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Design of Experiments for Bioprocess ApplicationsAndree Ellert
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Agenda
- A short profile of Sartorius
- DoE for Bioprocess Applications
- Detailed Case Study
- Integration of DoE into SCADA software
![Page 3: Design of Experiments for Bioprocess Applications Files/drupal...16 June 2011 Page 22-positive effect of point mutation on soluble space-time yield-significance: confidence interval](https://reader036.vdocument.in/reader036/viewer/2022070707/5ea3314cc8407410bf659f07/html5/thumbnails/3.jpg)
16 June 2011 Page 3
Group Structure*
Approx. 75%
100%Approx. 25%
Sartorius AG
* as of February, 2011
Sartorius AGOther
Shareholders
Sartorius Stedim Biotech S.A. Sartorius Mechatronics
Revenue 2010 €226.7 mnEmployees 1,934
Revenue 2010 €432.6 mnEmployees 2,581
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16 June 2011 Page 4
Two Group Divisions
Sartorius Stedim Biotech (SSB)Sartorius Stedim Biotech (SSB)Sartorius Stedim Biotech (SSB)Sartorius Stedim Biotech (SSB)
Sartorius Mechatronics (SMT)Sartorius Mechatronics (SMT)Sartorius Mechatronics (SMT)Sartorius Mechatronics (SMT)
� Strategically realigned as of 2009:
Evolving from a weighing technology
specialist into an applications expert
with a focus on the food and
pharmaceutical industries
� Listed on the Eurolist of the EuroNext Paris stock exchange
� Market leader in filtration, fermentation and in fluid management
� The No. 2 worldwide
� Total solution provider of laboratory andprocess weighing equipment
� Total solution provider for the biopharmaceutical industry
� Focus on single-use products
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16 June 2011 Page 5
Global Presence
Global manufacturingWorldwide sales subsidiaries
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16 June 2011 Page 6
Total Solution Provider: Single-use Biomanufacturing
Buffer
Pre
para
tion
Buffer
Pre
para
tion
Buffer
Pre
para
tion
Buffer
Pre
para
tion
Preparation Storage
Cell H
arve
stin
gCell H
arve
stin
gCell H
arve
stin
gCell H
arve
stin
g
Cell Removal Clarification Recirculation
Sterile Filtration Storage
CrossflowVolume Reduction Monitoring & Control
Purifica
tion
Purifica
tion
Purifica
tion
Purifica
tion
Affinity Chromat.Capturing Step
Polishing 2 Membrane Chromat.
SterileFiltration
CrossflowBuffer Exchange
CrossflowConcentration|Diafiltration
Low pH VirusInactivation
Polishing 1
Form and Fill
Controlled Freeze-thaw System
Preparation Storage
Med
ia P
repa
ration
Med
ia P
repa
ration
Med
ia P
repa
ration
Med
ia P
repa
ration
Cell L
ine
Cell L
ine
Cell L
ine
Cell L
ine
Ferm
enta
tion
Ferm
enta
tion
Ferm
enta
tion
Ferm
enta
tion
Seed Bioreactor Bioreactor
BioreactorSampling
Sterile Filtration
VirusInactivation Freeze-thaw Bags
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Agenda
- A short profile of Sartorius
- DoE for Bioprocess ApplicationsDoE for Bioprocess ApplicationsDoE for Bioprocess ApplicationsDoE for Bioprocess Applications
- Detailed Case Study
- Integration of DoE into SCADA software
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16 June 2011 Page 8
Media & buffer preparation
• drying time• water content• temperature• excipients• API content• ...
• flow rate• resin loading• bed height• resin type• pH value• ...
• filtration flux• TMP• retentate flow• membrane type• pore size• ...
• DO value• pH value• growth rate• temperature• inducer conc.• ...
• C-sources• amino acids• trace salts• pH value• mixing time• ...
factors
responses
• optimization of fill & finish steps
• improvement of flowability & compressibility
• ...
• optimization of clearance / polishing steps
• testing for process robustness
• ...
Fermentation
• optimization of clarification & concentration
• enhanced throughput capacity
• ...
