Maintaining chemical and physical stability of the product during freeze-drying is\nimportant but challenging. In addition, freeze-drying is typically associated with long process\ntimes. Therefore, mechanistic models have been developed to maximize drying efficiency without\naltering the chemical or physical stability of the product. Dried product mass transfer resistance (Rp)\nis a critical input for these mechanistic models. Currently available techniques to determine Rp only\nprovide an estimation of the mean Rp and do not allow measuring and determining essential local (i.e.,\nintra-vial) Rp differences. In this study, we present an analytical method, based on four-dimensional\nmicro-computed tomography (4D-microCT), which enables the possibility to determine intra-vial Rp\ndifferences. Subsequently, these obtained Rp values are used in a mechanistic model to predict the\ndrying time distribution of a spin-frozen vial. Finally, this predicted primary drying time distribution\nis experimentally verified via thermal imaging during drying. It was further found during this\nstudy that 4DmicroCT uniquely allows measuring and determining other essential freeze-drying process\nparameters such as the moving direction(s) of the sublimation front and frozen product layer thickness,\nwhich allows gaining accurate process knowledge. To conclude, the study reveals that the variation\nin the end of primary drying time of a single vial could be predicted accurately using 4D-microCT as\nsimilar results were found during the verification using thermal imaging.
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