor-p-05545
In WAVE 25, the cells and culture media are aseptically transferred into a Cellbag which
is placed on a rocking unit. The mobilization of the culture media is induced by the
rocking motion thereby eliminating the need for agitators or sparges. These Cellbag

14
bioreactors doesn’t require pre-sterilization, and is versatile (facilitates suspension,
microcarrier, batch, fed-batch or perfusion cultures). Online pH and DO profiles are
measured in real time by the help of optical probes placed into the reactor, while the online
weight measurement is calibrated and estimated using a load cell onto which the cellbag is
rested upon. WAVE bioreactors are dis-advantageous as they are not designed for
achieving larger culture volumes, as mammalian cells undergo shear stress due to rocking
at higher process volumes.
Fig 2.6: Rocking motion with a WAVE Biosystem
Source:”http://www.ucdenver.edu/academics/colleges/medicalschool/centers/cancercenter/Research/sharedre
sources/TissueBiobanking/Documents/Wave.pdf”
XDR bioreactors are designed like a stainless-steel bioreactor with the added flexibility of
disposable bags. The XDR-10 benchtop bioreactor system is designed as a small-scale
stirred-tank bioreactor consisting a cylindrically shaped container vessel with to heating
blankets that support a 10 L disposable bag. The disposable bag holds a built-in agitation
assembly, multiple sparger ports; ports for media addition and cell harvest, several aseptic
ports for online measurements of process parameters like pH, DO, and DCO2. The user
interface is based on Wonderware software.
2.3 METABOLIC PROFILES IN MAMMALIAN CULTURES
“Feed to Need” strategies were utilised in commercial fed batch process but was
determined to be impractical since the biomass (specific growth) and cell metabolic rates
are inconsistent and dynamically varies over time. Due to the paucity, the modern strategy
for feeding follows a concept of holding the culture at a fixed metabolic state by following
“adaptive feeding in real time”, by prefixing the desired concentration within the batch and
then stoichiometrically feeding in supplements in real time (Herwig et al., 2016). Cells
needs to be periodically supplemented with carbon and nitrogen source (Glucose and
Glutamine) in order to facilitate growth and yield higher volumetric productivities.

15
Fig 2.7: Glucose and Glutamine metabolism via Glycolysis, Krebs and
Glutaminolysis.
Source: DOI 10.15252/embj.201696151
Excessive feeding is recognized to induce a metabolic imbalance and stress to the cell lines
and lead to the formation of overflow metabolites, that affects the volumetric productivity.
Recent studies have recognised that lactic acid profile in a mammalian cell culture affects
the maximum cell count and final product concentrations. Higher lactic acid titers have
been recorded to decrease pH from its optimal conditions which decreases the cell
proliferation, metabolism and productivity. Maintaining the physio-chemical process
parameters at optimal or sub optimal condition is necessary to achieve potential results.
Carbohydrate, protein and lipid metabolic pathways converge in the Kreb’s cycle (Fig 2.7).
Pyruvate, the metabolic end product of glycolysis, has one of the alternate fates based on
the energy needed by the cells – enter into Kreb’s cycle for energy production (Fig 2.7 c)
or convert into lactate, an over flow metabolite. Under conditions of glucose starvation,
cells metabolise lactate back to pyruvate and meet their energy demands. Glutamine acts
as both a C- and N-source to the cells (Fig 2.7 a). Glutaminolysis results in the formation
of glutamate and ammonium (Fig 2.7 b). Glutamate is further broken down to
α-keto glutarate which is a Kreb’s cycle intermediate (Fig 2.7b).

16
CHAPTER 3
MATERIALS & METHODOLOGY
3.1 REAGENTS AND SOURCES
MATERIAL SOURCE
FINE CHEMICALS
Glutamine
Glucose
Sodium Hydroxide
Sodium Bicarbonate
Dimethyl sulfoxide (DMSO)
Sigma Aldrich, USA
CELLS & MEDIA
FreeStyle™ CHO-S cells (naked cell line) Thermo Fisher Scientific, USA
ActiCHO-P
ActiCHO Feed-A
ActiCHO Feed-B
GE Healthcare, USA
REAGENTS FOR SAMPLE ANALYSIS
Cedex™ HiRes Reagent kit
• Trypan Blue Stain
• Cedex Detergent
• Cleaning Solution
Roche Holding AG, Switzerland
Cedex Bio Reagent Kit and Calibrators
• NH3 Bio
• Glutamine V2 Bio
• Glutamate V2 Bio
• Lactate Bio
• Glucose Bio
• Calibrator A Bio
• Calibrator B Bio
ABL80 FLEX blood gas analyser
• Solution pack
• Sensor cassette
Radiometer, Denmark
Table 3.1: List of reagents utilized and their source

17
3.2 CELL CULTURE MEDIA AND SOLUTIONS
ActiCHO-P
ActiCHO-P Powder Base CD 22.36 g/L
Sodium Bicarbonate 1.8 g/L
Adjust pH to 6.90 – 7.55 using NaOH
Osmolality range should be 285 – 315 mOsm/kg
Filter sterilize
ActiCHO Feed-A
ActiCHO Feed-A Powder Base CD 181.04 g/L
Osmolality range at 5x dilution should be 247 – 303 mOsm/kg
Filter sterilize
ActiCHO Feed-B
ActiCHO Feed-B Powder Base CD 94.6 g/L
Osmolality range at 5x dilution should be 218 – 266 mOsm/kg
Filter sterilize
200 mM Glutamine
Glutamine 200 Mm
Filter sterilize
250 g/L Glucose
Glucose 250 g/L
Filter sterilize or Autoclave at 121 °C for 15 min
400 g/L Glucose
Glucose 400 g/L
7.5% Sodium bicarbonate
Sodium bicarbonate 7.5 % (w/v)
0.5M Sodium hydroxide
Sodium hydroxide 0.5 M
Filter sterilize
Freezing media ActiCHO-P media containing 7.5 % DMSO
Table 3.2: Composition of Cell culture media and solutions

