Mammalian Cell CultureSensors and Models

Mammalian Cell CultureSensors and Models

Trish Benton Michael Boudreau

PresentersPresenters

Trish Benton

Michael Boudreau

483? That means big

trouble

483? That means big

trouble

LandscapeLandscape

New at-line and inline sensors

Concentration Control

ModelingData Analytics

SensorsSensors

At –line Nova, HPLC

In-line Fogale, Aspectrics, Optek, CO2, differential pressure

On-line viable cell densityOn-line viable cell density

In and induced electrical field, an intact cell membranes is a physical barrier to ion migration.

Capacitance measured in picoFarads plotted against the frequency of change of an electrical field, measured in MHz, gives a beta-dispersion spectrum.

Beta Dispersion SpectraBeta Dispersion Spectra

Fogale uses Entire Dielectric SpectrumFogale uses Entire Dielectric Spectrum

Older analyzers measured capacitance at only one frequency.

Newer analyzers use a non-linear least squares fit of random measurements to generate the whole spectrum.

Concentration range: 0 -109 cell/ml for animal cells0 - 200 g/l dry weight for yeast and bacteria

Resolution: 0.01 - 106 cell/ml for animal cells0.02 g/l dry weight for yeast

T3V1 Cell Density

0

5

10

15

20

25

30

Viable Density Capacitance

T1V1 Cell Density

0

5

10

15

20

25

30

35

40

Viable Density Capacitance

Automated Multifunction AnalyzersAutomated Multifunction Analyzers

A robotic combination of enzymatic, amperometric, potentiometric and Coulter counter or CCD camera analyzers.

They can measure:– Sugar and amino acid substrates– Metabolic byproducts– Dissolved Oxygen and Dissolved Carbon Dioxide– pH– Cell Density and viability– Sodium, potassium, calcium, phosphate – “Gold Standard” freezing point test for osmolality.

AutosamplersAutosamplers

Autoclavable, multipoint auto-samplers enable multifunction analyzers to make at-line measurements.

Small sample size allow more frequent analysis. A 5L cell culture bioreactor can be sampled once every 4 hours.

Encoded Photometric Infrared SpectroscopyEncoded Photometric Infrared Spectroscopy

Encoded Photometric infrared analyzers can detect the constituents of multiple frequencies simultaneously

EP IR analyzer is a non-dispersive measurement where the radiation beam is dispersed according to wavelength after it has

passed through a sample

Chemometric analysis is off-line.

EP IR Measurement in Cell CultureEP IR Measurement in Cell Culture

A single analysis function can measure:– Glucose– Glutamine– Glutamate– Proline– Lactic Acid– Ammonia– Dissolved Carbon Dioxide

Concentration ControlConcentration Control

Glucose in high concentration attaches non-specifically to amino acids.

The quality and possibly the quantity of protein product can be increased by maintaining glucose concentration in a bioreactor at physiological levels of about 1 g/L.

Manual Glucose AdditionManual Glucose Addition

Typically glucose is added once a day throughout a cell culture run.

The result is a saw-tooth glucose concentration profile that ranges from 3 g/L to near 0 g/L.

Glucose Addition under Feedback ControlGlucose Addition under Feedback Control

Multifunction analyzers can be used in a feed back loop if the sample time is 25% of the dominant system response time.

In line analyzers, like Fogale viability and EP IR perform analysis on each sample within minutes. Their results can be used in most liquid concentration loops.

Benchtop Bioreactor with SensorsBenchtop Bioreactor with Sensors

Place picture of bioreactor with sensors here

Tuning of Concentration LoopsTuning of Concentration Loops

New concentration

Loops are usually

Integrators.

InSight Learning and

Adaptive Tuning

can identify these

Integrators on in-line

analyzers.

Bio-Process Modeling in Process Development

Bio-Process Modeling in Process Development

High fidelity modeling can help determine the impact of operating conditions on yield and product quality.

Bioprocess Modeling and ControlBioprocess Modeling and Control

Chapter 6 of the book “New Directions in Bioprocess Modeling and Control: Maximizing Process Analytical Technology Benefits” describes in detail how to build a model in DeltaV.

Sequential Modular SimulationSequential Modular Simulation

PumpSimulation

ValveSimulation

ReactorSimulation

Flow measurement

Simulated Properties Flow Temperature Pressure Etc.

Pressuremeasurement Temperature Measurement

Process simulation blocks

Sequential Modular Simulation on DeltaV

Sequential Modular Simulation on DeltaV

jii

i

jii

ji

KX

X

KX

K

jir 21

1

Michaelis-Menten

Rate of synthesis of i by j

Bioreactor Simulation on BioNet Control System

Bioreactor Simulation on BioNet Control System

Add picture of simulation here

Bioreactor Control System with Concentration Loops

Bioreactor Control System with Concentration Loops

Place bionet main view here

On-line Adaptation of SimulationOn-line Adaptation of Simulation

Actual Plant

Virtual Plant

Online KPI:Yield and Capacity

Inferential Measurements:

Biomass Growth and Production Rates

Adaptation

Key Actual Process VariablesKey Virtual

Process Variables

Model Parameters

Error between virtual and actual process variables

are minimized by correction of model parameters

Actual BatchProfiles

Process Analytical Technology in Process DevelopmentProcess Analytical Technology in Process Development

Dynamic Time Warping allows comparison of matched bioreactors when they progress at different rates.

PCA can weed out unimportant process parameters quickly.

Batches Not AlignedBatches Not Aligned

0

5

10

15

20

25

30

35

40

1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115

Batches Aligned with DTWBatches Aligned with DTW

0

5

10

15

20

25

30

35

40

1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115

PAT Online in Process DevelopmentPAT Online in Process Development Media comparisons Tech Transfers

ReferencesReferences 1. Kleman G.L.,Chalmers J. J., Luli G W, Strohl W R, A Predictive and

Feedback Control Algorithm Maintains a Constant Glucose Concentration in Fed-Batch Fermentations, APPLIED AND ENVIRONMENTAL MICROBIOLOGY, Apr. 1991, p. 910-917

2. Luan Y T, Mutharasan R, Magee W E, Effect of various Glucose/Glutamine Ratios on Hybridoma Growth, Viability and Monoclonal Antibody Formation, Biotechnology Letters Vol 9 No 8 535-538 (1987)

3. McMillan G, Benton T, Zhang Y, Boudreau M, PAT Tools for Accelerated Process Development and Improvement, BioProcess International Supplement MARCH 2008.

4. Boudreau M A, McMillan G K, New Directions in bioprocess Modeling and Control. ISA. Research Triangle Park, NC 2006.

5. Lee J M, Yoo C K, Lee I B, Enhanced process monitoring of fed-batch penicillin cultivation using time-varying and multivariate statistical analysis. Journal of Biotechnology, 110 (2004) 119-136.

6. Cinar A, Parulekar S J, Ündey C, Birol G, Batch Fermentation Modeling, Monitoring, and Control. Marcel Dekker, Inc. New York, NY 2003.

About the PresentersAbout the Presenters

Michael Boudreau is a Principal Consultant at Emerson Process Management.

Trish Benton is a Life Sciences Consultant at Broadley-James Corporation.