S. 1 © HiTec Zang GmbH - HRE Respiration Activity Monitoring System Bioprocessoptimisation

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RRespirationespiration AActivityctivity MoMonitoringnitoring SSystemystem

Bioprocessoptimisation

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Online – respiration

activity measurement

(OTR, CTR, RQ)

in shaking flasks

RRespirationespiration AActivityctivity MoMonitoringnitoring SSystemystem

The RAMOS® System

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The Tray

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Fields of Application

Online-tracing of the metabolic activityof pro- and eukaryotic cultures in shaking flasks

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Easy Determination of parameters:

- oxygen transfer rate (OTR)

- carbon dioxide transfer rate (CTR)

- respiration quotient (RQ)

- maximum growth rate (µmax)

- volumetric oxygen transfer coefficient (kLa)

…,

which afford a safe Scale-Up.

Possibilities

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Unlimited growth on minimal media Oxygen limitation

Product inhibition( e.g. pH) Diauxic growth

Time of fermentation

Oxy

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Time of fermentation

Oxy

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Time of fermentation

Oxy

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Time of fermentation

Oxy

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maximum oxygen transfer

capacity

Total oxygenconsumption [mol/l]

=

Substrate limitation(except C-source)

Time of fermentation

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Possibilities

Detection of characteristic biological phenomena (OTR)

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Possibilities

Detection of characteristicbiological phenomenaCTR development:

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Recognition of suitable conditions for conventional

mass screening

(operation duration, culture media, operation conditions …)

Optimisation of substrate concentrations and

reduction of media development time

Fermentation balancing (cytotoxycity- and

proliferation assays)

Growth control under sterile conditions

Targeted sampling depending on oxygen transfer rate

Quality control

Possibilities

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?

online-exhaustgas analytik

stirredbioreactor

OTRCTRRQ

online

shakingbioreactor

State of the Art

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Motivation

„The disadvantage of the shake flask as an experimental system is that the

experimenter has only limited capabilities for on-line

monitoring and control.“Payne et al., 1990

„Weakness of small-scale liquid fermentations:

discontinuous monitoring“Hilton, 1999

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What kind of Online Signal?

carbon source(glutamine, glucose, ...)

nitrogen source(ammonia sulfate, urea,

yeast extract, peptone, ...)

phosphorus source(phosphate, phytin)

sulfate source(sulfate, cysteine, ...)

trace elements, vitamins

Carbon dioxide

Oxygen

product(proteins, alcohol amino acids, ...)

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Unknown Fermentation Process

Time

culture process

end of experiment

A

B

normal shaking flask:

?

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B

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Time

culture process

end of experiment

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Known Fermentation Process

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measures online the

respiration activities (OTR, CTR, RQ)

of aerobic biological systems

in shaking flasks under

sterile conditions

Solution

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more information about microbiological processesin shaking flasks

rapid characterisation and targeted optimisation of media

replaces expensive experiments in the fermenter

creates optimal repoducabilty options

virtual non-stop operation by very short set-up time

reduction of experimental time to the actually required time

distinction of process-related and biological effects

casily handling

Distinct Advantages

parallel technology (time, comparability ...)

visualising the perfect inoculation point

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Graduated flask

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Sample Fermentations

Mammalian cell culture Hybridoma (50 ml liquid volume)

Determination of the optimal inoculation- and fed-batch starting time

Time of Fermentation [h]

OTR

/CTR

[m

ol/

(L·h

)]

Cell d

en

sit

y [

N/m

L]

0 50 100 150 200

OTRCTRcell density

glutamine- andglucose consumption

glucose consumption

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Media optimisationExample: optimum of osmolarity

0

0,005

0,01

0,015

0,02

0,025

0,03

0,22 0,24 0,26 0,28 0,3 0,32 0,34 0,36 0,38

Gro

wth

rate

µ [

h-1]

Osmolarity [osmol/kg]

optimum of osmolarityat 0,318 osmol/kg

Mammalian cell culture Hybridoma (50 ml liquid volume)

Sample Fermentations

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Mammalian cell culture Hybridoma

Comparison of RAMOS to a stirred reactor with online exhaust gas analytics

OTR

[m

ol/

(L·h

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0 20 40 60 80

stirred tank reactor (2 litre culture volume)

RAMOS (0,05 litre culture volume)

Dipl.-Ing. M. Canzoneri

Sample Fermentations

Time of Fermentation [h]

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Bacterium Corynebacterium glutamicum

Effect of different liquid volumes

Sample Fermentations

OTR

[m

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Time of Fermentation [h]

