Literature DB >> 14661919

Prediction of a stable microemulsion formulation for the oral delivery of a combination of antitubercular drugs using ANN methodology.

Snezana Agatonovic-Kustrin1, Beverley D Glass, Michael H Wisch, Raid G Alany.   

Abstract

PURPOSE: The aim of this project was to develop a colloidal dosage form for the oral delivery of rifampicin and isoniazid in combination with the aid of artificial neural network (ANN) data modeling.
METHODS: Data from the 20 pseudoternary phase triangles containing miglyol 812 as the oil component and a mixture of surfactants or a surfactant/cosurfactant blend were used to train, test, and validate the ANN model. The weight ratios of individual components were correlated with the observed phase behavior using radial basis function (RBF) network architecture. The criterion for judging the best model was the percentage success of the model prediction.
RESULTS: The best model successfully predicted the microemulsion region as well as the coarse emulsion region but failed to predict the multiphase liquid crystalline phase for cosurfactant-free systems indicating the difference in microemulsion behavior on dilution with water.
CONCLUSIONS: A novel microemulsion formulation capable of delivering rifampicin and isoniazid in combination was created to allow for their differences in solubility and potential for chemical reaction. The developed model allowed better understanding of the process of microemulsion formation and stability within pseudoternary colloidal systems.

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Year:  2003        PMID: 14661919     DOI: 10.1023/b:pham.0000003372.56993.39

Source DB:  PubMed          Journal:  Pharm Res        ISSN: 0724-8741            Impact factor:   4.200


  4 in total

1.  Characterizing colloidal structures of pseudoternary phase diagrams formed by oil/water/amphiphile systems.

Authors:  R G Alany; I G Tucker; N M Davies; T Rades
Journal:  Drug Dev Ind Pharm       Date:  2001-01       Impact factor: 3.225

2.  Assessing the importance of features for multi-layer perceptrons.

Authors:  Michael Egmont-Petersen; Jan L. Talmon; Arie Hasman; Anton W. Ambergen
Journal:  Neural Netw       Date:  1998-06

3.  Investigation of the phase behaviour of systems containing lecithin and 2-acyl lysolecithin derivatives.

Authors:  M Trotta; M Gallarate; F Pattarino; M E Carlotti
Journal:  Int J Pharm       Date:  1999-11-10       Impact factor: 5.875

4.  Effects of alcohols and diols on the phase behaviour of quaternary systems.

Authors:  R G Alany; T Rades; S Agatonovic-Kustrin; N M Davies; I G Tucker
Journal:  Int J Pharm       Date:  2000-03-10       Impact factor: 5.875

  4 in total
  4 in total

1.  Match of Solubility Parameters Between Oil and Surfactants as a Rational Approach for the Formulation of Microemulsion with a High Dispersed Volume of Copaiba Oil and Low Surfactant Content.

Authors:  Francisco Humberto Xavier-Junior; Nicolas Huang; Jean-Jacques Vachon; Vera Lucia Garcia Rehder; Eryvaldo Sócrates Tabosa do Egito; Christine Vauthier
Journal:  Pharm Res       Date:  2016-09-06       Impact factor: 4.200

2.  Parameter estimation for stiff equations of biosystems using radial basis function networks.

Authors:  Yoshiya Matsubara; Shinichi Kikuchi; Masahiro Sugimoto; Masaru Tomita
Journal:  BMC Bioinformatics       Date:  2006-04-27       Impact factor: 3.169

3.  Quality by Design Approach Using Multiple Linear and Logistic Regression Modeling Enables Microemulsion Scale Up.

Authors:  Michele Herneisey; Eric Lambert; Allison Kachel; Emma Shychuck; James K Drennen; Jelena M Janjic
Journal:  Molecules       Date:  2019-05-30       Impact factor: 4.411

Review 4.  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

  4 in total

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