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 166980christoph.herwig@tuwien.ac.at

http://institute.tuwien.ac.at/chemical_engineering/bioprocess_engineering/EN/