Application of in-line near infrared spectroscopy and multivariate batch modeling for process monitoring in fluid bed granulation

Fluid bed is an important unit operation in pharmaceutical industry for granulation and drying. To improve our understanding of fluid bed granulation, in-line near infrared spectroscopy (NIRS) and novel environmental temperature and RH data logger called a PyroButton (R) were used in conjunction with partial least square (PLS) and principal component analysis (PCA) to develop multivariate statistical process control charts (MSPC). These control charts were constructed using real-time moisture, temperature and humidity data obtained from batch experiments. To demonstrate their application, statistical control charts such as Scores, Distance to model (DModX), and Hotelling's T-2 were used to monitor the batch evolution process during the granulation and subsequent drying phase; moisture levels were predicted using a validated PLS model. Two data loggers were placed one near the bottom of the granulator bowl plenum where air enters the granulator and another inside the granulator in contact with the product in the fluid bed helped to monitor the humidity and temperature levels during the granulation and drying phase. The control charts were used for real time fault analysis, and were tested on normal batches and on three batches which deviated from normal processing conditions. This study demonstrated the use of NIRS and the use of humidity and temperature data loggers in conjunction with multivariate batch modeling as an effective tool in process understanding and fault determining method to effective process control in fluid bed granulation. Copyright (C) 2013. Published by Elsevier B.V.