18
3.3 STORAGE OF CELLS
CHO-S cells staged at mid-log was harvested by centrifuging them at 2000 rpm for 2 min
at room temperature. The supernatant was discarded, and the cell pellet was resuspended in
freezing media and aliquoted such that when revived in 25 – 50 mL of fresh media, the
concentration of viable cells will yield 0.25 - 0.3 106
/mL. The cells were initially stored at
-80 °C for at least 24 h before transferring them into liquid Nitrogen.
3.4 REVIVAL AND MAINTENANCE OF CELLS
CHO-S cells stored in liquid Nitrogen were revived by quickly thawing them at 37 °C and
resuspending them in approximately 8 – 10 mL of fresh media. The cells were then
separated from the freezing medium containing DMSO by spinning them at 2000 rpm for
1 min at room temperature. The cell pellet was then resuspended in 25 – 50 mL of fresh
medium in a shake flask such that it yields 0.25 – 0.3 106
/mL.
CHO-S cells were maintained in ActiCHO-P media supplemented with 6 mM Glutamine.
The cells were maintained in a 7.5% CO2 incubator with an orbital diameter of 19.05 mm
at 150 rpm and 37 °C. Cells were passaged every 3 – 4 days when the cell density has
reached 10-15 106
/mL, by dilution into fresh media.
3.5 CULTURE OF CELLS IN ReadyToProcess WAVE 25
CHO-S cells were grown in ActiCHO-P medium in shaker flasks to a cell density of 6-8
106
/ml. One day prior to inoculation ReadyToProcess WAVE 25 were setup with the
appropriate disposable single use bioreactor bag (as indicated in Table 3.3). The bioreactor
bag was inflated, and ActiCHO-P medium was transferred into the bag. The medium was
equilibrated to 37 °C and pH 7 overnight. On Day 0 of the culture, cells were transferred
by gravity flow into the bioreactor bag. The operation parameters and control strategies
employed for culturing the cells in Fed batch and perfusion modes are as per Tables 3.3
and 3.4 respectively.

19
Parameter FED BATCH
Bioreactor ReadyToProcess WAVE 25
Run ID FB08 FB09 FB10 FB13
Target
volume of
culture (L)
5 5 5 5
Disposable
bioreactor
bag used
Cellbag-10 L Cellbag-10 L Cellbag-10 L Cellbag-10 L
Medium
volume at
inoculation
(L)
3.7 L 3.7 L 2.7 L 2.7 L
Cell
concentration
at inoculation
(E6/ml)
0.220 0.229 0.241 0.500
Agitation
(rpm)
Rocking/Angle:
22-25/ 7
Rocking/Angle:
22-25/ 7
Rocking/Angle:
12-25/ 8
Rocking/Angle:
20-22/ 8
Aeration
(L/min)
0.2-0.8 0.2-0.8 0.2-0.8 0.25
Temperature
[°C]
37 37 21 - 37 37
pH setpoint 7.0 7.0 7.0 7.0
pH control
strategy
CO2/Base CO2/Base CO2/Base CO2/Base
DO setpoint
[%]
40 40 40 40
DO control
strategy
O2/Rocking O2/Rocking O2/Rocking O2/Rocking
Culture
Media
ActiCHO-P
with 6mM Gln
ActiCHO-P
with 6mM Gln
ActiCHO-P
with 6mM Gln
ActiCHO-P
with 6mM Gln
Feed
Strategy
2% Feed-A
0.2% Feed-B
2% Feed-A
0.2% Feed-B
4% Feed-A
0.4% Feed-B
2% Feed-A
0.2% Feed-B
Supplements
400 g/L Glc
200 mM Gln
400 g/L Glc
200 mM Gln
400 g/L Glc
200 mM Gln
NA
Table 3.3: Process design for fed-batch on WAVETM 25 bioreactor

20
Parameter PERFUSION
Bioreactor ReadyToProcess WAVE 25
Run ID PERF03 PERF04
Target volume
of culture (L)
1 1
Disposable
bioreactor bag
used
Cellbag- 2L with
internal floating
filter
Cellbag- 2L with
internal floating
filter
Medium volume
at inoculation
(L)
0.9L 0.9L
Cell
concentration at
inoculation
(E6/ml)
0.264 0.360
Agitation (rpm)
Rocking/Angle:
12/ 8
Rocking/Angle: 22-
25/ 8
Aeration
(L/min)
0.3-0.5 0.5
Temperature
[°C]
37 37
pH setpoint 7.0 7.0
pH control
strategy
CO2 CO2
DO setpoint [%] 40 40
DO control
strategy
O2/Rocking O2/Rocking
Culture Media
ActiCHO-P with
6mM Gln
ActiCHO-P with
6mM Gln
Feed Strategy
ActiCHO-P with
6mM Gln
ActiCHO-P with
6mM Gln
Supplements NA NA
Table 3.4: Process design for perfusion operations on WAVETM 25 bioreactor