Initial recovery
• optimization of fermentation conditions
• improvement of space-time yield / productivity
• ...
Polishing / virus clearance
Fill & finish
1111 2 3 4
• optimization of media & buffer composition
• reducing labor time and expense
• ...
5
Design of Experiments can be applied along the entire bioprocess chain
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16 June 2011 Page 9
Bioprocess Application: Media Preparation
Media & buffer preparation
Fermentation Initial recoveryPolishing /
virus clearanceFill & finish
1111 2 3 4 5
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16 June 2011 Page 10
Bioprocess Application: Media Preparation
- Shandong Lukang Pharmaceutical Group Co. (Jining, China) � 1,000 t/year
- same concentration of glutamine
- reduction of glutamate concentration by 53.6 %
- reduction of production costs by 7.1 % � 481,400 $/year
Media & buffer preparation
Fermentation Initial recoveryPolishing /
virus clearanceFill & finish
1111 2 3 4 5
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16 June 2011 Page 11
Bioprocess Application: Polishing | Virus Clearance
Media & buffer preparation
Fermentation Initial recoveryPolishing /
virus clearanceFill & finish
1111 2 3 4 5
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16 June 2011 Page 12
Bioprocess Application: Polishing | Virus Clearance
Media & buffer preparation
Fermentation Initial recoveryPolishing /
virus clearanceFill & finish
1111 2 3 4 5
- parameter variation over wide range does not affect AEX process
- design space was found, where removal of viral impurities can be assured
- AEX process is highly robust over the design space
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16 June 2011 Page 13
Bioprocess Application: Cell Culture | Fermentation
Media & buffer preparation
Fermentation Initial recoveryPolishing /
virus clearanceFill & finish
1111 2 3 4 5
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Agenda
- A short profile of Sartorius
- DoE for Bioprocess Applications
- Detailed Case StudyDetailed Case StudyDetailed Case StudyDetailed Case Study
- Integration of DoE into SCADA software
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16 June 2011 Page 1516 June 2011
E. coli MSD 5247
wild-type hEphB2
(D604-S898)
E. coli MSD 5248
mutated hEphB2
[L767P](D604-S898)
Model protein, expression vector and E. coli BL21 (DE3)
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16 June 2011 Page 1616 June 2011
Fluorescence measurement of protein expression reporter ZsGreen
- isolated from non-bioluminescent anemone Zoanthus sp. [Matz et al. 1999]- excitation/emission maximum: λex 496 nm / λem 506 nm
- Tecan GENiosTM fluorescence reader with 96 well microplates- excitation/emission wavelength: λex = 480 nm + 20 nm / λem= 530 nm + 20 nm
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16 June 2011 Page 1716 June 2011
inclusionbodies
solubleprotein
Typical course of a protein production process with E. coli MSD 5248
0
20
40
60
80
100
0
30
60
90
120
150
0 4 8 12 16 200
7
14
21
28
35
S48/53Zsol
S48/53Z_IB
t1
t2
ϑL
ϑL
[°C][%] [gl-1][103 RFU]
induction
pO2
S48/53Zk
production fed batchbatch
cXL_OD
cXL
pO2
t [h]
(0.8·10-3 moll-1 IPTG)
0.0
0.2
0.4
30
35
40
FR1
µ̂O2
[mlh-1]
FR1
µ̂O2
[h-1]
µ̂O2
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screening optimisation robustness
1. Screening
- Which factors significantly influence the response?
2. Optimisation
- Which factor settings result in optimal operation conditions?
3. Robustness testing
- How sensitive is the response to small changes in the optimal factors settings?
