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This paper introduces a rapid automated process-development approach for a continuous capsule-filling process. In our proposed method, both the material attributes and the critical process parameters were varied to understand and to optimize the overall process. Using our approach a statistical process model can be generated with unprecedented speed (2 days), which is the prerequisite for effectively developing and operating continuous process platforms. In a first set of experiments a process model was developed using different mixture compositions of ascorbic acid, lactose and magnesium stearate while changing simultaneously the critical process parameters of the capsule filler (speed, pressure, immersion depth and powder bed height). Targets of the model were the mean fill weight and the relative standard deviation of the produced capsules. In a second experimental set the model was tested, i.e., the goal was to predict the behavior of the system at different set points in order to predict weight and relative standard deviation for predefined targets. Predictions were very good, thus validating our approach. The combination of the rapid automated process development approach and the continuous capsule-filling process resulted in a new strategy for the development and manufacture of pharmaceutical dosage forms.