21
3.5.1 FED-BATCH MODE OF CULTURING
Cells were maintained in batch mode until day 2 of the culture. From Day 3 and onwards,
ActiCHO Feed-A and ActiCHO Feed-B were added to the reactor gravimetrically.
Glucose and glutamine were maintained at 6 g/L and 6 mM respectively in the medium by
externally supplementing with glucose and glutamine stock solution, from day 6 and
onwards (Table 3.3). Cell count and viability, osmolality, metabolite profile and gas
profile were monitored by sampling the culture approximately daily before and after
feeding using the instruments mentioned in Table 3.5. The cells were maintained in culture
until the viability of the cells dropped to below 85%, after which the batch was harvested.
3.5.2 PERFUSION MODE OF CULTURING
Cells were maintained in batch mode until day 3 of the culture. Perfusion was initiated 72
hours post-inoculation for a period of 10-15 days (Table 3.4). ActiCHO-P media
supplemented with 6mM Glutamine was perfused at a linear (PERF03) and non-linear
(PERF04) perfusion rate between 0.30L/day to 5L/day. Cell count, viability, osmolality,
metabolite profile and gas profile were monitored by sampling the culture approximately
every 24 hours using the instruments mentioned in Table 3.5. The perfusion was carried
out until the cell viability was dropped to <85%.
PARAMETER ASSESSED INSTRUMENT
Viable cell count
Total cell count
Viability
Roche Cedex HiRes
Glutamine concentration
Glucose concentration
Glutamate concentration
Ammonia concentration
Lactate concentration
Roche Cedex Bio
Na+
K+
pCO2
pO2
ABL80 FLEX blood gas analyzer
pH measurement Mettler Toledo pH meter
Osmolality Advanced™ Model 3250
Table 3.5: Instruments used in the assessing the cell culture sample

22
3.6 COMPUTATION OF CELL GROWTH KINETICS AND METABOLIC
PROFILES
The profiling of the CHO-S cells’ growth characteristics along with the supplemented and
generated metabolites is carried out by utilizing both the online and offline data, that is
plotted with the help of a Visual Basic Application (VBA) script, that skims through the
excel data sheets and acquires relevant data points, processes the values to compatible and
comparable units. This array of data is then used to generate consumption and generation
profiles.
3.6.1 SPECIFIC GROWTH RATE
Specific growth rate is calculated by equation (2), where µ is the specific growth rate at
time t, x0 and x are the viable cell densities that is measured offline at time t0 = 0 hrs and at
time, t, respectively.
3.6.2 SPECIFIC CONSUMPTION-GENERATION PROFILES
The rate of metabolite consumption from within the media has been observed to be
directly proportional to the rate of cell growth, given by equation (3), where x is cell
density at time t, dx is the difference between cell densities at t and t-1, Y is the yield, and
µ is the specific growth rate. Integration of -ds/xdt from range t=0 to t gives the
consumption profile and +ds/xdt from range t=0 to t gives generation profiles, derived
from equation (4).
------- (1)
------- (2)
-----(3)
----(4)
----(5)

23
CHAPTER 4
RESULTS
4.1. METABOLITE TRENDS IN FED-BATCH PROCESSES
Towards understanding the metabolite consumption and generation trends in fed-batch
mode of culturing, four CHO-S cultures– FB08, FB09, FB10 and FB13 – with a final
volume of 5 L each, were conducted in ReadyToProcess WAVE 25 as mentioned in Table
3.3. Cell counts, viability, metabolite and gas profiles were measured daily before and after
feeding the reactor (Fig 4.1 a-d).
FB08 and FB09 were designed as positive control runs wherein Acti-CHO Feed A and
Feed B were added at 2% (v/v) and 0.2% (v/v) respectively from Day 3 and onwards.
Also, Glucose and Glutamine were supplemented as stock solutions to maintain 6 g/L and
6 mM respectively from Day 6 and onwards. Towards quantifying the metabolic stress
induced by temperature stress heating control was turned off for approximately 48h in
FB10 (Fig 4.1 e, grey line) while keeping all other parameters similar to FB08 and FB09.
Furthermore, in FB13 the effects of supplementing Glucose and Glutamine was observed
by not adding these stock solutions while increasing the feed rate of Feed A and Feed B to
2% (v/v) and 0.2% (v/v), respectively. It is important to note that Feed A has a high
concentration of Glucose (approximately 70 g/L). Metabolite consumption and generation
profiles were calculated after estimating their amounts that have been introduced through
the feeds in the post-feed sample (observed as a peak) and their gradual consumption over
the next 22-24 hours (pre-feed sample). Specific growth rates, pH and gas profiles were
also compared between these cultures.
Analysis of the cell growth profiles of FB08, FB09, FB10 and FB13 (Fig 4.2 a) has
indicated that both FB10 and FB13 have suffered significantly with respect to FB08 and
FB09. While FB10 compromised on achieving peak VCC; FB13 was impaired on
longevity of the run. FB08 and FB09 have recorded peak VCC of 22.2 MVC/mL 20.83
MVC/mL respectively over the 16 days long culture time each. FB10 recorded a peak
VCC of 14.58 MVC/mL over a 14 days long culture time. While the peak VCC of FB13 is
comparable to FB08 and FB09 (16.6% lower) the culture longevity has significantly

