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

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)

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

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

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

Droplet Freezing Time and Spray Thermal Load

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

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)    

Changes in Chamber Temperature Model vs Experiment

Changes in Chamber Temperature Model vs Experiment

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

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.

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.

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: 20% w/v BSA; 50 ml sample

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

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

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