Post on 24-Mar-2020
transcript
Developing smart control strategies for
freeze-drying of lactic acid bacteria
EFFoST Annual Meeting, 20-23 November 2012, Montpellier, France
1
(1) Joint Research Unit of Microbiology and Food Process Engineering
AgroParisTech, INRA, Thiverval-Grignon, France
Stéphanie Passot (1), Ioan Cristian Tréléa (1) Miquel Galan (2)
(2) R&D Process and Application Development Manager
Telstar Technologies, S.L., Terrassa, Spain
BackgroundBackgroundProduction of freeze-dried concentrates of lactic acid
= a complex process
Fermentation
Cooling
Concentration
PAT“Operations that monitor, analyze
and control critical quality attributes of processes and
2
Functionality: acidification activity
(CinAc®)
Formulation
Freeze-dryingFreezing
Sublimation
Desoprtion
Storage
attributes of processes and products, while manufacturing is in progress, i.e. continuous quality
verification”
BackgroundBackgroundProduction of freeze-dried concentrates of lactic acid
= a complex process
Fermentation
Cooling
Concentration
A pluridisciplinary team
Process understanding
Experimental and modeling study
Development of new sensing
3
Formulation
Freeze-dryingFreezing
Sublimation
Desoprtion
Storage
Development of new sensing
technologies
Implementation of monitoring &
control tools on the pilot plants
Demonstration on the final end-
user (cheese)
Bacteria Freeze-Drying: The approachBacteria Freeze-Drying: The approach
LAB concentrate
Protective medium:
(200 g/L sucrose)
Freezing (tray)
Primary dryingSecondary drying
Product
3 Process variables3 Process variables
� Shelf temperature
� Chamber pressure
Critical Quality attributesCritical Quality attributes
�Acidification activity
� Structure of the cake
Raw material attributesRaw material attributes
� Physical properties
Storage
4
� Time� Structure of the cake
� Storage stabilityPAT PAT
Bacteria Freeze-Drying: The approachBacteria Freeze-Drying: The approach
LAB concentrate
Protective medium:
(200 g/L sucrose)
Freezing (tray)
Primary dryingSecondary drying
Product
3 Process variables3 Process variables
� Shelf temperature
� Chamber pressure
Critical Quality attributesCritical Quality attributes
�Acidification activity
� Structure of the cake
Raw material attributesRaw material attributes
� Physical properties
Storage
5
� Time� Structure of the cake
� Storage stability
Critical Process ParametersCritical Process Parameters
� Product temperature
� Water activity, moisture content
� End point of drying steps
Quantitative Relationship
Sensing method
Measure or Predict in real
time the CPP
Modeling & advanced
optimization tools
Fermentation
Cooling
Concentration
Formulation
Relationships between CPP and bacteria qualityRelationships between CPP and bacteria quality
� Study the whole process
� Quantify the biological degradation after each
step of the freeze-drying process
�Impact of the sublimation conditions
6
Formulation
Freeze-dryingFreezing
Sublimation
Desoprtion
Storage
�Impact of the sublimation conditions
� Impact of the residual moisture content
ON
� The bacteria acidification activity
� Storage stability
Functionality: acidification activity
(CinAc®)
1- Viability � Plate counts
2- Technological property: Acidification activity � CINAC
6
7
-6
0
dpH/dt, pHu.min-1
Samples analysisSamples analysis
7
The higher the tm value, the lower the acidification activity
Corrieu et al. 1988 (Patent FR 2629612)
4
5
0 200 400 600
Time (minutes)
pH
-24
-18
-12
103 dpH/dt, pHu.min
tm
3- Residual moisture content: Karl Fisher titration, water activity, Tg
Fermentation
Cooling
Concentration
Shelf T°
Chamber pressure-60
-40
-20
0
20
40
0 20 40
Time (h)
Temperature (°C
)0
20
40
60
80
100
Pressure (Pa)
-60
-40
-20
0
20
40
0 20 40
Time (h)
Temperature (°C
)
0
20
40
60
80
100
Pressure (Pa)
Conservative Aggressive
Pilot plant
(Usifroid, SMH 15)
Freeze-drying protocol
Shelf T°
Chamber P
Relationships between CPP and bacteria activityRelationships between CPP and bacteria activity
8
Formulation
Freeze-dryingFreezing
Sublimation
Desoprtion
Storage
Freezing
DesorptionSublimation
(Usifroid, SMH 15)
� Pilot plant equipped with a sample thief and a hygrometer
Effect of water content on the acidification activityEffect of water content on the acidification activity
Analysis of samples removed at various times of the desorption step
320
340
Conservative
Aggressivet = 25 hr
Low activity
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240
260
280
300
0 2 4 6 8
Water content (%)
tm (min)
t = 0
t = 6 hr
Desorption Sublimation
High activity
Effect of water content on storage stabilityEffect of water content on storage stability
8
12
16
20
k (min/day)
Old data
Conservative
AggressiveTg = 25 °C
Optimal range of water content for bacteria stability
10
0
4
8
0 2 4 6 8
Water content (%)
k (min/day)
Slope k = loss rate of acidification activity
Tcoll: the minimum temperature at which the ice sublimation is
accompanied with the collapse of the dried structure
Frozen region
Su
blim
ati
on
fro
nt
Collapse-7°C
Freeze-drying microscopy:
(FDCS 196, Linkam Sci. Inst.)