24
Fig 4.1: Metabolite Profiles of Fed Batch cultures FB08, FB09, FB10 and FB13
VCC and metabolite trends of FB08 (a) and FB09 (b) are characteristic fed-batch runs owing to the regular
feeding, supplementation of glucose and glutamine as needed and the maintenance of strict process
parameters. Owing to drop in temperature, an important process parameter, the VCC (dark blue line) of
FB10 (c) is significantly lower than FB08 and FB09. Correspondingly, the metabolite patterns show an
under-utilization of glucose (orange line) and delayed Warburg shift (light blue line) compared to FB08 and
FB09. The longevity of FB13 has been pronouncedly decreased as indicated by the abrupt fall of VCC (dark
blue line). The reason for this sudden drop could be the lack of glucose (orange line) or lactate (light blue
line) available to the culture.
Culture time (days) Culture time (days)
Culture time (days)

25
reduced by 6 days which could be a result of the exiguity of glucose and glutamine
supplementation.
Furthermore, the specific growth rates of these various fed-batch cultures (Fig 4.2 b) shed
more insights into the observed growth profiles. FB08 and FB09 recorded a higher specific
growth rate (µ) from day 2 to day 5 which correspond to the log phase of the growth curve.
This is followed by a steady drop till the end of the culture.
Fig 4.2: Cell growth (a) and cell specific growth rate (b) profiles of FB08, FB09, FB10
and FB13
FB08 (dark blue line) and FB09 (orange line) exhibit VCC, viability (a) and cell specific growth rate (µ) (b)
profiles characteristic of fed-batch cultures. FB10 (grey line) reported significantly lower VCC (a) and cell
specific growth rate (days 3-5) (b) due to drop in temperature on days 3-4. The significantly lower cell
specific growth rate (b) of FB13 (yellow) from Day 1 to 6 indicate anomalous behaviour that is unexplained
by the lack of supplementation of glucose and glutamine. Corresponding to this, the VCC and longevity (a)
of FB13 are also lower than the controls (FB08 and FB09).
Culture time (days)
Culture time (days)

26
The temperature stress endured by FB10 seems to have reduced the attainable culture
viability, as the µ decreased significantly between days 3-4, the log phase of the culture.
Correspondingly, it can be observed in the cell growth profile that the culture could not
achieve a peak VCC similar to FB08 and FB09. The specific growth rate of FB10 is
comparable to FB08 and FB09 from days 6 to 14, indicating that following the temperature
correction the culture characteristics are similar to the control runs.
It is interesting to note that the prolonged lag phase in FB13, which could have resulted in
the premature termination of the culture. FB13 has consistently exhibited lower µ
throughout from Day 1 to Day 6, despite a higher feeding rate, indicating that the
premature termination of the culture could not be due to lack of supplementation. Further
investigation into the gases, pH and metabolite profiles is warranted to identify the root
cause for this anomalous behaviour.
The pH of FB13 (Fig 4.3 a) on Day 0 was observed to be 7.7 which is significantly higher
compared to the rest of the cultures. This higher pH could be the potential reason for the
lower µ of this culture. The pH is restored to normal range (7.15±0.15) on Day 2 of culture
which corresponded to the steep increase in µ from Day 2 to Day 3 of culture.
Nevertheless, the stress induced by this high pH (7.9) on the cells were irreversible as seen
by the outcome of this culture.
Corresponding to the lower growth of these cells, the pO2 levels in media for FB13 (Fig
4.3 c) is higher than the other cultures, thus indicating a slower metabolism. It is also
interesting to observe the increase in pCO2 (Fig 4.3 b) and pO2 (Fig 4.3 b) levels of FB10
on Day 3, the mid-point reading when the heating was turned off. This points out to the
lower metabolic rate and thus, the decreased cell counts that were observed in FB10.
Glucose, lactate, glutamine, glutamate and ammonium levels were measured in the media
by sampling the culture daily before and after feeding the cultures so as to account for the
amount of metabolites that have been added through the feeds and supplements. The
difference in metabolite levels from post-feeding to before-feeding the next day was used
to calculate the metabolite consumption and generation profiles. Being representatives of
standard fed-batch cultures, FB08 and FB09 were considered as ‘normal’ and ‘standard’
profiles for all metabolites. The deviations in FB10 and FB13 were analysed with respect
to these cultures.

27
Glucose and lactate metabolism (Fig 4.4) of FB10 indicate a slower metabolism than FB08
and FB09 as expected due to the lack of heating and temperature drop in this culture.
Lactate has accumulated significantly higher than the control cultures, indicating it to be a
response to stress experienced by the cells. Warburg effect is also observed later (Day 8) in
FB10 than the control runs (Day 5). This is further supported by the glutamine, glutamate
and ammonium (Fig 4.5) consumption and generation profiles. The relatively lower VCC
of FB10 is further reflected in the lower consumption and generation profiles of all the
metabolites analysed. FB13, on the other hand, exhibited a faster and aggressive
metabolism than the control runs. Glucose is consumed faster than the control runs (Fig
4.4 a & b) and due to non-replenishment in the form of glucose stock, glucose levels
depleted to near-zero values. This has concomitantly triggered lactate consumption (Fig
4.4 c & d) similar to the control runs by Day 5 and has reached a near zero value for lactate
too.
Fig 4.3 pH and dissolved gases profile
of FB08, FB09, FB10 and FB11
The increase in pCO2 (b) and pO2 (c) levels in
FB10 (grey line) and the significantly higher pH
(a) and elevated pO2 (c) levels in FB13 (yellow
line) indicate reduced metabolism in these cultures
than FB08 (blue line) and FB09 (orange line)
Culture time (days)
Culture time (days)
Culture time (days)

