1. Heat and Mass Transfer in Spray Freeze-Drying
Alina A. Alexeenko
School of Aeronautics & Astronautics, Purdue University
In collaboration with
Israel Sebastiao, Purdue University
Dr Tom Robinson, Aerosol Theurapeutics
CPPR 2016: Freeze Drying of Pharmaceuticals & Biologicals Conference

2. Heat Transfer in Freeze-Drying
Advantages:
Established, validated aseptic processes and equipment
Simple process models
Challenges:
Heat transfer is highly inefficient:
Fluid and shelves have high thermal inertia
Low pressures:
Viscous losses
Sensing is difficult/expensive
Open loop controls
Container presents heat and mass transfer barrier
qcontact
qrad
qgas
Contact: qcontact=f(Tshelf,Tprod,vial)
Radiation: qrad=f(Tshelf,Tprod,Twall)
Gas: qgas=qcond + qconv
Gas convection: qconv=f(pch,Tprod, Twall)

3. Spray Freeze-Drying Packed Bed Agitated/ Fluidized Bed
Dried Porous
Material
Frozen core
Agitated/
Fluidized Bed
Typically low pressures
Primarily radiative heat transfer
Atmospheric and above pressures
Primarily convective heat transfer

4. Atmospheric Spray Freeze-Drying
Solvent outlet N2
Product Solution inlet
Spray
Porous
transport

5. Atmospheric Spray Freeze-Drying
Three main processes that comprise a typical ASFD cycle:
Spray atomization
Heat transfer within the chamber and
Drying

6. Droplet Freezing Time and Spray Thermal Load

7. Droplet Freezing Time and Spray Thermal Load
Very fast freezing: freezing time is less than a second!

8. Chamber Heat Transfer
Because heat transfer is such an important part of the ASFD process, a model was developed to predict the time evolution of the temperature of the chamber gas.
Drying Gas Temperature Model (Tmodel)

9. Changes in Chamber Temperature
Model vs Experiment

10. Changes in Chamber Temperature
Model vs Experiment

11. Gas flow (N2): Tin=180 K p0-in=15.5 psig pout= 0 psig Porous Tube:
Changes in Chamber Temperature
ANSYS Fluent 13 CFD simulations using actual dimensions to assess pressure, temperature, and velocity gradients inside the chamber at maximum flow rate.
Porous tube
Filter
Gas flow (N2):
Tin=180 K
p0-in=15.5 psig
pout= 0 psig
Porous Tube:
40 media grade
Filter:
20 media grade
Adiabatic Walls

12. Changes in Chamber Temperature
ANSYS Fluent 13 CFD simulations using actual dimensions to assess pressure, temperature, and velocity gradients inside the chamber at maximum flow rate.

13. Estimation of Drying Time
Mass and energy conservation equations are employed to describe the evolution of the powder moisture content. These equations are combined with data from ASFD runs to obtain a temperature-dependent correlation to estimate the drying time.
In the following slides, Datasets 1-2 are runs with 10% BSA solutions whereas Dataset 3 is a run with 20% BSA.

14. ASFD: Drying Time Dataset 1 & 2: 10% w/v BSA; 50 ml sample
Exponential
Curve Fit
Linear
Dataset 1 & 2: 10% w/v BSA; 50 ml sample
Dataset 3: % w/v BSA; 50 ml sample

15. ASFD: Drying Time Dataset 1 & 2: 10% w/v BSA; 50 ml sample
~10min
Comparable BSA freeze-drying: 10 – 20 hours of primary drying

16. Low-Pressure Spray Freeze-Drying
Even faster drying rates for suspended particles due to radiant heating
Complex heat and mass transfer:
Very rarefied flow around particles – free molecular flow around particle!
Additional forces, e.g. thermophoretic may induce particle motion
Thermophoresis movie

17. Summary
Extremely fast drying (< 1 sec!) is possible for typical spray freeze-drying and is expected to be beneficial for protein stability
Drying times could be lower by about an order of magnitude than for typical freeeze-drying
Fast response time due to lower viscosity working fluid – LN2 vapor vs silicone oil liquids is beneficial for closed-loop control
Development of simple process models is a major need for adopting spray freeze-drying in bio/pharmaceutical manufacturing.
THANK YOU!!
CPPR 2012