Abstract
Transplantation brings hope for many patients. A multidisciplinary approach on this field aims at creating biologically functional tissues to be used as implants and prostheses. The freeze-drying process allows the fundamental properties of these materials to be preserved, making future manipulation and storage easier. Optimizing a freeze-drying cycle is of great importance since it aims at reducing process costs while increasing product quality of this time-and-energy-consuming process. Mathematical modeling comes as a tool to help a better understanding of the process variables behavior and consequently it helps optimization studies. Freeze-drying microscopy is a technique usually applied to determine critical temperatures of liquid formulations. It has been used in this work to determine the sublimation rates of a biological tissue freeze-drying. The sublimation rates were measured from the speed of the moving interface between the dried and the frozen layer under 21.33, 42.66 and 63.99 Pa. The studied variables were used in a theoretical model to simulate various temperature profiles of the freeze-drying process. Good agreement between the experimental and the simulated results was found.
Highlights
Freeze-drying is a gentle drying method widely used for sensitive products such as biopharmaceuticalsC
Mathematical modeling enhances the understanding of the freeze-drying process and becomes an effective manner of studying its optimization
Heat and mass transfer models for the freeze-drying process have been developed by a number of researchers and these are presented in scientific literature (Sadikoglu, Liapis, 1997; Sheehan, Liapis, 1998; George, Datta, 2002)
Summary
Freeze-drying is a gentle drying method widely used for sensitive products such as biopharmaceuticals. Optimization studies of the freeze-drying process have been performed by some researchers (Chakraborty et al, 2011; Chouvenc et al, 2004; Grant, Matehtschuk, Dalby, 2009). Mathematical modeling enhances the understanding of the freeze-drying process and becomes an effective manner of studying its optimization. A computer simulation run on these models is used to analyze drying rates and to predict the surface temperature profile (Liapis, Litchfield, 1979; Millman, Liapis, Marchello, 1985; Pisano, Fissore, Barresi, 2011). Heat and mass transfer models for the freeze-drying process have been developed by a number of researchers and these are presented in scientific literature (Sadikoglu, Liapis, 1997; Sheehan, Liapis, 1998; George, Datta, 2002)
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