Application of different models to evaluate the key factors of fluidized bed layering granulation and their influence on granule characteristics
Different modeling approaches were used to understand the key factors affecting the outcomes of pulse sprayed FBLG. A large amount of metformin hydrochloride (~83%) was layered onto Cellets® seeds to obtain directly compressible granules. The effect of spray rate, mass flow rate, inlet air temperature, atomization pressure, and coating solution on the five granule characteristics (mean size, relative width, granule porosity, production yield, and aggregation index) was evaluated using a DSD and correlated with RSM, PLS, and ANN models.
- • Large amount of metformin was layered onto Cellets® seeds using pulsed-spray FBLG.
- • DSD identified factors: size, distribution, porosity, yield, and aggregation index.
- • Predictability of RSM and ANN models (R2 > 0.80) was superior to PLS model (R2 > 0.47).
- • ANN model could predict all responses concurrently with acceptable accuracy.
The cohesive drug was converted into non-hygroscopic, free-flowing, and stable granules which had several benefits such as large particle size, narrow size distribution, lesser granule porosity, high yield, negligible aggregation, and good compactibility. RSM (R2 > 0.81) and ANN models (R2 > 0.80) had a better fit with experimental factors compared with PLS model (R2 > 0.47). Machine-learning algorithms like the ANN as considering multiple factors could give a robust and successful modeling for the FBLG process.
Additional excipient used in the research : Kollidon
Ravi Maharjan, Seong Hoon Jeong,
Application of different models to evaluate the key factors of fluidized bed layering granulation and their influence on granule characteristics,
Powder Technology, Volume 408, 2022, 117737, ISSN 0032-5910,