QSPR modeling of pseudoternary microemulsions formulated employing lecithin surfactants: Application of data mining, molecular and statistical modeling

Data mining, computer aided molecular modeling, descriptor calculation, genetic algorithm and multiple linear regression analysis techniques were combined together to generate predictive quantitative structure property relationship (QSPR) models explaining the formation of lecithin-based W/O microem...

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Bibliographic Details
Published in:International journal of pharmaceutics 2005-05, Vol.295 (1), p.135-155
Main Authors: Taha, Mutasem O., Abdel-Halim, Heba, Al-Ghazawi, Mutasim, Khalil, Enam
Format: Article
Language:English
Subjects:
Biological and medical sciences
Emulsions
General pharmacology
Genetic algorithm
Lecithin
Medical sciences
Microemulsions
Models, Molecular
Models, Statistical
Molecular modeling
Multiple linear regression
Pharmaceutical technology. Pharmaceutical industry
Pharmacology. Drug treatments
Phosphatidylcholines - administration & dosage
Physicochemical descriptors
QSPR
Quantitative Structure-Activity Relationship
Regression Analysis
Surface-Active Agents - administration & dosage
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Summary:Data mining, computer aided molecular modeling, descriptor calculation, genetic algorithm and multiple linear regression analysis techniques were combined together to generate predictive quantitative structure property relationship (QSPR) models explaining the formation of lecithin-based W/O microemulsions. Ninety-four microemulsion phase diagrams were collected from five different references published over the past few years. Computer-based molecular modeling techniques were then applied on the components of the collected microemulsion systems to generate corresponding plausible three-dimensional (3D) structures. The resulting 3D models were utilized to calculate a group of molecular physicochemical descriptors. Thereafter, genetic algorithm and backward stepwise regression analysis were separately assessed as means for selecting optimal descriptor sets for statistical modeling. The selected descriptors were correlated with microemulsion existence areas employing multiple linear regression analysis. The resulting W/O models were statistically validated and found to be of significant predictive power. The models allowed better understanding of the process of microemulsion formation. Unfortunately, all QSPR modeling efforts directed towards O/W microemulsions failed completely.
ISSN:0378-5173
1873-3476
DOI:10.1016/j.ijpharm.2005.02.012