Automated sampling and on-line analytics to increase process understanding

Abstract

Generation of process understanding is the key task to enable quality by design (QbD) and process analytical technology (PAT) as “a system for designing, analyzing and controlling” bioprocesses. Understanding of the underlying physiologic and metabolic mechanisms allows to interpret process variability, control it and guarantee for a safe product.
Automation technology for liquid handling, facilitating automated sampling as well as on-line analytics, is a fundamental task enabling deeper process understanding as well as process monitoring and control.
The application of an automated sampling and sample processing system (Numera) is demonstrated for raw material characterization and real-time monitoring. Within the raw material characterization, the system enabled the description of enzymatic release kinetics in the complex raw material corn steep liquor. The trigger for this application was the higher frequency, higher reproducibility in comparison to hand-drawn samples and the use in the 4-reactor parallel mode. Real-time monitoring was applied in a mammalian cell culture process for analysis of amino acid patterns allowing conclusions about cell metabolism in real-time.
Summarizing, it could be shown, that automated liquid handling is a hard-to-replace PAT tool for current and future challenges in biotechnology.

Full text

IFPAC Washington, 5 March, 2019 Slide 1
Automated sampling and
on-line analytics to increase
process understanding
Dr Alexandra Hofer, Dr Paul Kroll and
Prof Christoph Herwig

IFPAC Washington, 5 March, 2019 Slide 2
Short introduction
Securecell AG
Information Technology
Bioprocess automation
Process analytical technology
Process Information
Management Software

IFPAC Washington, 5 March, 2019 Slide 3
Research partners
Technical University Vienna
Division: Biochemical Engineering
Prof. Christoph Herwig
Zurich University of Applied
Sciences
Division: Bioprocess Technology
Dr. Lukas Neutsch

IFPAC Washington, 5 March, 2019 Slide 4
PAT –Process Analytical Technology
PAT:
“a system for designing, analyzing, and controlling manufacturing
through timely measurements (i.e., during processing) of critical
quality and performance attributes …” (FDA PAT initiative)
Science- based approach →for generation of process understanding
−measurements of critical parameters in supernatant or gas phase
−systematic observation of the bioprocess →monitoring

IFPAC Washington, 5 March, 2019 Slide 5
PAT –Process Analytical Technology
State of the art of monitoring
CPP; Critical material attributes (CMA)
Critical quality attributes (CQA)
Key process indicators (KPI)
In-line analysis
On-line analysis
At-line/ Off-line analysis
•Biomass (OD, CDW, VCC)
•Substrates / Metabolites
•Product
•Product quality
SIR
M
CW 220V M
ES
;
O2
Air
FIRC
FIRC
QIR O2
QIR R-OH
QIR CO2
Gas
Analyzer
Waste Air
Waste Air
PIRC
HV1
CW
FIRC
M
EA
;
WIR
M
ES
;
OD
QIRC pO2
QIR Biomass
TIRC
M
EA
;
FIRC
Feed 2
Feed 1
Base
WIR
WIR
Steam
Off-line
On-line
In-line
or
Septum
QIRC pH
Sensor
OD
QIR Biomass
QIR Biomass
CDW
Off-line
Manual
Air
HV3
HV2
QIR Biomass
Permit.

IFPAC Washington, 5 March, 2019 Slide 6
Sampling
Basis for monitoring and control task →sampling
Workflow today
Manual sampling
−tedious
−risk of
contamination
Sample processing
−centrifugation/
filtration
−dilution
−extraction
Off-line/at-line analysis
−manual transfer Data management
−paper-based
−merge with
process data
difficult
Bioreactor

IFPAC Washington, 5 March, 2019 Slide 7
Sampling
direct measurement of
specific analytes
usage of highly
automated offline
analyzers
reliability through
application of reference
methods
extensive parallelization
flexibility and storage
of reference samples for
later analysis
risk for contamination of
the process and sample
high sampling volume
needed
operator-to-operator
deviations (error-prone)
tedious; requires a lot of
human resources
low sampling frequency
and commonly no real-
time availability of data
paper-based and error-
prone data management

IFPAC Washington, 5 March, 2019 Slide 8
Solution: Automation and Digitization
➢Modular system
➢Automated sampling,
sample preparation (dilution,
extraction, filtration) and
storage of cell suspension
and supernatant
➢Parallelization
➢Flexibility: adaptable to
process
First step: automated sampling

IFPAC Washington, 5 March, 2019 Slide 9
Manual versus automated sampling
Numera tested @ ZHAW in Switzerland
Pichia pastoris
Repeated fed-batch
Automated sampling enables
Low volume and high
frequency samples
Highly reliable results
At-line analysis with
reference method

IFPAC Washington, 5 March, 2019 Slide 10
Application example
Complex raw material analysis

IFPAC Washington, 5 March, 2019 Slide 11
Background
Process: Penicillium chrysogenum for production of antibiotics
Goal: Investigation of effects of complex raw material (CSL) on process
performance/ fungal physiology →to generate process understanding
Main target: identification of bioavailability of amino acids from CSL

