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QIR N.N
QIR N.N.
QIR Gluc
QIR EtOH
QIR MeOH
QIR Gly
SIR
CW 220VES;
O2
Air
FIRCFIRC
QIR O2
QIR R-OH
QIR CO2
GasAnalyzer
Figaro
Was
te A
ir
Waste Air
PIRC
Air
HV1
HV3
HV2
CW
ES;
To Inactivation Collection
FIRC
ES;
EA;
WIR
ES;
QIR MeOH QIR EtOH QIR HAc QIR FAc QIR FAl QIR AcAlGas Chromatograph
QIR MeOH QIR EtOH QIR Gly QIR Gluc QIR Sorb QIR N.NEnyzmatic Phomotric Robot
FTIR
Turbidity
QIRC pH
QIRC pO2
QIR Biomass
QIR Biomass
Capcit.
QIR NADH
Fluoresc.
EA;
FIRC
In-line
On-line
Off-line
Feed 2
Feed 1
Base
WIR
WIR
Steam
Off-line
WIRC
orSeptum
Indication Recording
FIRC
FI
FIRC
Control
PIMS
PIMS
Local
PIMS
PIMS
NONE
PLS
PIMS
NONE
LEGEND
On-line
On-line
In-line
S
l
Biochemical Engineering
Bioprocess Technology
Our Vision
We build bridges between the “omics” sciences, process development and scale up for industrially relevant biopharmaceutical processes
Our Goal
Method development for efficient and scientifically based biopharmaceutical process development
2
GenomicsProteomics
Metabolomics
BioprocessDevelopment
Facility design& Realization
Qualification& Operation
Scale Up
Produce what you wanted(cGMP)
Build what you wanted(cGMP)
Field of Research Teaching
3
Research Area Biochemical Engineering
Integrated Quality by Design Approach
CO2 Fixation and Renewable Energy
Integrated Bioprocess Development
Straw Biorefinery
Wood Decay and Wood Aging Processes
Biotechnology for Wood and Forest Industry
Red Biotechnology On-line Monitoring of biomass, metabolites, internal components and recombinant protein direct and indirect determination of specific rates and Yields in Real Time Metabolic Modelling Transient experiments for quick derivation of Design Space
Emission control
Bio- control
Function-alization
Enzymatic, biomimetic, or microbial treatment of wood materials or living plants.
Development of an efficient, low temperature biomass fractionation process for the produc- tion of value-added chemicals and materials from annual plants.
Renewable Energy from Waste Biohydrogen and Biomethane production from Waste streams Striktly Anaerobic Cultivations Quantitative bioprocess development
Process understanding across unit operations Quality by Design Studies on propagation of effects from fermentation to purification Debottleneck DSP Alternatives chromatography Strategies for optimized multiproduct facilities
Sizereduction
Pre-treatment
Filterpress
Precipi-tation
Enzymatichydrolysis
Bleaching
Lignin
Xylose solution
Pulp (DP)
Enzymes
Pretreatmentchemicals
Stra
w
Stra
w
Pre
treat
ed
Stra
w
Pret
reat
men
t liq
uor
Sold
frac
tion
Sold
frac
tion
4
Quantitative Bioprocess Development for Production of Biofuels and cocurrent CO2 Fixation
Motivation
CO2 emissions are made responsible for climate change. Source of renewable energies (such as wind or solar energy) need to be made storeable.
Mission
Development of a robust and economic competitive process for biofuels Using raw material from renewable energy sources Fixation of CO2 Prove the feasibility to use real emission gases
Our research focuses on: Technology development and integration of 2nd and 4th generation of biomass utilization Quantification and scale up of biohydrogen, bioethanol and biomethane production Comprehensive and quantitative process development aiming for industrial application
The technology will be very important in respect to the global carbon cycle and renewable energy production.
On-line and off-line analytics as well as PAT are used for real time data exploitation
CH4 production from H2 and CO2
0
10
20
30
40
50
60
70
80
90
6 8 10 12 14 16
Time [h]
Off
gas
[%]
CH4 CO2 H2
CH4CO2H2 Integration
Anaerobic CO2 Production by S. cerevisiae
0
0,5
1
1,5
2
2,5
3
3,5
4
4,5
5
0 2 4 6 8 10 12
Time [h]
CO
2 [%
]
CO2
Methanogenic Archaeaconvert H2 and CO2 to CH4
S. cerevisiae for bioethanol and concomitant CO2 production
Facultative and strict anaerobic bacteria
Automation & bioprocess control
H2 Production by E.aerogenes
0
1
2
3
4
5
6
7
8
9
0 5 10 15 20 25 30 35
Time [h]
H2
[%
]
H2
Output
Methods and Results
5
Generic Tools for QbD, PAT and Bioprocess Identification
Motivation
Quality by Design (QbD) is used to extract process knowledge and information from experimental data to reach process understanding.Quantitative robust variables must be derived for identification of critical process parameters (CPPs) for critical quality attributes (CQAs).Generic approaches must be provided to allow the paradigm change from empirical to sci-ence based bioprocess development.
Mission
Develop generic tools to apply the PAT/QbD approach to different cultures and bioprocess modes.
