scholarly journals Fluid Bed Granulation

2020 ◽  
Author(s):  
Keyword(s):  
Fluid Bed ◽  
Fluid Bed Granulation

Development of carvedilol-cyclodextrin inclusion complexes using fluid-bed granulation: a novel solid-state complexation alternative with technological advantages

2016 ◽  
Vol 68 (10) ◽  
pp. 1299-1309 ◽  
Author(s):  
Ellen C. P. Alonso ◽  
Karina Riccomini ◽  
Luis Antônio D. Silva ◽  
Daniela Galter ◽  
Eliana M. Lima ◽  
...  
Keyword(s):  
Solid State ◽  
Inclusion Complexes ◽  
Cyclodextrin Inclusion Complexes ◽  
Cyclodextrin Inclusion ◽  
Fluid Bed ◽  
Fluid Bed Granulation

scholarly journals Model Development and Validation of Fluid Bed Wet Granulation with Dry Binder Addition Using a Population Balance Model Methodology

Processes ◽  
2018 ◽  
Vol 6 (9) ◽  
pp. 154 ◽  
Author(s):  
Shashank Muddu ◽  
Ashutosh Tamrakar ◽  
Preetanshu Pandey ◽  
Rohit Ramachandran
Keyword(s):  
Experimental Study ◽  
Geometric Mean ◽  
Population Balance ◽  
Balance Model ◽  
Population Balance Model ◽  
Model Framework ◽  
Fluid Bed ◽  
Liquid Spray ◽  
Fluid Bed Granulation ◽  
Binder Liquid

An experimental study in industry was previously carried out on a batch fluid bed granulation system by varying the inlet fluidizing air temperature, binder liquid spray atomization pressure, the binder liquid spray rate and the disintegrant composition in the formulation. A population balance model framework integrated with heat transfer and moisture balance due to liquid addition and evaporation was developed to simulate the fluid bed granulation system. The model predictions were compared with the industry data, namely, the particle size distributions (PSDs) and geometric mean diameters (GMDs) at various time-points in the granulation process. The model also predicted the trends for binder particle dissolution in the wetting liquid and the temperatures of the bed particles in the fluid bed granulator. Lastly, various process parameters were varied and extended beyond the region studied in the aforementioned experimental study to identify optimal regimes for granulation.

Mechanistic modelling of fluid bed granulation, Part II: Eased process development via degree of wetness

2019 ◽  
Vol 572 ◽  
pp. 118836
Author(s):  
Maryam Askarishahi ◽  
Mohammad-Sadegh Salehi ◽  
Martin Maus ◽  
Daniela Schröder ◽  
David Slade ◽  
...  
Keyword(s):  
Process Development ◽  
Mechanistic Modelling ◽  
Fluid Bed ◽  
Fluid Bed Granulation

Modeling agglomeration processes in fluid-bed granulation

AIChE Journal ◽  
1999 ◽  
Vol 45 (10) ◽  
pp. 2069-2078 ◽  
Author(s):  
Steven A. Cryer
Keyword(s):  
Fluid Bed ◽  
Fluid Bed Granulation

scholarly journals Design Space Approach in Optimization of Fluid Bed Granulation and Tablets Compression Process

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Jelena Djuriš ◽  
Djordje Medarević ◽  
Marko Krstić ◽  
Ivana Vasiljević ◽  
Ivana Mašić ◽  
...  
Keyword(s):  
Process Parameters ◽  
Design Space ◽  
Quality Attributes ◽  
Dissolution Profile ◽  
Compression Force ◽  
Critical Quality Attributes ◽  
Fluid Bed ◽  
Fluid Bed Granulation ◽  
Atomization Pressure ◽  
Space Approach

The aim of this study was to optimize fluid bed granulation and tablets compression processes using design space approach. Type of diluent, binder concentration, temperature during mixing, granulation and drying, spray rate, and atomization pressure were recognized as critical formulation and process parameters. They were varied in the first set of experiments in order to estimate their influences on critical quality attributes, that is, granules characteristics (size distribution, flowability, bulk density, tapped density, Carr's index, Hausner's ratio, and moisture content) using Plackett-Burman experimental design. Type of diluent and atomization pressure were selected as the most important parameters. In the second set of experiments, design space for process parameters (atomization pressure and compression force) and its influence on tablets characteristics was developed. Percent of paracetamol released and tablets hardness were determined as critical quality attributes. Artificial neural networks (ANNs) were applied in order to determine design space. ANNs models showed that atomization pressure influences mostly on the dissolution profile, whereas compression force affects mainly the tablets hardness. Based on the obtained ANNs models, it is possible to predict tablet hardness and paracetamol release profile for any combination of analyzed factors.

scholarly journals Development of a fluid bed granulation process control strategy based on real-time process and product measurements

Talanta ◽  
2012 ◽  
Vol 100 ◽  
pp. 293-302 ◽  
Author(s):  
Anneleen Burggraeve ◽  
Ana F.T. Silva ◽  
Tom Van Den Kerkhof ◽  
Mario Hellings ◽  
Chris Vervaet ◽  
...  
Keyword(s):  
Process Control ◽  
Real Time ◽  
Control Strategy ◽  
Time Process ◽  
Granulation Process ◽  
Fluid Bed ◽  
Fluid Bed Granulation
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