Detection of Nucleation during Cooling Crystallization through Moving Window PCA Applied to in Situ Infrared Data

The method here proposed based on the moving window principal component analysis can be employed in time-varying processes tracked through in situ spectroscopy. In the case under investigation, it aimed to detect the nucleation during crystallization processes. For this purpose, statistical indexes were employed, and the contribution plot helped identifying the spectral variables that were changing due to nucleation. Isonicotinamide was here considered as a model active pharmaceutical ingredient, and its cooling crystallization was monitored by means of in situ infrared spectroscopy. The procedure allowed to overcome issues that may be encountered with static principal component analysis, since it could distinguish the slow-varying changes due to external perturbations (temperature) from abnormal events such as the sudden concentration decrease related to the crystallization. The proposed method was demonstrated to correctly detect nucleation without any a priori knowledge of the peaks involved in the process, leading the false alarm rate from 77.38% (obtained with the static principal component analysis) to 6.9%.