(533d) Modeling Two-Dimensional Moisture Content and Size Evolution of Pharmaceutical Granules in a Semicontinuous Fluid Bed Dryer
- Conference: AIChE Annual Meeting
- Year: 2019
- Proceeding: 2019 AIChE Annual Meeting
- Group: Pharmaceutical Discovery, Development and Manufacturing Forum
- Time: Wednesday, November 13, 2019 - 1:33pm-1:54pm
A modeling study of this process was performed in (Ghijs et al., 2019). It comprised a model relating single granule drying behavior to the evolution in moisture content seen in the semicontinuous process, including the effect of granule size. The model of (Mortier et al., 2012) represented the drying phenomena on single granule scale, and was thus applied in a sequential addition mode in order to emulate the semicontinuous drying behavior. The model performed well when applied to the data from (De Leersnyder et al., 2018) collected at a dryer cell fill level of 1 kg of granules in the cell. However, lower levels could not yet be validated mechanistically. Therefore, in order to enhance modelâs predictive power for wider application, the work indicates that a more accurate inclusion of fluidization, air conditions and filling effects would benefit the model. This work presents these augmentations.
While the model of (Ghijs et al., 2019) assumed an ideal and constant fluidization behavior, the reality in the ConsiGmaâ25â¢ dryer is presumably different as air flow, particle size distribution and moisture content influence fluidization quality. The approach from (Peglow et al., 2007) is therefore incorporated into the model. It relates single particle drying kinetics to batch behavior by taking into account fluidization behavior conceptually, predicting the fraction of the drying air that brings the granules in suspension and the fraction that bypasses the granules. The single particle drying kinetics in this case still stem from the mechanistic model of (Mortier et al., 2012).
Other features of the model in (Peglow et al., 2007) are the mass and heat balances for exchange of water vapor and heat between granules and drying air. This updates the average relative humidity of the drying air in the fluid bed accordingly. That in turn influences the drying rate of the granules present in the bed. The heat and mass balances, which also include the heat transfer from the dryer to the environment, are moreover tailored to the ConsiGmaâ25â¢ dryer itself according to the work of (Mortier, Gernaey, De Beer, & Nopens, 2014).
A final model augmentation is the tracking of granules and the drying regimes they are subjected to throughout the drying process. Indeed, granules in the fluid bed chamber entered the system at different times due to the continuous filling of the cell. Moreover, those entering at a later time are moreover starting their drying curve in different conditions than these entering first in an empty cell. The different air conditions are captured with the heat and mass balances. The tracking of the granules per size fraction and moisture content occurs with a 2D population balance model (PBM). The latter models the moisture content distribution of the granules per size fraction. The range of moisture content of the granules is discretized into a number of levels, which serves as the grid for the PBM. The number of granules in each moisture content level is then tracked, and evolves due to the drying. The decrease in moisture content is modeled by a negative growth rate, as in the work of (Mortier, Gernaey, De Beer, & Nopens, 2013). Also the continuous inflow of wet granules into the dryer cell is introduced into the PBM as a source term in the moisture content level of the wet granules. This way, the entire population can be tracked for the semicontinuous operation.
It is concluded that a more accurate representation of semicontinuous drying of pharmaceutical granules has been achieved, capturing the influence of the CPPs of the drying process mechanistically. The model concept, implementation, simulation and calibration methodology will be presented.
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