IFPAC Washington, 5 March, 2019 Slide 12
Background
Process: Penicillium chrysogenum for production of antibiotics
Goal: Investigation of effects of complex raw material (CSL) on process
performance/ fungal physiology →to generate process understanding
Main target: identification of bioavailability of amino acids from CSL
CS L
AspGlyThr Cys
Cys Gln
Ala
Ala
TyrHis
Glu
His
Glu
Asp
SP
LP

IFPAC Washington, 5 March, 2019 Slide 13
Background
Process: Penicillium chrysogenum for production of antibiotics
Goal: Investigation of effects of complex raw material (CSL) on process
performance/ fungal physiology →to generate process understanding
Main target: identification of bioavailability of amino acids from CSL
CS L
Ser
Ala
Phe
Ser
Leu
Asp Gly Thr Cys
Cys Gln
Ala
Ala
TyrHis
Glu
HisGluAsp

IFPAC Washington, 5 March, 2019 Slide 14
Background
Process: Penicillium chrysogenum for production of antibiotics
Goal: Investigation of effects of complex raw material (CSL) on process
performance/ fungal physiology →to generate process understanding
Main target: identification of bioavailability of amino acids from CSL
CS L
Ser
Ala
Phe
Ser
Leu
Asp Gly Thr Cys
Cys Gln
Ala
Ala
TyrHis
Glu
HisGluAsp
mSR,i
Ala
Phe
Ser

IFPAC Washington, 5 March, 2019 Slide 15
Background
Process: Penicillium chrysogenum for production of antibiotics
Goal: Investigation of effects of complex raw material (CSL) on process
performance/ fungal physiology →to generate process understanding
Main target: identification of bioavailability of amino acids from CSL
CS L
Ser
Ala
Phe
Ser
Leu
Asp Gly Thr Cys
Cys Gln
Ala
Ala
TyrHis
Glu
HisGluAsp
mSR,i
Ala
Phe
Ser
rE

IFPAC Washington, 5 March, 2019 Slide 16
Background
Process: Penicillium chrysogenum for production of antibiotics
Goal: Investigation of effects of complex raw material (CSL) on process
performance/ fungal physiology →to generate process understanding
Main target: identification of bioavailability of amino acids from CSL
CS L
Ser
Ala
Phe
Ser
Leu
Asp Gly Thr Cys
Cys Gln
Ala
Ala
TyrHis
Glu
HisGluAsp
mSR,i
Ala
Phe
Ser
rE
rER,i rER,i
Gln
Cys
Thr
Asp
His Ala
Thr Cys
Glu

IFPAC Washington, 5 March, 2019 Slide 17
Background
Process: Penicillium chrysogenum for production of antibiotics
Goal: Investigation of effects of complex raw material (CSL) on process
performance/ fungal physiology →to generate process understanding
Main target: identification of bioavailability of amino acids from CSL
CS L
Ser
Ala
Phe
Ser
Leu
Asp Gly Thr Cys
Cys Gln
Ala
Ala
TyrHis
Glu
HisGluAsp
mSR,i
Ala
Phe
Ser
rE
rER,i rER,i
Gln
Cys
Thr
Asp
His Ala
Thr Cys
Glu
qiqi

IFPAC Washington, 5 March, 2019 Slide 18
How to investigate bioavailability?
Experimental plan
−Media experiment (with CSL)
−Addition of sterile supernatant of fungi fermentation (enzyme-mix)
−Monitor amino acids over time
GOAL: identify enzymatic release rates of amino acids
from complex material (CSL)

IFPAC Washington, 5 March, 2019 Slide 19
How to investigate bioavailability?
Experimental plan
−Media experiment (with CSL)
−Addition of sterile supernatant of fungi fermentation (enzyme-mix)
−Monitor amino acids over time
Set-up
−4 parallel reactors (DASbox, Eppendorf)
−Numera for automated sampling & sample processing
−HPLC for analytics
GOAL: identify enzymatic release rates of amino acids
from complex material (CSL)

IFPAC Washington, 5 March, 2019 Slide 20
Result
Automated sampling with Numera allows high frequency sampling in multibioreactor system
➢Sample frequency once per
hour; every 6h
➢Sampling for 72h (over night)
➢Two phases can be identified

IFPAC Washington, 5 March, 2019 Slide 21
Result
Automated sampling with Numera allows high frequency sampling in multibioreactor system
→More data, more information →Monod model can be fitted
→Enzymatic release rate rER,i for 10 amino acids identified

IFPAC Washington, 5 March, 2019 Slide 22
Result
Automated sampling with Numera allows high frequency sampling in multibioreactor system
→More data, more information →Monod model can be fitted
→Enzymatic release rate rER,i for 10 amino acids identified
→Process understanding can be gained

