Particle Size, Moisture, and Fluidization Variations Described by Indirect In-line Physical Measurements of Fluid Bed Granulation

Abstract

Abstract. The aim of this study was to evaluate an instrumentation system for a bench scale fluid bed granulator to determine the parameters expressing the changing conditions during the spraying phase of a fluid bed process. The study focused mainly on four in-line measurements (dependent variables): fluidization parameter (calculated by inlet air flow rate and rotor speed), pressure difference over the upper filters, pressure difference over the granules (lower filter), and temperature of the fluidizing mass. In-line particle size measured by the spatial filtering technique was an essential predictor variable. Other physical process measurements of the automated granulation system, 25 direct and 12 derived parameters, were also utilized for multivariate modeling. The correlation and partial least squares analyses revealed significant relationships between various process parameters highlighting the particle size, moisture, and fluidization effect. Fluidization parameter and pressure difference over upper filters were found to correlate with in-line particle size and therefore could be used as estimates of particle size during granulation. The pressure difference over the granules and the temperature of the fluidizing mass expressed the moisture conditions of wet granulation. The instrumentation system evaluated here is an invaluable aid to gaining more control for fluid bed processing to obtain repeatable granules for further processing.

In-line spatial filtering velocimetry for particle size and film thickness determination in fluidized-bed pellet coating processes

“…Plitzko and Dietrich focussed on the in-line SFV detection of pellet agglomeration during Wurster coating [30], while SFV has recently been established for in-line particle size monitoring in fluidized bed granulation [27,[31][32][33][34][35][36]. The obtained SFV data improved the understanding of the impact of process variables by using model-based process control approaches, such as DoE, univariate and multivariate PLS.…”

Evaluation of in-line spatial filter velocimetry as PAT monitoring tool for particle growth during fluid bed granulation

“…However, particle size determination was influenced by size segregation in the fluid bed: the in-line technique underestimated and the at-line method overestimated the final granule size. Lipsanen et al showed that the pressure difference over the upper filters (indication of blockage of filters) and the fluidization parameter correlated well with the in-line particle size measurements [27].…”

“…Furthermore, we examined whether the in-line particle size data could be related to off-line measured end granule properties (tapped density and Hausner ratio) using univariate, multivariate and multiway models, hence allowing early estimation of these end product properties during processing. Whereas previous reports about in-line SFV emphasized on the sensitivity of the technique towards the in-line detection of granule size and process failures [26][27], the present study examines the application of the technique to enhance fluidized bed process understanding through the continuous measurement of particle size, in combination with DOE. Furthermore, models were built using the continuously measured in-line particle size information allowing early prediction of end granule properties.…”

Applications of Modeling in Oral Solid Dosage Form Development and Manufacturing

“…It has been proposed in the literature that development of a robust fluid bed process depends on control of the moisture profile [23,24,[31][32][33][34][35][36][37][38][39][40]. Moisture profile control of a fluid bed granulation process requires an operator or controller to manipulate three interdependent control "levers" available during processing.…”