28
Nevertheless, the complete consumption of both glucose and lactate and non-
replenishment of glucose has resulted in early termination of the culture. Despite the
presence of glutamine (Fig 4.5 a), an alternate C-source, the culture could not survive.
FB10 and FB13 throw interesting insights into the metabolic stress experienced by the
cells under varied conditions. While FB10 displayed an under-utilization of nutrients due
to temperature induced stress, FB13 exhibited an aggressive utilization of nutrients to
counter pH-induced stress. However, neither cultures achieved the optimum cell counts.
Fig 4.4 Glucose and lactate profiles of FB08, FB09, FB10 and FB11
Glucose levels (a) and glucose consumption (b) trends of FB08 (blue line) and FB09 (orange line) show a
very similar pattern. FB10 (grey line) exhibits a significantly lower glucose consumption and FB13 (yellow
line) an extremely fast glucose consumption until its complete depletion. Lactate metabolism (c & d) in
FB08 (blue line) and FB09 (orange line) exhibited very similar trends except on Day 10. Both FB08 and
FB09 shifted to lactate consumption around Day 5 of culture. FB10 (grey line) did not consume lactate until
Day 8 of culture while FB13 (yellow line) consumed lactate around Day 5 similar to FB08 and FB09 despite
lower lactate concentration. Lactate consumption in FB13 is much faster than FB08 and FB09 due to
glucose reaching near zero.
Culture time (days)

29
Fig 4.5 Glutamine, glutamate and ammonium profiles of FB08, FB09, FB10 and FB13
Glutamine (a & b), glutamate (c & d) and ammonium (e & f) metabolism in FB08 (blue line) and FB09
(orange line) show a very similar patterns as expected of normal fed-batch cultures. Glutamine was not
effectively consumed in FB10 (grey line) due to lack of heating and decreased metabolism. In FB13 (yellow
line) glutamine synthesis can be observed from Days 7-10 as expected of a GS+ cell line. Glutamate is
generated (or under-utilized) (c & d) at a higher level in both FB10 and FB13. The levels of ammonium
generated (e & f) in both FB10 (grey line) and FB13 (yellow line) are less than those of FB08 and FB09.
Culture time (days)
Culture time (days)
Culture time (days)

30
4.2. METABOLITE TRENDS IN PERFUSION PROCESSES
To fathom the metabolite consumption and generation trends in a continuous process,
CHO-S cells were expanded in perfusion mode in ReadyToProcess WAVE 25, utilizing
Cellbag-2L integrated with an internal floating filter. Two cultures PERF03 and PERF04
were subjected to linearized and non-linear perfusion feed strategies respectively (Fig 4.6).
In PERF03 perfusion was initiated from Day 3 with a daily step increase in perfusion rate
until a maximum of 5 VVD. However, in PERF04, perfusion was initiated only from Day
5 of the culture, when the glucose level in the medium is below 2 g/L. The daily increment
in the perfusion rate was done gradually such that a maximum of 3 VVD was attained as
against the maximum of 5 VVD in PERF03. Cell counts, gas profile and metabolite levels
were estimated by sampling the reactors daily (Fig 4.7). It is interesting to note the similar
metabolite profiles in these two cultures regardless of the differences in their perfusion
strategies. The perfusion action has kept the overflow metabolites – lactate and ammonium
– at a low concentration in the culture medium as expected. Warburg effect, i.e., lactate
consumption, has been observed in both the cultures around Day 4 – 5 despite the
difference in their cell counts.
The cell growth profiles of PERF03 and PERF04 (Fig 4.8 a) indicated prolonged culture
viabilities and higher peak VCC values compared to fed batch cultures, as expected.
Despite following different perfusion strategies, PERF03 and PERF04 have attained
similar peak VCC - 63.84 MVC/mL and 78.13 MVC/mL, respectively. However, PERF03
Fig 4.6 Perfusion feed strategies of
PERF03 and PERF04
Linear feed strategy and demand-based non-
linear feed strategy were employed for
PERF03 (blue line) and PERF04 (orange line)
respectively
Culture time (days)

31
has attained peak VCC on Day 8 of culture which is much earlier than that of PERF04
(Day 11).
It had been interesting to observe that the cell count profile has been biphasic for both
PERF03 and PERF04 wherein the cell counts dropped and then raise owing to the removal
of cell debris due to perfusion. Correspondingly, even the cell viability trends have
exhibited a biphasic behaviour. This behaviour has led to the judgement to terminate of the
culture irrespective of high cell viability (>85%). The specific growth profiles of PERF03
and PERF04 (Fig 4.8 b) have displayed comparable characteristics. Owing to the non-
linear perfusion strategy of PERF04, its specific growth rate uneven during the later part of
the culture period compared to the even trend observed for PERF03.
pH, pO2 and pCO2 profiles indicate that pH and dissolved oxygen was well maintained in
the cultures to promote growth of cells (Fig 4.9). The glucose consumption (Fig 4.10 b) of
PERF03 appears to be slightly lower but uniform when compared to PERF04. This could
be due to the non-uniform availability of glucose in PERF04. This trend is also reflected in
the lactate generation (Fig 4.10 d) of PERF03 and PERF04.
Fig 4.7: Metabolite Profiles of Perfusion cultures PERF03 and PERF04
VCC and metabolite trends of PERF03 (a) and PER04 (b) indicate high and comparable VCC (dark blue
line) in both the cultures. Both the cultures exhibit similar metabolite profiles despite the dissimilar
perfusion strategies. Overflow metabolites – lactate (light blue line) and ammonium (green line) – are at a
lower concentration because of their timely removal by perfusion. Warburg effect – lactate consumption –
is observed at approximately the same time – Day 4-5 – despite the significant difference in the cell count
of the two cultures.

