Literature DB >> 28415481

Modeling of drug release behavior of pH and temperature sensitive poly(NIPAAm-co-AAc) IPN hydrogels using response surface methodology and artificial neural networks.

Sanogo Brahima1, Cihangir Boztepe1, Asim Kunkul1, Mehmet Yuceer2.   

Abstract

An interpenetrated polymer network (IPN) poly(NIPAAm-co-AAc) hydrogel was synthesized by two polymerization method: emulsion and solution polymerization. The pH- and temperature-sensitive hydrogel was loaded by swelling with riboflavin drug, a B2 vitamin. The release of riboflavin as a function of time has been achieved under different pH and temperature environments. The determination of experimental conditions and the analysis of drug delivery results were achieved using response surface methodology (RSM). In this work, artificial neural networks (ANNs) in MATLAB were also used to model the release data. The predictions from the ANN model, which associated input variables, produced results showing good agreement with experimental data compared to the RSM results.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  ANN; Drug release; IPN; RSM; Smart hydrogel

Mesh:

Substances:

Year:  2017        PMID: 28415481     DOI: 10.1016/j.msec.2017.02.081

Source DB:  PubMed          Journal:  Mater Sci Eng C Mater Biol Appl        ISSN: 0928-4931            Impact factor:   7.328


  3 in total

Review 1.  Thermo-Sensitive Nanomaterials: Recent Advance in Synthesis and Biomedical Applications.

Authors:  Paola Sánchez-Moreno; Juan de Vicente; Stefania Nardecchia; Juan A Marchal; Houria Boulaiz
Journal:  Nanomaterials (Basel)       Date:  2018-11-13       Impact factor: 5.719

2.  Preparation and Characterization of Temperature/pH Dual-Responsive Gel Spheres for Immobilizing Nitro Bacteria.

Authors:  Qiong Wan; Xuan Li; Yingchun Ren; Yixi Cao; Kai Ju; Guohong Yang; Yongqing Sun; Xinyan Zhang
Journal:  ACS Omega       Date:  2022-02-08

Review 3.  State-of-the-Art Review of Artificial Neural Networks to Predict, Characterize and Optimize Pharmaceutical Formulation.

Authors:  Shan Wang; Jinwei Di; Dan Wang; Xudong Dai; Yabing Hua; Xiang Gao; Aiping Zheng; Jing Gao
Journal:  Pharmaceutics       Date:  2022-01-13       Impact factor: 6.321

  3 in total

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