Application of HTP microfluidic culture systems to media and process optimisation
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Transcript of Application of HTP microfluidic culture systems to media and process optimisation
Application of HTP microfluidic culture systems to media and process optimisation
Steven C. Peppers, Ph.D., MBAPrincipal Scientist, R&D
Reg Joseph, B.Sc., MBABusiness Area Manager, BioProduction
BioProduction Systems and ServicesInvitrogen Corporation
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Complexity of Cell’s Needs
Metabolic pathways chart fromBoehrringer-Mannheim
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Complexity of culture systems
Interactions within:Uptake of nutrientsReceptor signalingMetabolic pathwaysPhysicochemical qualitiesDynamic states
No tools to fully probe this complexity
Build up of components at inappropriate concentrations
Special technologies for managing complexity:1. Statistical designs and strategy2. Scaled down HTP tools3. Expertise in cell requirements and media components
DOE (Design of Experiment):
Statistically sound means of planning and analyzing efficient experiments:
Examples: 2-level factorials and fractional factorials, central composite designs, minimum run designs, mixtures, steepest ascent, Box-Behnken, D-optimal
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Multi-factor central composite designs
Com
pone
nt B
(Glu
tam
ine,
nM
)
-1 (4)
+1 (8)
0 (6)
Component A(Glucose, g/L)
-1 (2) +1 (4)0 (3)
Compo
nent
C
(Osm
olality
)
Run#
AGluc.
BL-Gln
COsm
1 -1 -1 +1
2 +1 -1 -1
3 -1 +1 -14 +1 +1 +1
5 0 0 0
6 0 0 0
7 -1.4 0 0
8 +1.4 0 09 0 -1.4 0
10 0 +1.4 011 0 0 -1.4
12 0 0 +1.4
Run chart showing coded levels
Half-factorial central composite for 3 factors
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What’s The Right Tool For The Right Job?
Requirement
Currently Used Platforms New Tool
Well Plates Shake Flasks Stirred Tank
BioreactorsBioProcessor
s SimCell
HTP Yes Rather limited No Yes
Scalable No Not generally Yes Yes
Reliable Yes Yes Yes Yes
Efficient No No No Yes
Effective bioprocess development tool:1. High throughput—100’s of different conditions2. Scalable—Predict performance in ST bioreactors3. Reliable—High precision, accuracy and reproducibility4. Efficient—Process in time and labor, cost effective
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Micro-Bioreactor Array (MBA)
6 Chambers
600 uL Working Vol.
Independent Loading
Stirring by Bubble
Invitrogen working with BioProcessors
for 2 yr
BioProcessors SimCell System
Incubation Modules
Loading Cell
Sampling Module
Optical Sensing Module
Fluidic Module
Central Robot
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Scalability of SimCell Results
SimCell at Day 6
pH 6.9 4.45 x106 TC/mL
pH 7.2 3.07 x106 TC/mL
Difference/Average = 36.7%
ST Bioreactors at Day 6
pH 6.9 4.57 x106 TC/mL
pH 7.2 3.13 x106 TC/mL
Difference/Average = 37.4%
Ratio of “Dif/Avg” values = 0.98
SimCell MicroBioreactors with CHO CellsMean +/- SD (n=6)
0
1
2
3
4
5
6
0 1 2 3 4 5 6 7 8Days
Tota
l Cel
ls/m
L x1
06
(by
Opt
ical
Den
sity
)
pH 6.9pH 7.2
Stirred Tank Bioreactors with CHO CellsMean +/- SD (n=2)
0
1
2
3
4
5
6
0 1 2 3 4 5 6 7 8
Days
Tota
l Cel
ls/m
L x1
06
pH 6.9pH 7.2
SimCell MicroBioreactors with CHO CellsMean +/- SD (n=6)
0
1
2
3
4
5
6
0 1 2 3 4 5 6 7 8Days
Tota
l Cel
ls/m
L x1
06
(by
Opt
ical
Den
sity
)
pH 6.9pH 7.2
Stirred Tank Bioreactors with CHO CellsMean +/- SD (n=2)
0
1
2
3
4
5
6
0 1 2 3 4 5 6 7 8
Days
Tota
l Cel
ls/m
L x1
06
pH 6.9pH 7.2
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Complex Factorials in SimCell
Starting Media and pH Conditons Feed Additions, Day 4Level pH Osmo Target Glucose Glutamine Pluronic Gluc Feed Glutamate FeedAspartate
-1.68 6.9 246.2 0.64 0.32 0.8 0 0 0-1 6.9 270 2 1 0.8 0 0 00 7.1 305 4 2 1.3 2 2 0.16651 7.3 340 6 3 1.8 4 4 0.3330
1.68 7.3 363.8 7.36 3.68 2.14 5.36 5.36 0.4462
Coded Level
Goal: Confirm SimCell capability in complex factorials
Fractional Central Composite Design, N=192
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Design-Expert® Software
Total Cell DensityAvg. Days 6-8
X1 = C: Glucose in Starting Medium
X2 = F: Glucose FeedDay 4
Response Surface C:FWith Other Factors at:A: pH = 6.9B: Osmo = 270 mOsmD: GLN = 3 mME: Pluronic = 1.8 g/LG: GLU Feed = 4 mMH: ASP Feed = 0.33 fold
