(461d) Sequential Fixed Fluidized Bed Foam Granulation (SFFBFG) and Drying: Multivariate Model Development for Water Content Monitoring with Near-Infrared Spectroscopy

Foam granulation is a non-conventional technique in which the binding solution is sprayed as an aqueous foam onto a powder bed. This method could offer some advantages including a better binder distribution along with the usage of less binder compared to conventional spray granulation. In this work, the aqueous foam is sprayed onto a pharmaceutical powder blend followed by an agglomeration process in a fluidized bed granulator. The main objectives of this work are (a) to covert a lab-scale fluidized bed dryer (FBD) into a fluidized bed foam granulator (FBFG) with the capacity to be used as a FBD following the FG step; (b) to develop a partial least squares (PLS) regression model for granules water content monitoring during this FBFG process and (c) to bring forward sufficient evidence of the FBFG process feasibility and efficiency in comparison with more conventional techniques. The latter is the main target within our endeavor towards process intensification in pharmaceutical industrial production. Data gathered during the entire process are preprocessed by various techniques. Fist, baseline shift is removed by Savitsky-Golay 1^st derivative. Secondly, data are aligned by linear interpolation as batch durations are different. Finally, the 3D data is unfolded to 2D according to the observation-wise rearrangement.

The calibration model was built based on 58% of the initial dataset by Random Subset Cross-Validation () and validated externally. The external validation was performed on the remaining 42 % of the initial dataset. With respect to the results:

• Only two (02) latent variables (LV) were sufficient to capture approximatively 99.6 % of the total variance contained in the initial dataset. Furthermore, it was shown that the scores of the first LV (LV1) were related to the presence of water.
• An and of 0.93 and 1.8 % w/w are obtained respectively. Besides, the validation of the model gave an and of 0.9 and 2.4 % w/w respectively showing the ability of Near Infrared (NIR) spectroscopy to satisfactorily predict the granules water content during this non-conventional technique.
• The scanning electron microscopy (SEM) pictures validated the proof of concept and confirmed that this method could be used as a granulation technique in the pharmaceutical field and be combined with FBD within the same apparatus