Direct observation of the structure during
primary drying (sublimation)
Properties of the raw materialProperties of the raw material
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Tcoll = -7°°°°C ≈ Tg’� Maltodextrin DE 5-8: 10% solution
Dried regionSu
blim
ati
on
fro
nt
-10°C
-7°C
-9°C
BUT for bacteria suspension Tcoll = -27°°°°C >> Tg’ = -36°°°°C
Formulations with low value of Tg’ and Tcoll >> Tg’
� Performing primary drying at product temperature higher than Tg’
0
Temperature (°C
)
Shelf T°
Tg
0
Temperature (°C
)
Shelf T°
Product T°°°° close to Tg’ Product T°°°° close to Tcoll
0
Temperature (°C
)
Shelf T°
Tg
0
Temperature (°C
)
Shelf T°
Tg
0
Temperature (°C
)
Shelf T°
0
Temperature (°C
)
Shelf T°
Product T°°°° close to Tg’ Product T°°°° close to Tcoll
Relationships between CPP and bacteria activityRelationships between CPP and bacteria activity
12
Differences in biological activity recovery after freeze-drying ?
Probably Yes
-60
-40
-20
0 10 20 30Time (h)
Temperature (°C
)
Tcoll
-60
-40
-20
0 10 20 30Time (h)
Temperature (°C
)
Shelf T°Tcoll
Tg
OR ??
-60
-40
-20
0 10 20 30Time (h)
Temperature (°C
)
Tcoll
-60
-40
-20
0 10 20 30Time (h)
Temperature (°C
)
Tcoll
-60
-40
-20
0 10 20 30Time (h)
Temperature (°C
)
Shelf T°Tcoll
Tg
-60
-40
-20
0 10 20 30Time (h)
Temperature (°C
)
Shelf T°Tcoll
Tg
OR ??
Some experimental results
Primary drying (DI) -20°C/20 Pa 0°C/20 Pa
tm1 before FD 261 min 240 min
tm2 after FD 475 min 366 min
dtm=tm2-tm1 214 min 126 min
Loss of biological activity during FD
Close to Tg’ Close to Tcoll-10
0
10
Temperature (°C
)
0°°°°C / 20 Pa
-20°°°°C / 20 Pa-10
0
10
Temperature (°C
)
0°°°°C / 20 Pa
-20°°°°C / 20 PaClose to Tg’
Close to Tcoll
Relationships between CPP and bacteria activityRelationships between CPP and bacteria activity
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Loss of biological activity during storage
FD: freeze-drying
-50
-40
-30
-20
0 5 10 15 20 25
Time (hr)
Temperature (°C
)
Tg’
Tcoll
-50
-40
-30
-20
0 5 10 15 20 25
Time (hr)
Temperature (°C
)
Tg’
Tcoll
Close to Tg’
200
400
600
800
0 20 40 60 80 100
Storage time (days)
tm (min)
-20°C/20 Pa 0°C/20 Pa
k=2.8
k=2.1
Hypothesis: Degradation rate K = f (Product T°-Tg)
Freeze-dried samples of LAB
Equilibration at various
Kdt
dtm=
0
400
800
1200
1600
2000
tm (min)
aw = 0.73
aw = 0.33
aw = 0.09
K
Can we integrate in the model the degradation of “biological activity”?