32
Fig 4.9 pH and gas profiles of PERF03
and PERF04
pH (a) in both PERF03 (blue line) and PERF04
(orange line) is well maintained by sequestrating
the required CO2 (b) for regulation. Dissolved
oxygen is maintained in both the cultures by the
influx of O2 (c).
Fig 4.8 Cell growth (a) and
cell specific growth rate (b)
profiles of PERF03 and
PERF04
The double peak VCC (a) exhibited
by PERF03 (blue line) corresponding
with the rise in it’s viability (a)
indicate that the cell debris is cleared
by the perfusion action and
prolonging the longevity of the cells.
The VCC of PERF04 (orange line)
displayed a steady rise to attain the
peak following a steady decline, while
maintaining the viability of the cells,
similar to PERF03. The specific
growth rate (µ) (b) of PERF03 (blue
line) and PERF04 (orange line) are
slightly different. PERF03 recorded a
steady rise and fall while PERF04
showed a steady rise and an uneven
drop owing to the non-linear feeding
strategy.
Culture time (days)
Culture time (days)
Culture time (days)

33
On the other hand, the consumption of glutamine (Fig 4.11 b) and ammonium (Fig 4.11 f)
are very similar between PERF03 and PERF04. However, glutamate generation rate (Fig
4.11 d) is slightly increased in PERF04 than PERF03 similar to glucose consumption and
lactate generation trends. The steady consumption and production of metabolites is as
expected in a steady state process.
Fig 4.10 Glucose and lactate trends for PERF03 and PERF04
Glucose (a) and lactate (c) trends of PERF03 (blue) and PERF04 (orange line) exhibit a similar pattern in the
initial days of the culture and becomes diverse due to the varied perfusion strategies. Glucose consumption (b)
and lactate generation (d) of PERF04 (orange line) is slightly higher than those of PERF03 (blue line).

34
Fig 4.11 Glutamine glutamate and ammonium trends for PERF03 and PERF04.
Gluamine (a) glutamate (c) and ammonium (e) concentration in the medium for PERF03 (blue line) and
PERF04 (orange line) show slight variation. However, glutamine consumption (b) and ammonium
generation (f) trends of PERF03 (blue line) and PERF04 (orange line) show that they are highly similar,
while glutamine generation (d) of PERF04 (orange line) is marginally higher than that of PERF03 (blue
line)

35
CHAPTER 5
DISCUSSION AND FUTURE SCOPE
5.1 DISCUSSION
The metabolite profiles of fed batch operations conducted on WAVE 25 were analyzed
under conditions of temperature stress and nutrient stress. The metabolite profiles of fed
batch cultures, FB08 and FB09 are considered as ‘standard’ profiles observed while
running the culture under standards and optimal process conditions. FB10 culture was
subjected to a temperature stress by disabling heating the culture, thus, lowering the
process parameter to 21 0
C on Day 3-4. The cells responded to this external stress by
lowering cell growth kinetics in comparison to FB08 and FB09 cultures. Consequently, the
peak VCC attained by FB10 is 34.3% lowering than that of FB08 and FB09. Analysis of
pO2 and pCO2 profiles indicated that O2 was under-consumed and pCO2 levels peaked,
leading to formation of carbonic acid and subsequent drop in pH on Day 4 of culture.
Consequently, a surge in lactate and ammonium levels was observed in FB10 compared to
FB08 and FB09. Hence, the levels of overflow metabolites elevated in response to
prolonged temperature induced stress.
The improper influx of CO2 into the media, in FB13, seemed to have elevated the culture
pH beyond optimal range, thus impacting the health of the culture at the beginning of the
experiment. pH imbalance seems to have shortened the longevity of the culture, as inferred
from the suppressed specific growth rate trend. Thus, the impact of nutrient limitation
induced stress could not be well studied as expected from this experiment. However, in
response to the pH stress the culture metabolized glucose and lactate at a faster rate to near
zero concentrations in the culture compared to FB08 and FB09. It is interesting to observe
the unpredictable Warburg effect observed in FB10 and FB13. FB10 showed late lactate
consumption due to temperature stress on Day 8 of culture, while FB13 has shown early
Warburg similar to FB08 and FB09 on Day 5. The cause for this difference in the onset of
Warburg effect needs to be further investigated.

36
Perfusion mode of cell culturing has shown promising results, as expected, by extending
culture viability, while maintaining an extended log phase by both the cultures PERF03
and PER04. It was presumed that the greater the perfusion rates the better the descry of the
metabolic performance of the culture, as discretion the perfusion strategy was designed
towards as linear (PERF03) and non-linear (PERF04) feeding.
On examining the cell growth trends, it can be seen that despite the differences in
perfusion feed strategy, both the cultures exhibited an extended log phase. PERF04, with
the non-liner perfusion rate, seems to have achieved a higher peak cell density in
comparison to PERF03, with the linear perfusion rate, despite a longer lag phase. This
statement could be supported by slight depression within the specific growth profile.
The metabolite trends of PERF03 indicate it to be a highly active culture, while PERF04
shows slightly less metabolic activity, probably due to the late onset of log phase. The
same can be argued for the pO2 profile, since PERF04 displayed a delayed O2 utilization
trend. The metabolic efficacy of cultures can further be supported by the Warburg effect,
PERF03 and PERF04 displayed lactate consumption at approximately the same time, Day
4-5. However, the pO2 levels in PERF03 and PERF04 are significantly different in these
cultures. While PERF03 proceeded towards rapid O2 depletion, PERF04 exhibited O2
accumulation.
It can be concluded from the above analysis that physical control parameters are crucial
parameters that need to be kept under optimal process conditions. They can affect the
metabolism directly which in turn, lowers the culture viability and volumetric productivity.
As presumed and confirmed a higher perfusion rate seems to promote a higher metabolic
activity of the culture and pertains to extend the longevity and productivity of the cells.
This also facilitates in concluding that linearity of perfusion doesn’t play the pivotal role in
higher metabolic activity, rather, the higher the perfusion be it linear or non-linear might
tend to provide satisfactory similar trends.

