https://doi.org/10.15255/KUI.2021.008
Published: Kem. Ind. 71 (1-2) (2022) 9–19
Paper reference number: KUI-08/2021
Paper type: Original scientific paper
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Cumulative Drug Release Modelling of PCL-PVP Encapsulated Tramadol by DA-SVM, MLR, PLS, and OLS Regression Techniques

A. Chabane, F. Bouchal, M. Hentabli, F. Rezgui and H. E. Slama

Abstract

This work aimed to model the kinetics of cumulative drug release from formulations based on encapsulation by biodegradable polycaprolactone and polyvinylpyrrolidone polymers. Different ratios of the polymerswere prepared by a solvent evaporation method using Span 20 and Span 80 as surfactants. The cumulative drug release was estimated depending on the formulation component and time. Four models: hybrid model of support vector machine and dragonfly algorithm (DA-SVM), partial least squares (PLS) model, multiple linear regression (MLR) model, and ordinary least squared (OLS) model, were developed and compared. The statistical analysis proved there were no issues in variable inputs. The results showed that the DA-SVM model gave a better result where a determination coefficient was close to one and RMSE error close to zero. A graphical interface was built to calculate the cumulative drug release.

This work is licensed under a Creative Commons Attribution 4.0 International License

Keywords

Dragonfly algorithm, support vector machine, Tramadol, cumulative drug releases, modelling, biopolymer, least squares