Abstract
This work presents a multilayered model-based approach to scale-up slow and forced convection-based freezing of human induced pluripotent stem cells. The approach combines a hybrid single-cell freezing model (covering the cell and cryovial layers) with a computational fluid dynamics model (covering the freezer layer). The proposed approach can calculate the cell survival rate considering spatial and time-dependent temperature profiles within a freezer unit. The approach was first demonstrated on a single cryovial problem where it was found that the inlet coolant velocity affected the cell survival rate when fast cooling rates were applied. The freezing of 235 cryovials was then studied, where 18 operation conditions consisting of six cooling rates (three constant and non-constant cooling rates, respectively) and three inlet coolant velocities were investigated. The multilayered approach captured the spatial heterogeneity in the cell survival rates for a given inlet coolant velocity and temperature profile.
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