37
5.2 FUTURE SCOPE
Understanding the metabolic pathways in fed-batch and perfusion cultures under different
conditions of growth is needed for efficient design of media and feed supplements. The
work done herewith paves way for analysis of the different metabolic pathways and the
influence of overflow metabolites on CHO cells. Further research on parameter or process-
oriented cell cultures is warranted to improve the understanding for better process
productivity and development of model-based controls.

38
REFERENCES
1. Kristina M. Lybecker (2016) The Biologics Revolution in the Production of Drugs;
Fraser Institute. July 2016, p1-5, p34-36.
2. Prashansa Agrawal (2015) Biopharmaceuticals: An emerging trend in Drug
Development; SOJ Pharmacy & Pharmaceutical Sciences. February 2015.
3. M. Yang and M. Butler Mooney, V. (2000) Effects of Ammonia on CHO Cell
Growth, Erythropoietin Production, and Glycosylation; Biotechnology &
Bioengineering; Vol. 68 Issue: 4 p370-380, 11p
4. Jee Yon Kim, Yeon-Gu Kim and Gyun Min Lee. (2011) CHO cells in
biotechnology for production of recombinant proteins: current state and further
potential; Applied Microbiology & Biotechnology, Vol. 93 Issue 3, p917-930. 14p
5. Christian Larroche, M. Sanroman, Guocheng Du and Ashok Pandey. (2016)
Current Developments in Biotechnology and Bioengineering 1st Edition, ©
Elsevier 2017.
6. Kathleen A. Estes and Eric Langer (2017). Update on Continuous Bioprocessing:
From the Industry’s Perception to Reality, Pharmaceutical Technology, Volume 41,
Issue 6, pg 70–72
7. Eric S. Langer and Ronald A. Rader. (2014) Continuous Bioprocessing and
Perfusion: Wider Adoption Coming as Bioprocessing Matures BioProcessing Journal,
Vol. 13 Issue 1, p43-49.
8. R. Po¨rtner. (2015) Bioreactors for Mammalian Cells, Animal Cell Culture, ©
Springer International Publishing Switzerland, Cell Engineering 9, DOI 10.1007/978-
3-319-10320-4_4
9. Konakovsky, V., Clemens, C., Müller, M. M., Bechmann, J., Berger, M.,
Schlatter, S., & Herwig, C. (2016). Metabolic Control in Mammalian Fed-Batch Cell
Cultures for Reduced Lactic Acid Accumulation and Improved Process Robustness.
Bioengineering (Basel, Switzerland), 3(1), 5.
10. Asenjo, J. and Merchuk, J. (2010). Bioreactor system design. Boca Raton: CRC
Press/Taylor & Francis Group.
11. Bruce Lehr and Delia Lyons. (2016) Perfusion in the 21st Century; Biopharm
International. August 2016, Vol. 29 Issue 8, p24.

39
ANNEXURES
Table 4.1: Fed-batch (FB08) with 2% of Feed-A and 0.2 % of Feed-B feeding

40
Table 4.2: Fed-batch (FB09) with 2% of Feed-A and 0.2 % of Feed-B feeding

41
Table 4.3: Fed-batch (FB10) with 4% of Feed-A and 0.4% of Feed-B feeding

42
Table 4.4: Fed-batch (FB13) with 2% of Feed-A and 0.2% of Feed-B feeding

43
Table 4.5: Perfusion (PERF03) with linearized perfusion rate till Day 14

44
Table 4.6: Perfusion (PERF04) with non-linear perfusion rate till Day 13

45
Table 4.7: Specific Growth rate in Fed Batch culture (FB08) in Cellbag-5L
X0= 0.23 E6 cells/mL Exp: FB08
X
X/X0 ln (X/X0) t (hrs) µ= ln(x/x0)/t
(E6 cells/mL)
0.23 1.00 0.00 0
0.42 1.84 0.61 24 0.025
1.30 5.66 1.73 48 0.036
3.93 17.17 2.84 72 0.039
9.62 41.99 3.74 96 0.039
16.00 69.88 4.25 120 0.035
20.41 89.13 4.49 144 0.031
22.20 96.96 4.57 168 0.027
21.39 93.39 4.54 192 0.024
20.04 87.50 4.47 216 0.021
16.59 72.42 4.28 240 0.018
16.52 72.12 4.28 264 0.016
15.52 67.79 4.22 288 0.015
13.75 60.06 4.10 312 0.013
11.69 51.04 3.93 336 0.012
10.23 44.65 3.80 360 0.011
9.22 40.28 3.70 384 0.010
average µ
0.023
(per hr)=