13
46
7
0
1
3
4
5
1E+006
2E+006
3E+006
4E+006
5E+006
Cel
ls /
mL
X1: Glucoseat Start (g/L)
X2: Gluc.Feedat day4 (g/L)
Design-Expert® Software
Total Cell DensityAvg. Days 6-8
X1 = C: Glucose in Starting Medium
X2 = F: Glucose FeedDay 4
Response Surface C:FWith Other Factors at:A: pH = 6.9B: Osmo = 270 mOsmD: GLN = 3 mME: Pluronic = 1.8 g/LG: GLU Feed = 4 mMH: ASP Feed = 0.33 fold
13
46
7
0
1
3
4
5
1E+006
2E+006
3E+006
4E+006
5E+006
Cel
ls /
mL
X1: Glucoseat Start (g/L)
X2: Gluc.Feedat day4 (g/L)
Response Surface from Analysis
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Interaction in Late Log Phase Growth
Design-Expert® Software
OD Avg 5-6.5 days
Design Points
C- 2.000C+ 6.000
X1 = A: pHX2 = C: Glucose
Actual FactorsB: Osmo = 305.00D: Glutamine = 2.00E: Pluronic = 1.30F: Gluc Feed = 2.00G: Glutamate = 2.00H: Aspartate = 0.167
Glucose at Start (g/L)
6.90 7.00 7.10 7.20 7.30
Interaction
A: pH
OD
Avg
5-6
.5 d
ays
7.00E+05
1.55E+06
2.40E+06
3.25E+06
4.10E+06
22
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Interaction in Final tPA Productivity
Design-Expert® Software
tPA at Day 8
Design Points
C- 2.000C+ 6.000
X1 = A: pHX2 = C: Glucose
Actual FactorsB: Osmo = 305.00D: Glutamine = 2.00E: Pluronic = 1.30F: Gluc Feed = 2.00G: Glutamate = 2.00H: Aspartate = 0.167
Glucose at Start (g/L)
6.90 7.00 7.10 7.20 7.30
Interaction
A: pH
tPA
at D
ay 8
0
52.5
105
157.5
210
22
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Optimizing both Cell Density and Productivity
Selected Outcome Set to Weight
Cells/mL, days 5-6.5 Maximum 3Cells/mL, days 6.5-8 Maximum 3Prod’n of tPA, day8 Maximum 5
Design-Expert® Software
Desirabili ty1
0
X1 = A: pHX2 = C: Glucose
Actual FactorsB: Osmo = 270.01D: Glutamine = 2.80E: Pluronic = 0.84F: Gluc Feed = 4.00G: Glutamate = 3.73H: Aspartate = 0.333
6.90 7.00 7.10 7.20 7.30
2.00
3.00
4.00
5.00
6.00Desirability
A: pH
Glu
cose
at
Star
t (g
/L)
0.458 0.5300.603
0.675
0.748
Prediction 0.819
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SimCell™ at Invitrogen
Purchased model with 4 incubators
1008 chambers possible
24-factor 2-Level factorials possible
Recently installed at Grand Island (GIBCO) site
Currently in OQ phase
PQ and early implementation scheduled for 3rd and 4th quarter
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A
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D
E
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D
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Database and Firewall
DOE design
Hamilton STARplusCompose 100’s of variations of a medium
Next Optimization
Cycle
SimCell™
System
HTP Assays and Data analysis
Occasional scaled-up
verification
General Workflow Plans
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Improved economics for services
Development program: 11 factors - CCD
SimCell Bioreactor Combination plates/shaker w/Bioreactor
Optimized SimCell
Std Project cost
X 7.5X 1.2X ½X
Time 11 weeks 56 weeks 33 weeks 11 weeks
*Cost per data point
$146 $1085 $465 $167
Value per data point High High Low/Med ?
*Not a consumable cost; calculated by dividing the full project cost by number of data points
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Improving media design & manufacturing
Traditional Mixtures Experiment
¼
¼
½
80-100 components
– many replicates at
varying conc.X
Reduce components
Preserve or increase performance
Benefits Reduce COGS
# of weighs/product raw material mgmt, incoming QC
Decrease variability & formulation errors Eliminate redundancies & counter effects
Let’s get smarter around media components:a) Multiple Salt forms* – calcium nitrate + calcium chlorideb) Hydration levels - L-Histidine vs L-Histidine HCl H2Oc) Differing forms of the same amino acid - cysteine vs cystine
*May have opposite effects
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Conclusions
• SimCell system installed at Invitrogen- Currently going through validation- Beta programs with key cell lines underway- Formal service offering in 2007
• Demonstrated ability to perform complex factorial designs
• Developed and validated a fed-batch model using SimCell
• Optimize media, process, and feed simultaneously• Cost models enables high value services at
reasonable prices