Strategy of experimentation – three primary DoE objectives
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16 June 2011 Page 1916 June 2011
15 20 25 30 35 400.0
0.1
0.2
0.3
0.4
0.5
µwhigh
ϑLmax
µmax
µmin
ϑLmin
µwhigh
[h-1]
ϑLlow
[°C]
screening
3 3
k 0 i i ij i ji 1 1 i j
linear terms interaction terms
y x x x k = 1 (sol), 2 (IB)= ≤ <
= β + β ⋅ + β ⋅ ⋅ + ε∑ ∑14243 1442443
Screening for significant expression factors in a large search domain
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16 June 2011 Page 2016 June 2011
Exemplary setup with multi-bioreactor system BIOSTAT® Qplus
MFCS/win
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16 June 2011 Page 2116 June 2011
- positive effect of point mutation on soluble space-time yield
soluble space-time yield
-6400
-4800
-3200
-1600
0
1600
3200
4800
6400
x2 · x
3x
1 · x
3x
3 (C
IPTG)
βIB
E. coli MSD 5247 (wt-hEphB2) E. coli MSD 5248 (mut-hEphB2)
x1 · x
2x
2 (ϑ
L)x
1 (µ
w)
-1200
-900
-600
-300
0
300
600
900
1200β
sol
E. coli MSD 5247 (wt-hEphB2) E. coli MSD 5248 (mut-hEphB2)
x2 · x
3x
1 · x
3x
3 (C
IPTG)
x
1 · x
2x
2 (ϑ
L)x
1 (µ
w)
insoluble space-time yield
Identification of significant factors after model fitting
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16 June 2011 Page 2216 June 2011
- positive effect of point mutation on soluble space-time yield- significance: confidence interval does not include zero & p-value < 0.05- all terms related to x3 (CIPTG) are not significant and hence deleted from the models
soluble space-time yield
-1200
-900
-600
-300
0
300
600
900
1200β
sol
E. coli MSD 5247 (wt-hEphB2) E. coli MSD 5248 (mut-hEphB2)
x2 · x
3x
1 · x
3x
3 (C
IPTG)
x
1 · x
2x
2 (ϑ
L)x
1 (µ
w)
Identification of significant factors after model fitting
X XXTerm Coefficient Conf.int. ± p-value
β1sol_47 163 73 0.003
β2sol_47 -207 73 0.001
β3sol_47 -9 73 0.756
β12sol_47 -117 73 0.011
β13sol_47 -22 73 0.458
β23sol_47 58 73 0.095
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16 June 2011 Page 2316 June 2011
model
ysol_5248
ysol_5247
0.576 > -0.0460.921 > 0.913
0.797 > 0.7240.894 < 0.922
model
yIB_5248
yIB_5247 0.929 > 0.8540.968 < 0.983
0.852 > 0.2650.965 > 0.939
2adjR 2Q
2adjR 2Q
-1200
-900
-600
-300
0
300
600
900
1200β
sol
E. coli MSD 5247 (wt-hEphB2) E. coli MSD 5248 (mut-hEphB2)
x1 · x
2x
2 (ϑ
L)x
1 (µ
w)
-6400
-4800
-3200
-1600
0
1600
3200
4800
6400β
IB
E. coli MSD 5247 (wt-hEphB2) E. coli MSD 5248 (mut-hEphB2)
x1 · x
2x
2 (ϑ
L)x
1 (µ
w)
soluble space-time yield insoluble space-time yield
Model pruning results in higher model quality
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16 June 2011 Page 2416 June 2011
MSD 5247
(wt-hEphB2)
MSD 5248
(mut-hEphB2)
soluble space-time yield insoluble space-time yield
Use of regression models for definition of an optimisation region
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16 June 2011 Page 2516 June 2011
15 20 25 30 35 400.0
0.1
0.2
0.3
0.4
0.5
µwhigh
ϑLmax
µmax
µmin
ϑLmin
µwhigh
[h-1]
ϑLlow
[°C]
screeningoptimisation
2 2 22
k 0 i i ij i j ii ii 1 1 i j i 1
linear terms interaction terms quadratic terms
y x x x x k = 1 (sol), 2 (IB)= ≤ < =
= β + β ⋅ + β ⋅ ⋅ + β ⋅ + ε∑ ∑ ∑14243 1442443 14243
The central composite circumscribed (CCC) optimisation design
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16 June 2011 Page 2616 June 2011
- optimal point at µw = 0.25 h-1 / ϑL = 26.6 °C
