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

B

A

B

A

B

A

B

D

E

A

B

A

B

A

B

A

B

A

B

A

B

A

B

A

B

A

B

A

B

D

E

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