Résumé : The aim of this study is to propose a strategy to implement a PAT system in the blending step of pharmaceutical production processes. It was examined whether Raman spectroscopy can be used as PAT tool for the in-line and real-time endpoint monitoring and understanding of a powder blending process. A screening design was used to identify and understand the significant effects of two process variables (blending speed and loading of the blender) and of a formulation variable (concentration of active pharmaceutical ingredient (API): diltiazem hydrochloride) upon the required blending time (response variable). Interactions between the variables were investigated as well. A Soft Independent Modelling of Class Analogy (SIMCA) model was developed to determine the homogeneity of the blends in-line and real-time using Raman spectroscopy in combination with a fiber optical immersion probe. One blending experiment was monitored using Raman and NIR spectroscopy simultaneously. This was done to verify whether two independent monitoring tools can confirm each other's endpoint conclusions. The analysis of the experimental design results showed that the measured endpoints were excessively rounded due to the large measurement intervals relative to the first blending times. This resulted in effects and critical effects which cannot be interpreted properly. To be able to study the effects properly, the ratio between the blending times and the measurement intervals should be sufficiently high. In this study, it anyway was demonstrated that Raman spectroscopy is a suitable PAT tool for the endpoint control of a powder blending process. Raman spectroscopy not only allowed in-line and real-time monitoring of the blend homogeneity, but also helped to understand the process better in combination with experimental design. Furthermore, the correctness of the Raman endpoint conclusions was demonstrated for one process by using a second independent endpoint monitoring tool (NIR spectroscopy). Hence, the use of two independent techniques for the control of one response variable not only means a mutual confirmation of both methods, but also provides a higher certainty in the determined endpoint.