46
X
(E6 cells/mL)
0.22 1.00 0.00 0
0.45 2.02 0.030 24 0.030
1.30 5.90 0.037 48 0.037
4.06 18.44 0.040 72 0.040
9.40 42.72 0.039 96 0.039
16.41 74.59 0.036 120 0.036
19.50 88.64 0.031 144 0.031
20.56 93.45 0.027 168 0.027
20.83 94.68 0.024 192 0.024
19.80 90.00 0.021 216 0.021
16.37 74.42 0.018 240 0.018
16.25 73.86 0.016 264 0.016
14.76 67.07 0.015 288 0.015
14.13 64.25 0.013 312 0.013
12.45 56.60 0.012 336 0.012
10.33 46.94 0.011 360 0.011
8.58 39.01 0.010 384 0.010
average µ
0.024
(per hr)=

47
X
(E6 cells/mL)
0.24 1.00 0.00 0
0.48 2.00 0.69 24 0.029
1.21 5.03 1.62 48 0.034
3.40 14.11 2.65 72 0.037
3.59 14.88 2.70 96 0.028
5.87 24.35 3.19 120 0.027
11.12 46.11 3.83 144 0.027
14.08 58.37 4.07 168 0.024
14.58 60.43 4.10 192 0.021
13.67 56.65 4.04 216 0.019
13.07 54.18 3.99 240 0.017
12.18 50.48 3.92 264 0.015
11.33 46.96 3.85 288 0.013
10.83 44.89 3.80 312 0.012
9.23 38.28 3.64 336 0.011
average µ
0.022
(per hr)=

48
X X/X0 ln (X/X0) t (hrs) µ= ln(x/x0)/t
(E6 cells/mL)
0.496 1.000 0.000 0
0.530 1.069 0.067 15 0.004
0.700 1.411 0.344 39 0.009
1.898 3.826 1.342 63 0.021
1.930 3.892 1.359 86 0.016
4.711 9.500 2.251 87 0.026
4.771 9.620 2.264 110 0.020
8.717 17.577 2.867 111 0.026
9.230 18.612 2.924 134 0.022
10.539 21.251 3.056 134 0.023
12.732 25.674 3.245 158 0.021
16.643 33.559 3.513 158 0.022
16.495 33.262 3.504 183 0.019
17.556 35.401 3.567 183 0.019
18.179 36.656 3.602 207 0.017
18.098 36.494 3.597 207 0.017
18.529 37.362 3.621 209 0.017
average µ 0.019

49
Table 4.11: Specific Growth rate in Perfusion culture (PERF03) in Cellbag-2L
X0= 0.264 E6 cells/mL Exp: PERF03
X X/X0 ln (X/X0) t (hrs) µ= ln(x/x0)/t
(E6 cells/mL)
0.264 1.000 0.000 0
0.766 2.900 1.065 22 0.048
2.377 9.003 2.198 47 0.047
6.250 23.676 3.164 70 0.045
12.956 49.076 3.893 94 0.041
24.331 92.165 4.524 118 0.038
37.999 143.936 4.969 142 0.035
50.140 189.924 5.247 166 0.032
64.102 242.811 5.492 191 0.029
39.830 150.870 5.016 215 0.023
44.037 166.806 5.117 239 0.021
63.843 241.828 5.488 263 0.021
47.279 179.087 5.188 287 0.018
45.961 174.096 5.160 311 0.017
45.173 171.109 5.142 335 0.015
43.943 166.452 5.115 359 0.014
48.820 184.923 5.220 382 0.014
average µ 0.029

50
Table 4.12: Specific Growth rate in Perfusion culture (PERF04) in Cellbag-2L
X0= 0.365 E6 cells/mL Exp: PERF04
X X/X0 ln (X/X0) t (hrs)
µ=
ln(x/x0)/t
(E6 cells/mL)
0.365 1.000 0.000 0
0.615 1.686 0.522 17 0.031
2.173 5.957 1.785 40 0.045
4.882 13.387 2.594 65 0.040
9.314 25.539 3.240 88 0.037
10.559 28.953 3.366 113 0.030
12.035 33.001 3.497 137 0.026
21.849 59.912 4.093 161 0.025
28.542 78.265 4.360 185 0.024
39.921 109.468 4.696 209 0.022
41.614 114.111 4.737 233 0.020
76.798 210.590 5.350 257 0.021
67.806 185.932 5.225 281 0.019
50.557 138.634 4.932 305 0.016
average
µ
0.027

51
PROJECT DETAILS
Student Details
Student Name Joel John
Register Number 150924092 Section / Roll No 39
Email Address joelcmd@gmail.com Phone No (M) +91-8593826814
Project Details
Project Title Metabolite Consumption and Production Patterns In Fed Batch
And Perfusion Cell Cultures
Project Duration 21 weeks Date of reporting 28-01-2019
Organization Details
Organization
Name
Wipro GE Healthcare Life Sciences
Full postal address
with pin code
JFWTC, Plot #122, Export Promotion Industrial Park,
Phase 2, Hoodi Village, Whitefield,
Bengaluru-560066, Karnataka
Website address www.gelifesciences.com
Supervisor Details
Supervisor Name Dr. Neelima Boddapati
Designation Lead Research Scientist
Full contact address
with pin code
JFWTC, Plot #122, Export Promotion Industrial Park,
Phase 2, Hoodi Village, Whitefield,
Bengaluru-560066, Karnataka
Email address neelima.boddapati@ge.com Phone No (M) +91-8040887369
Internal Guide Details
Faculty Name Dr. Ramachandra Murty V
Full contact address
with pin code
Dept of Biotechnology, Manipal Institute of Technology, Manipal –
576 104 (Karnataka State), INDIA
Email address murty.vytla@manipal.edu

Undergraduate Thesis - Joel John

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