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SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio
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Page 1: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

SIMULATION OF A BIOREACTOR

Tiffany TarrantTodd Giorgio

Page 2: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

What is a Bioreactor?

• Experimental device used to culture cells

• Provides nutrient media, oxygen support, fluid environment, area to grow

• Used both in laboratories and in industry-- specifically used in the lab portion of the BME 281: Biotechnology class

Page 3: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

BME 281: Biotechnology

• Course goal: to integrate cellular and molecular biology with process bioengineering to describe the manufacture of products derived from mammalian cells

Page 4: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

Why Simulate?

• based on initial lab results

• quicker, more efficient, and less expensive

Page 5: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

Experimental Time Comparison

• Laboratory• 22 days to prepare

cells for bioreactor• 5 days to obtain a significant amount of

growth

• TOTAL: 27 days

• Simulation• approximately 1

minute to enter experimental

data and get results

• TOTAL: 1 minute

Page 6: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

Typical Cell Culture

Page 7: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

• HeLa--common in research labs• ECV304--endothelial cells• 293--used in BME 282 lab

• can be distinguished based on specific growth constants & the extent to which they are affected by local environmental limitations

Cell Types

Page 8: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

Past Work

• Modeled simple exponential growth based only on cell-specific growth constant

• Accounted for oxygen delivery limitation

• Introduced different impeller types

Page 9: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

Simple Exponential Growth

• unlimited growth

• cell types distinguished based on k

Cell Growth

0

2000

4000

6000

8000

10000

12000

0 50 100 150 200 250 300

time (hours)

cell

conc

entra

tion

(cells

/ml)

HeLa

ECV304

293

Page 10: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

Oxygen Limitation Effects

Cell Growth

0

10

20

30

40

50

60

70

0 100 200 300 400

time (hours)

con

cen

trat

ion

(c

ells

*10^

5/m

l)

HeLa

ECV304

293

Page 11: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

Impeller

• different types influencing the amount of power that is delivered to the bioreactor system

• increases oxygen dispersal throughout the system, thereby increasing delivery

• forces imposed on cells due to stirring causes mechanical damage and cell death

Page 12: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

Impeller Types

Rushton turbine Rushton turbine PaddlePaddle Marine PropellerMarine Propeller

Anchor Anchor Helical ribbon Helical ribbon

Page 13: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

Current Work

• Incorporation of impeller effects on growth

• Integration of ISF to balance oxygen delivery capabilities with cell death due to mechanical damage

• Validation of model with actual lab results

• Literature search to investigate other cell culture models

Page 14: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

Impeller Effects

Impeller Effects

0

200000

400000

600000

800000

1000000

1200000

1400000

0 100 200 300 400

time (hours)

cell

co

nce

ntr

atio

n

(cel

ls/m

l) Rushton Turbine

Paddle

Marine Propeller

Page 15: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

Integrated Shear Factor

Growth vs. ISF

-20

0

20

40

60

80

100

120

0 10 20 30 40

ISF

relat

ive g

rowt

h (%

)

growth

• Cell growth under different shear conditions can be correlated to an ISF factor

Page 16: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

Stirring Speed Effects via ISF

• ISF related to speed

of impeller and its distance from the walls of the

bioreactor

Stirring Speed Effects

-50000

0

50000

100000

150000

200000

250000

300000

0 24 48 72 96 120 144 168 192

time (hours)

cell c

once

ntrati

on

(cells

/ml)

100 rpm

250 rpm

300 rpm

350 rpm

400 rpm

600 rpm

Page 17: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

Experimental Comparisons

• Given a time lag, model correlates with BME 282 data

Model Data: Lab 293 Cells

0

200000

400000

600000

800000

1000000

1200000

0 24 48 72 96 120 144 168 192

time (hours)

cell c

once

ntrat

ion (c

ells/m

l) Model

Lab Data

Page 18: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

Other Models

• No other model attempted to integrate several interrelated factors that affect cell growth

• Instead, focused on one parameter or determining event

• None incorporated oxygen delivery limitations

Page 19: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

Program Flowchart

V O L U M E(in p u t ra d iu s & f lu id h e ig h t)

C A L C _ IN IT(in p u t in it ia l co n c .)

P W R N U M _ F U N C(in p u t im p e lle r typ e)

D A M A G E(in p u t im p e lle r sp e e d)

ca lcu la te s IS F

IM P E L L E Rca lcu la tes p ow e r & kLa

O X Y G E Nd e term ine s O 2 s ta te

M A IN(in p u t ce ll typ e)

Page 20: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

Parameter Effects on GrowthCell Type Rate of exponential

growth (+)Bioreactor Radius Culture volume (+)

oxygen delivery (-)Impeller Diameter(+)

Impeller Diameter Power delivered tocells (+) & k(-)

ISF-how many cellssurvive damage (-)

Fluid Height Culture volume (+) Oxygen delivery (-)& k (-)

Concentration @each time point

When oxygenbecomes limiting(+/-)

Impeller type Power delivered tocells (+)

Deliverycapabilities (+)

Impeller Speed ISF & powerdelivered to cells(+/-)

Oxygen deliverycapabilities (+)

Page 21: SIMULATION OF A BIOREACTOR Tiffany Tarrant Todd Giorgio.

Future Work

• 1. Slight alterations to the program to make it more user-friendly

• 2. Specific documentation of program procedure and functions