Flask 1 : 10 mL

Flask 2 : 15 mL

Flask 3 : 20 mL

Flask 4 : 30 mL

Flask 5 : 40 mL

Flask 6 : 50 mL

oxygen limitation

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Effect of different substrate concentrations

Bacterium Pseudomonas fluorescens

Sample Fermentations

OTR

[m

ol/

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fermentation time [h]

1x concentrated2x concentrated4x concentrated

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Media- and process optimisation

OTR

[m

ol/

(L·h

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Time of Fermentation [h]

Media with 100% comp. 1,30 ml liquid

Media with 200% comp. 1,30 ml liquid

Media with 200% comp. 1,20 ml liquid

Yeast Hansenula polymorpha

Sample Fermentations

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Mammalian cell cultures Hybridoma

Cell-growth within aRAMOS experiment

Dipl.-Ing. M. Canzoneri

Sample Fermentations

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Mammalian cell culture Hybridoma

Time of Fermentation [h]

Cell d

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y [

N/m

l]

0 40 80 120 160

8-time parallel measurement

Dipl.-Ing. M. Canzoneri

Cell proliferation within a RAMOS experiment

Sample Fermentations

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Easy Handling

little required space –

RAMOS fits to normal bench top

easy and fast-learnable appliance

fully automated user software

virtual non-stop operation by very short set-up time

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Operating Interface

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Flask Overview

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Oxygen Transfer Rate (OTR)

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Detail View for each Flask(OTR, CTR, RQ)

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O2-, CO2 - Transfer

Oxygen transfer (OT) Carbon dioxide transfer (CT)

Balancing of the total

oxygen transfer during the fermentation process

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growth rate µ

maximum Growth Rate µ

maximum growth rate µ

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OTR CTR

Shedding light on your processShedding light on your process

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Economic efficiency consideration

The variation of the media concentration led to an

reduction of the time of fermentation of ca. 37 %

Time of amortisation: ca. 6 months

OTR

[m

ol/

(L·h

)]

Time of Fermentation [h]

Media with 100% comp. 1,30 ml liquid

Media with 200% comp. 1,30 ml liquid

Media with 200% comp. 1,20 ml liquid

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Cell culture (Hybridoma)

• Dosing

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FTT® Fluid-Train System

• Dosing and automated samplin

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FTT® Fluid-Train System

• controlled loop dosing

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● determination of RQ by OUR, CER online measurement● exact feeding of cultures● significant increase in production rates ● shortening of the fermentation periods

RQFeed™ - Feeding algorithm

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● reproducable biomechanical measurement● personalised drug and toxin research● alternative to animal experiments● integrated, fully automated and heat sterilisable pipetting unit● 24 - 96 Multiwell units with integrated sensorics

CellDrum™ - Cell force measurement

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● 1 to 8(5) Measurement Channels for 1 to 4 Fermenters ● High Resolution Measurement● Humidity Compensation (-c Version)● "True" OUR, CER and RQ Measurements (-c Version)● Low Interference ● Possible Overpressure ● Wear-resistant Sensor System ● Compact Design● Additional Functions can be integrated● Optionally free Programmability● Numerous Coupling Options● Data Export is possible

HiSense™ - Precision Gas Analysis

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Cell culture (Hybridoma)

• Without dosing

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Cell culture (Hybridoma)

• Dosing according to OTR controlled loop starting at RQ<1

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Cell culture (Hybridoma)

• Dosing program

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Cell culture (Hybridoma)

• Parameterisation of taking samples

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Cooperations and Publications

Cooperations:

Publications:Anderlei T., Büchs J., Device for sterile online measurement of the oxygen transferrate in shaking flasks, Biochem. Eng. J. 7(2), 157-162, 2001

Stöckmann Ch., Maier U., Anderlei T., Knocke Ch., Gellissen G., Büchs J.,The Oxygen Transfer Rate as Key Parameter for the Characterisation of Hansenula polymorphaScreening Cultures, J. Ind. Microbiol. Biotechnol. 30, 613-622, 2003 Anderlei T., Zang W., Büchs J., Online respiration activity measurement (OTR, CTR, RQ)in shake flasks, Biochem. Eng. J. 17(3), 187-194, 2004 Lotter St., Büchs J. Utilization of power input measurements for optimisation of cultureconditions in shaking flasks, Biochem. Eng. J. 17(3), 195-204, 2004 Losen M., Lingen B., Pohl M., BüchsJ., Effect of oxygen-limitation and medium compositionon Escherichia coli in small-scale cultures, Biotechnol. Progress. (accepted)

Prof. Dr. Manfred BiselliAachen University of Applied Science, Division JülichFaculty of Biotechnology

Prof. Dr.-Ing. Jochen BüchsRWTH Aachen University,Faculty of Bioprocess Engineering