Original scientific paper
https://doi.org/10.15255/KUI.2019.038
Artificial Intelligence and Mathematical Modelling of the Drying Kinetics of Pharmaceutical Powders
Sonia Keskes
; Laboratory Quality Control, Physico-Chemical Department, SAIDAL of Médéa, Algeria
Salah Hanini
; Laboratory of Biomaterials and Transport Phenomena (LBMPT), Faculty of Technology, University Yahia Fares of Médéa, Algeria
Mohamed Hentabli
orcid.org/0000-0002-6693-0708
; Laboratory Quality Control, Physico-Chemical Department, SAIDAL of Médéa, Algeria
Mammar Laidi
orcid.org/0000-0002-8977-9895
; Laboratory of Biomaterials and Transport Phenomena (LBMPT), Faculty of Technology, University Yahia Fares of Médéa, Algeria
Abstract
The study aims at modelling the drying kinetics of a pharmaceutical powder with active ingredient Candesartan Cilexetil. The kinetics was carried out in a vacuum dryer at different temperature levels, pressure, initial mass, and water content. The effect of some operating parameters on the drying time was studied. The modelling of drying times was based on the use of experimental design method. The data obtained were adjusted using 17 semi-empirical models, one proposed, a static ANN and DA_SVMR, regrouping all studied kinetics. The proposed model and DA_SVMR model were chosen as the most appropriate to describe the drying kinetics.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Keywords
Dragonfly algorithm; support vector machine regression (DA_SVMR); artificial neural network (ANN); mathematical modelling; drying kinetics; vacuum drying; Candesartan Cilexetil
Hrčak ID:
235869
URI
Publication date:
19.3.2020.
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