Assessment of Prediction Models for Punch Sticking in Tablet Formulations

Assessment of Prediction Models for Punch Sticking in Tablet Formulations

Blog Article

Punch sticking is a common tablet compression manufacturing issue experienced during late-stage large-scale manufacturing.Prediction of punch sticking propensity and identification of the sticking component is important for early-stage formulation development.Application of novel predictive capabilities offers early-stage sticking propensity assessment.

16 API compounds were utilised to assess punch sticking color touch 7/97 prediction using removable punch tip tooling.API descriptors were tested for sticking correlation using multivariate analysis.NIR imaging, SEM-EDX and Raman microscopy were used to examine the material adhered to the punch tips.

Predictive modelling using linear and non-linear equations proved inaccurate in punch sticking mass prediction.PCA analysis identified gotrax handlebar sticking correlated physical descriptors and provided a dataset and method for further descriptor studies.Raman microscopy was identified as a suitable technique for chemical identification of punch sticking material, which offers insight towards a mechanistic understanding.