Extraction of process understanding in a real-time automated bioreactor setup Generic approach: extension to different cultures, bioprocess setups and culture modes Development of quality processes robust regarding quality and productivity Extrapolate Approach to dynamic process conditions: quicker and more exhaustive metabolic analysis
Output & Outlook
Experimental Design Data Information Knowledge
Design of Experiments• Identification of CCPs/CQAs• Risk based approach to
identify non critical parameters• Definition of analytics: What
signal quality is needed for which CCPs/CQAs?
Real Time Measurements• Off-gas• Feed rates, base consumption• In-line sensors: FT-MIR,
capacitance• At-line: GC, Enyzmatic
Photometric
Morphology• High throughput, • Automated light microscopy• x,y,z axis scanning• Feature extraction algorithms
Data Mining• Calculation of scale-
independent specific rates and yields
• Determination of morphologic key parameters
Soft Sensors• Kinetic Models, Metabolic
Analysis Observers• Calculation of non-measured
quantitiesReconciliationConsistency check
Design space• Data exploitation routines• Extraction of process
understanding• Establishment of design space• Control strategies
Determining morphologic key parameters
image analysis, normalization, quantification and classification
using in-house developed Matlab© routines
Model buildingsuggestion of mechanistic,
structured morphologic;unstructured stoichometric,
as well as hybrid models
Hybrid Models
TCA
Metabolic Flux Model
TCATCA
Metabolic Flux Model
P
Growing regions (A0)
Non-growing regions (A1)
Vacuoles (A2)
Autolysed region (A4)
Degen. region (A3)Product formation associated compartments / enzyme pools A1PC
A1
A2 A3
A0
A4
A1PCI
II
I III IV
V VI
VI’ VII
Structured Morphologic Model cf. [3,4]
P
6
Biopharmaceutical Downstream Processing and Integrated Bioprocess Development
Introduction
The bottleneck for many biopharmaceutical production processes lies in the purification of the product by chromatography, as product titers will increase. Therefore R&D activities are needed to debottleneck the Downstream Process (DSP) by:
understanding propagation of effects across the unit operations, employing Quality by Design (QbD) principles using Design of Experiments (DoE) development of alternative unit operations for purification, mainly for the capture step
and strategies for optimization of the use of multiproduct facilities
Biochemical Engineering is interdisciplinary. We need to look beyond the fermentation.The combination of all activities shown allow the determination of how to fit the processto facility or fit the facility to process.
Upstream Output Considerations (Titer g/L) for the next ten years in the biopharmaceutical industry
Batch
Fedbatch for high cell density
Fedbatch for protein production
Harvest &Cell disruption
Protein-solubilization &refolding
Filtration
CaptureChromatography
Ultra & Dia-Filtration
Final Purification Chromatography
Lyophilisation/ Freezing
Process understanding across unit operations Debottleneck DSP
Strategies for optimized multiproduct facilities
By employing QbD principles, it is our goal to analyze and understand the effect of changed process parameters in the USP area on the resulting pro-duct quality attri-butes in the DSP area.
The variations of the different pro-cess parameters are carried out according to DoE. We thereby under-stand the propagati-on of the CPP to CQA relationships across unit opera-tions. This allows the analysis of the whole process: from the cryo-tube to the purified and frozen protein.
Integrated time & motion analysis tools allow the analysis of the rate limiting step for increased productivity in a given multipro-duct facility.
Due to the expected future high titers from optimized expression systems, we aim to establish new methods beyond chromatography such as • crystallization • precipitation • membrane assisted Aqueous 2-phase systems (ATPS) • membrane adsorber
available DSP infrastructurehomogenizers, crossflow filtration unit, refolding tank, K-Prime chromatography system
Outlook
Goals and activities
7
Field for Collaboration
We carry out Quantitative Strain Characterization Analysis of Physiological Regulations Responding to Stress conditions
Metabolic Engineering Cell Modeling, e.g. Metabolic Flux Analysis Media Optimization using on-line decision making tools
We conduct Characterization & Development of On-line Monitoring Instruments Determination of On-line Measurement of Specific Compound
We investigate Innovative DoE strategies using dynamic process conditions Limits of the design space, such as maximum metabolic (intrinsic) rates
and adaptation times, using on-line exploitation methods
We integrate Instruments and data analysis tools in ready made exploitation tools
which are commercially availabel for the industry for efficient process development
Data exploitation tools for quantitative Strain Characterization
and Process Development
Characterization & Developmentof
On-line Monitoring Devices
Media Development Experimental design
Design Space Determination Control Strategies
Analysis of Physiological Regulations upon Stress Conditions System Biology
Method Development
for Efficient and Scientifically
Based Bioprocess Development
Productivity
Conversion
Quality
Concentration
Continiousculture
Batch Fed-BatchPerfusion
Transientculture
PAT
DoEIC
HQ8/9
QbD
Contact:
Vienna University of TechnologyInstitute of Chemical EngineeringResearch Division Biochemical EngineeringGumpendorferstraße 1a1060 ViennaAustria
Univ.Prof. Dipl.-Ing. Dr.techn. Christoph HerwigT +43 1 58801 166400M +43 676 4737217F +43 1 58801 [email protected]
http://institute.tuwien.ac.at/chemical_engineering/bioprocess_engineering/EN/