A study on the applicability of multiple process analysers in the production of coated pellets.

Process analytical technology (PAT) has become an important factor in design, analysis and control of complex technological processes. In the present study, pellet coating process was monitored using four different PAT approaches, i.e. near-infrared (NIR) spectroscopy, Raman spectroscopy, in-line image analysis, and spatial filtering technique (SFT). Robustness and accuracy of a novel in-line image analyser was studied during the active ingredient coating process on the pilot scale in the first part of the study. In the second part, multivariate model for in-line monitoring of critical quality attributes, such as moisture content and coating thickness, was calibrated with off-line NIR measurements of laboratory scale samples. The quality of the model was evaluated during the pilot scale batches. In the last part of the study, applicability of two different Raman process analysers for real time moisture content and coating quantity determination was investigated extensively. In addition, Raman spectral data was correlated with the in-line SFT measurements. The results and their interpretations present novel aspects of multiple process analysing techniques, which could help improve pellet coating process monitoring and control. Moreover, presented multivariate model calibration approaches could significantly reduce time, costs, and effort needed to implement PAT into the pharmaceutical industry.