Relationships between CPP and bacteria activityRelationships between CPP and bacteria activity
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Equilibration at various
water activity values
Storage at 25°°°°C under vacuum
Measurement of biological
activity at 7, 10 and 29 days
k0=3.89
k1 = 0.032
( )TgTk storagee−
= 1
0kK
0
20
40
60
-50 0 50 100
Tstorage - Tg (°C)
K (min/day)
0
0 10 20 30
Storage time (days)
aw = 0.09
Integration of the equations describing the
degradation rate in the lyo-model
Simulation of the evolution of tm during
the process
-40
-20
0
20
0 10 20 30
Time (h)
Temperature (°C
) Close to Tg’
DI = -20°°°°C, 20 Pa
80
Loss of acidfication activity (min)
19 min
Relationships between CPP and bacteria activityRelationships between CPP and bacteria activity
15DI: Primary drying
Time (h)
-40
-20
0
20
0 10 20 30
Time (h)
Temperature (°C
) Close to Tcoll
DI = 0°°°°C, 20 Pa
0
20
40
60
0 1 2 3 4 5 6
Thickness of dry layer (mm)
Loss of acidfication activity (min)
Close to Tg’
Close to Tcoll
19 min
Bacteria Freeze-Drying: The approachBacteria Freeze-Drying: The approach
LAB concentrate
Protective medium:
(200 g/L sucrose)
Freezing (tray)
Primary dryingSecondary drying
Product
3 Process variables3 Process variables
� Shelf temperature
� Chamber pressure
Critical Quality attributesCritical Quality attributes
�Acidification activity
� Structure of the cake
Raw material attributesRaw material attributes
� Physical properties
Storage
16
� Time� Structure of the cake
� Storage stability
Critical Process ParametersCritical Process Parameters
� Product temperature
� Water activity, moisture content
� End point of drying steps
Quantitative Relationship
Sensing method
Measure or Predict in real
time the CPP
Modeling & advanced
optimization tools
Chamber
Vacuum
Ice
Condenser
Mass transfer Heat transfer
Modelling and optimization toolModelling and optimization tool
A one-dimensional model of heat and mass transfer
17
Dry product
Vial bottom
Tray
Frozen
product
Dry product
Vial wall
Vacuum
Shelf
Product top
Sublimation front
Product bottom
Shelf
Product top
Sublimation front
Vacuum
Sensor
Parameter estimation using a specific tool developed by IIM-CSIC
Modelling and optimization toolsModelling and optimization tools
18www.iim.csic.es/~amigo
Modelling and optimization toolsModelling and optimization tools
Experimental description
� Six experiments
(Primary drying)
Estimation of parameters of the freeze-drying model
Mass transfer Heat transfer
19www.iim.csic.es/~amigo
(Primary drying)
� Product temperature, vapor
pressure
� No replica: experimental
errors were fixed at 10%
Bacteria Freeze-Drying: The approachBacteria Freeze-Drying: The approach
LAB concentrate
Protective medium:
(200 g/L sucrose)
Freezing (tray)
Primary dryingSecondary drying
Product
3 Process variables3 Process variables
� Shelf temperature
� Chamber pressure
Critical Quality attributesCritical Quality attributes
�Acidification activity
� Structure of the cake
Raw material attributesRaw material attributes
� Physical properties
Storage
20
� Time� Structure of the cake
� Storage stability
Critical Process ParametersCritical Process Parameters
� Product temperature
� Water activity, moisture content
� End point of drying steps
Quantitative Relationship
Sensing method
Measure or Predict in real
time the CPP
Modeling & advanced
optimization tools
To measure or predict in real time the critical process parameters or product quality
Development of sensing methodsDevelopment of sensing methods
Common sensors
� Product temperature probe
� Vapor pressure
� Pressure rise test
Electronic nose
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New sensors
� Electronic nose
� Acoustic impedance probe
Water activity Acidification activity
To measure or predict in real time the critical process parameters or product quality
Development of sensing methodsDevelopment of sensing methods
Common sensors
� Product temperature probe
� Vapor pressure
� Pressure rise test
Acoustic impedance probe
22
New sensors
� Electronic nose
� Acoustic impedance probe
To measure or predict in real time the critical process parameters or product quality
Development of sensing methodsDevelopment of sensing methods
Common sensors
� Product temperature probe
� Vapor pressure
� Pressure rise test
Acoustic impedance probe
23
New sensors
� Electronic nose
� Acoustic impedance probe
Bacteria Freeze-Drying: The approachBacteria Freeze-Drying: The approach
LAB concentrate
Protective medium:
(200 g/L sucrose)
Freezing (tray)
Primary dryingSecondary drying
Product
3 Process variables3 Process variables
� Shelf temperature
� Chamber pressure
Critical Quality attributesCritical Quality attributes
�Acidification activity
� Structure of the cake
Raw material attributesRaw material attributes
� Physical properties
Storage
24
� Time� Structure of the cake
� Storage stability
Critical Process ParametersCritical Process Parameters
� Product temperature
� Water activity, moisture content
� End point of drying steps
Quantitative Relationship
Sensing method
Measure or Predict in real
time the CPP
Modeling & advanced
optimization tools