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Parallel Integrated Bioreactor Arrays for Bioprocess Development. Harry Lee, Paolo Boccazzi, Rajeev Ram, Anthony Sinskey. Outline. Bioprocesses and bioprocess development Alternative approaches and advantages of microfluidics Parallel Integrated Bioreactor Arrays (PIBA)

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parallel integrated bioreactor arrays for bioprocess development

Parallel Integrated Bioreactor Arrays for Bioprocess Development

Harry Lee, Paolo Boccazzi, Rajeev Ram, Anthony Sinskey

outline
Outline
  • Bioprocesses and bioprocess development
  • Alternative approaches and advantages of microfluidics
  • Parallel Integrated Bioreactor Arrays (PIBA)
  • Preliminary biological validation
  • Applications
  • Next steps
bioprocesses
Bioprocesses
  • Microbial fermentation is used to produce
    • Human insulin, human growth hormone
    • Plasmid DNA vaccine, protein subunit vaccine

Human insulin

E. coli bacteria

Monoclonal antibody

Mammalian cell lines

1000L Bioreactor

  • Mammalian cell culture is used to produce
    • Monoclonal antibodies, Protein therapeutics (ie. erythropoietin)
    • Viruses for vaccines
bioprocess development

Uncontrolled culture conditions

  • Oxygen starvation during sampling
  • Low cell density culture

 Uncertain transfer of results

to larger scale

  • Labor intensive operation
  • Low experimental throughput
Bioprocess development
  • Optimal microbial strains or cell lines must be screened
  • Growth conditions must be empirically optimized
    • pH, temperature, nutrients, O2, induction, etc.

Conventional technology

Experimental Throughput

Process Knowledge

properties of ideal system
Properties of ideal system
  • Controlled growth conditions (pH, DO)
  • High oxygen transfer rate
  • Online optical density and growth rate
  • Parallelism of shake flasks
  • Automation
  • Improved data quality
  • Ease of use

 Potential to predict performance

in large scale bioreactor

conventional approaches
Conventional approaches
  • Miniature stirred tanks, enhanced well plates

 Online cell density measurements not reliable (bubble interference)

 Measurements require sampling

    • Mechanical multiplexing

 minimal labor savings

    • Robotic multiplexing

 Expensive

microfluidic advantage
Microfluidic advantage
  • Microfluidics enables high oxygen transfer rate without bubbles
    • Online optical density measurements
    • Online growth rate estimation
  • Integrated sensors and fluidics
    • Measurements do not perturb the fermentation
    • Minimal mechanical parts
    • Compact, bench scale instrument
piba device module patent pending

Pressure chamber generates positive pressure to drive fluid into channels.

Pressure chamber

Peristaltic Mixing Tubes

Growth well

Growth well

1.5cm

Fluid reservoir

PDMS membrane

pH sensor

Membrane acts as sterile barrier

Acid reservoir

oxygen sensor

Base reservoir

Metering valves to control injected volume

Molded interface gaskets

Metering valves

Molded interface gaskets for ease of use

Injector channel

Filling port

Filling port

PIBA device module (patent pending)

optical density

Integrated optical oxygen and pH sensors. (Fluorescence lifetime)

e coli fermentation in piba

Similar to Stirred Tank

6X

2.4M x 2

3X

No pH

E. Coli fermentation in PIBA

45.7

  • Highest oxygen transfer rate in mbioreactor array
  • First pH and DO controlled mbioreactor array
  • Growth to cell densities (13g-dcw/L) 4X higher than previous mbioreactors
  • Online optical density enabled by bubble free oxygenation

15

30.5

OD 650nm (1cm)

10

Cell density (g-dcw/L)

15.2

5

Similar to Flasks

0

0

7.5

7

pH

6.5

6

120

100

80

DO (% Air Sat)

60

40

20

0

0

1

2

3

4

5

6

7

8

9

Time (h)

unique capability real time od monitoring

3

2.5

Nutrient Limitation

2

1.5

Doubling Time (h)

1

0.5

Lag phase

0

Unique capability: Real time OD monitoring

E. coli growth on LB medium

30

25

20

OD 650nm, 1cm

15

10

5

0

0

1

2

3

4

5

6

7

8

Time (h)

  • Detailed growth kinetics are observable  quantitative study of lag phase
  • Identify nutrient limitations by change in growth rate
    • Screening to high cell density is important to see nutrient limitations
    • Important to isolate cell density dependent phenomena
applications
Applications
  • Standard platform for fermentation and cell culture
    • Standardization allows sharing data, improved data interpretation
    • Standardization was the driver for microfluidics in analytics
  • Bioprocess development
    • Improved process optimization
    • Screening based on higher quality data
      • Production scale conditions, growth rate changes
    • Production bioreactor modeling
      • Inhomogeneities, dynamically changing conditions
value proposition
Value Proposition
  • Improved process screening
    • Screen under production scale conditions
    • Early determination of production process yield
    • Impacts investment decision on $500M - $1B production facility
  • Production reactor modeling
    • Time varying environment
    • High cell density growth
    • Faster manufacturing scale-up
      • One year shorter time to market for a $500M product ~ $30M
next steps
Next Steps
  • Improved understanding of economic model
    • Case-studies
  • Beta prototype development
    • Improved user friendliness  fluidic interfaces
    • Improved manufacturing process  Injection molded layers
  • Deploy Beta to collaborators/customers
  • Rigorous biological validation
    • Rank order of process screen the same in PIBA and bench scale reactor
    • Production reactor modeling
slide14
Team
  • Dr. Paolo Boccazzi
    • Microbial Physiology, Molecular Biology, Bioprocess Development
  • Dr. Harry Lee
    • Electrical Engineering, Microfabrication, System Integration
    • MIT $50K Entrepreneurship Competition Winning team member, 2005
  • Prof. Rajeev J. Ram
    • Electrical Engineering, Optoelectronic devices, Optical Spectroscopy
    • Director, MIT Center for Integrated Photonic Systems
    • Associate Director, Research Laboratory of Electronics
  • Prof. Anthony J. Sinskey
    • Biology, Health Sciences and Technology, Metabolic Engineering
    • Co-Founder: Genzyme, Merrimack Pharmaceuticals, Metabolix