The development of mechanistic models for pharmaceutical processes is of increasing importance due to a noticeable shift toward continuous production in the industry. Sensitivity analysis is a powerful tool during the model building process. A global sensitivity analysis (GSA), exploring sensitivity in a broad parameter space, is performed to detect the most sensitive factors in two models, that is, one for drying of a single granule and one for the drying of a population of granules [using population balance model (PBM)], which was extended by including the gas velocity as extra input compared to our earlier work. beta(2) was found to be the most important factor for the single particle model which is useful information when performing model calibration. For the PBM-model, the granule radius and gas temperature were found to be most sensitive. The former indicates that granulator performance impacts drying behavior, the latter is informative with respect to the variables that primarily need to be controlled during continuous operation. In addition, several GSA techniques are analyzed and compared with respect to the correct conclusion and computational load. (c) 2014 American Institute of Chemical Engineers AIChE J, 60: 1700-1717, 2014