IFPAC Washington, 5 March, 2019 Slide 23
Result
Automated sampling with Numera allows high frequency sampling in multibioreactor system
→More data, more information →Monod model can be fitted
→Enzymatic release rate rER,i for 10 amino acids identified
→Process understanding can be gained
Highly automated
Without manual intervention
One experiment –more data –more information

IFPAC Washington, 5 March, 2019 Slide 24
Automated Sampling
direct measurement of
specific analytes
usage of highly
automated offline
analyzers
reliability through
application of reference
methods
extensive parallelization
flexibility and storage
of reference samples for
later analysis
risk for contamination of
the process and sample
high sampling volume
needed
operator-to-operator
deviations (error-prone)
tedious; requires a lot of
human resources
low sampling frequency
and commonly no real-
time availability of data
paper-based and error-
prone data management

IFPAC Washington, 5 March, 2019 Slide 25
Application example
On-line monitoringof CHO process

IFPAC Washington, 5 March, 2019 Slide 26
Automated sampling & on-line analytics
Challenge →From measurement to monitoring!
(1) Automated sampling
(2) Transfer to analyzer
(3) Data management
(4) Process control
(1) (2)
(3)(4) ?
?
?

IFPAC Washington, 5 March, 2019 Slide 27
Automated sampling & on-line analytics
Online analytics available through automated sampling (Numera)
Feedback/ control enabled via process management system (Lucullus PIMS)

IFPAC Washington, 5 March, 2019 Slide 28
Set-up @ TU Vienna
Fully automated analysis of product, vitamins and amino acids by HPLC
and of substrates, metabolites and product by Cedex BioHT enabled by
Numera and Lucullus

IFPAC Washington, 5 March, 2019 Slide 29
On-line monitoring of CHO cultivation
Substrate & metabolites
–Glucose, Lactate and Ammonia
–Monitoring with Cedex Bio HT
–Data point every 2 h (every 30 min
possible)
–Analytical data available in Lucullus
PIMS

IFPAC Washington, 5 March, 2019 Slide 30
On-line monitoring of CHO cultivation
Product
–IgG
–Monitoring with HPLC
–Data point every 1 h (every 15 min
possible)
–High-frequency
–24/7 →no attendance needed

IFPAC Washington, 5 March, 2019 Slide 31
On-line monitoring of CHO cultivation
Amino acids
–Monitoring with HPLC
–21 amino acids can be analyzed

IFPAC Washington, 5 March, 2019 Slide 32
On-line monitoring of CHO cultivation
Amino acids
–Monitoring with HPLC
–21 amino acids can be analyzed
Benefits
−Process transparency
−Early decisions in process development
−Possibilities for control actions

IFPAC Washington, 5 March, 2019 Slide 33
Automated sampling, on-line analytics and Lucullus PIMS
direct measurement of
specific analytes
usage of highly
automated offline
analyzers
reliability through
application of reference
methods
extensive parallelization
flexibility and storage
of reference samples for
later analysis
risk for contamination of
the process and sample
high sampling volume
needed
operator-to-operator
deviations (error-prone)
tedious; requires a lot of
human resources
low sampling frequency
and commonly no real-
time availability of data
paper-based and error-
prone data management

IFPAC Washington, 5 March, 2019 Slide 34
Automated sampling, on-line analytics and Lucullus PIMS
direct measurement of
specific analytes
usage of highly
automated offline
analyzers
reliability through
application of reference
methods
extensive parallelization
flexibility and storage
of reference samples for
later analysis
no risk of contamination
of the process and sample
low sampling volume
possible
High reliability
manual intervention
reduced to minimum
high sampling frequency
and real-time availability of
data
Automated data
management

IFPAC Washington, 5 March, 2019 Slide 35
Summary
✓PAT tools are essential in pharmaceutical development, manufacturing, and
quality assurance
✓Numera and Lucullus represent an integrated PAT solution
✓High frequent, on-line measurements facilitate
•process transparency and knowledge generation (standardized, reliable, accurate, automated
procedures)
•early decisions in process development (real time, high frequent, 24/7 measurement)
•control strategies (feed-back control loop)

IFPAC Washington, 5 March, 2019 Slide 36

Thank you for
your attention!
Contact
alexandra.hofer@securecell.ch
Securecell AG
www.securecell.ch
Follow us on

IFPAC Washington, 5 March, 2019 Slide 38
Sampling frequency
Sample processing
Duration
min
Frequency
h
-1
day
-1
Direct transfer
6’
10 h
-1
240 day
-1
Sampling + Filtration
10’
6 h
-1
144 day
-1
Sampling + Dilution
12’
5 h
-1
120 day
-1
Sampling + Dilution+ Filtration
15’
4 h
-1
96 day
-1

IFPAC Washington, 5 March, 2019 Slide 39
Application I: raw material analysis
Approach Experimental assessment of hypothesis
Result Pulse of limiting amino acid could increase titer by three-fold