- STYsol 28-times higher compared to STYsol
in screening with µw = 0.08 h-1 / ϑL = 37 °C
- optimal point at µw = 0.25 h-1 / ϑL = 30.5 °C
- STYIB 30-times higher compared to STYIB
in screening with µw = 0.08 h-1 / ϑL = 37 °C
soluble space-time yield
2 2adjR 0.950 / Q 0.942= =
3130
2928
2726
3500
7000
10500
14000
17500
0.160.18
0.200.22
0.240.26
ST
Yso
l [RF
Uh-1
]
µw [h-1]ϑ
L [°C]
3130
2928
2726
12000
24000
36000
48000
60000
0.160.18
0.200.22
0.240.26
ST
YIB
[RF
Uh-1
]
µw [h-1]ϑ
L [°C]
insoluble space-time yield
2 2adjR 0.966 / Q 0.918= =
Use of regression models for response surface modelling
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16 June 2011 Page 2716 June 2011
2adjR 0.999 =
soluble space-time yield
0 3 6 9 12 15 180
3
6
9
12
15
18
^
[103 RFUh-1]
ysol
[103 RFUh-1]ysol
0 10 20 30 40 50 600
10
20
30
40
50
60
^
[103 RFUh-1]
yIB
[103 RFUh-1]yIB
2adjR 0.994=
9
2
2
4
5
DF
167.0
3.563
0.172
3.735
163.3
SS x 106
Total
Pure Error
Lack of Fit
Residual
Model
source
34.97 > 6.2632.65
0.048 < 19.00.086
0.934
F-valueMS x 106
18.56
1.781
9
2
2
4
5
DF
867.7
7.610
5.430
13.04
854.7
SS x 106
Total
Pure Error
Lack of Fit
Residual
Model
source
52.43 > 6.26170.9
0.714 < 19.02.715
3.260
F-valueMS x 106
96.41
3.805
insoluble space-time yield
ANalysis Of VAriance (ANOVA) for the regression models
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16 June 2011 Page 2816 June 2011
- space-time yield must show robustness compared to small deviations in factor levels
- response is robust, if Q² is low and values vary around ± σ of CP mean
The 2² full factorial robustness design
15 20 25 30 35 400.0
0.1
0.2
0.3
0.4
0.5
µwhigh
ϑLmax
µmax
µmin
ϑLmin
µwhigh
[h-1]
ϑLlow
[°C]
screeningoptimisationrobustness
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16 June 2011 Page 2916 June 2011
insoluble space-time yield
0
10000
20000
30000
40000
50000
- σ
+ σ
- σ
+ σ
soluble space-time yield insoluble space-time yield
6
6
5
5
4
4
3
3
2
2
1
1
replicate index5432
1
spac
e-tim
e yi
eld
[RF
Uh-1
]
2sol2IB
Q < 0.001
Q < 0.001
soluble space-time yield
Response robustness compared to small factor changes
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16 June 2011 Page 3016 June 2011
Observed problems during experimentation
- recipes for each bioreactor had to be changed according to strategy
- individual start of multiple experiments
- lot of manual data typing
→ time-consuming work, inefficient workflow, error-prone procedure!
MODDE 9.0 by UMETRICSBioPAT® MFCS/win 3.0
X
![Page 31: Design of Experiments for Bioprocess Applications Files/drupal...16 June 2011 Page 22-positive effect of point mutation on soluble space-time yield-significance: confidence interval](https://reader036.vdocument.in/reader036/viewer/2022070707/5ea3314cc8407410bf659f07/html5/thumbnails/31.jpg)
Agenda
- A short profile of Sartorius
- DoE for Bioprocess Applications
- Detailed Case Study
- Integration of DoE into SCADA software Integration of DoE into SCADA software Integration of DoE into SCADA software Integration of DoE into SCADA software
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16 June 2011 Page 3216 June 2011
The BioPAT® MFCS/win DoE module
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16 June 2011 Page 3316 June 2011
The BioPAT® MFCS/win DoE module
MODDE 9.0 by UMETRICSBioPAT® MFCS/win 3.0
�
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Thank you!