Process analytical technology (PAT) approach to the formulation of thermosensitive protein-loaded pellets: Multi-point monitoring of temperature in a high-shear pelletization.

In the literature there are some publications about the effect of impeller and chopper speeds on product parameters. However, there is no information about the effect of temperature. Therefore our main aim was the investigation of elevated temperature and temperature distribution during pelletization in a high shear granulator according to process analytical technology. During our experimental work, pellets containing pepsin were formulated with a high-shear granulator. A specially designed chamber (Opulus Ltd.) was used for pelletization. This chamber contained four PyroButton-TH® sensors built in the wall and three PyroDiff® sensors 1, 2 and 3cm from the wall. The sensors were located in three different heights. The impeller and chopper speeds were set on the basis of 32factorial design. The temperature was measured continuously in 7 different points during pelletization and the results were compared with the temperature values measured by the thermal sensor of the high-shear granulator. The optimization parameters were enzyme activity, average size, breaking hardness, surface free energy and aspect ratio. One of the novelties was the application of the specially designed chamber (Opulus Ltd.) for monitoring the temperature continuously in 7 different points during high-shear granulation. The other novelty of this study was the evaluation of the effect of temperature on the properties of pellets containing protein during high-shear pelletization.

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(®) 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.