In the pharmaceutical industry, freeze-drying (also known as lyophilization) is often used to increase the shelf life of heat-sensitive biopharmaceuticals such as protein-based therapeutic drugs and vaccines. The most time- and energy-consuming step of a lyophilization process is primary drying. When a new system configuration (e.g., a new equipment, product formulation, or primary packaging) is to be tested in process development or when transferring to manufacturing facilities, one needs to characterize heat and mass transfer in the new configuration through a battery of experiments that can be very demanding. In this study, we use a model-based design of experiments (MBDoE) to design optimal experiments for fast primary-drying model parameter estimation. We show that MBDoE allows estimating all key heat- and mass-transfer parameters in a statistically meaningful way using one single, optimally designed experiment. Using data from industrial equipment, we test the effectiveness of the methodology on two typical problems to be faced in pharmaceutical process development and transfer: (i) transfer of product manufacturing between two different pieces of equipment and (ii) change of vial type for a given product in a given equipment. Results demonstrate that the proposed methodology can substantially ease the experimentation, thus accelerating the development of freeze-drying operations.