Nifedipine is a dihydropyridine calcium channel antagonist effective in the clinical management of cardiovascular disease. Due to nifedipine's poor water solubility and erratic bioavailability, complexation with selected cyclodextrins was studied in order to overcome these limitations. The aim was to develop a quantitative structure property relationship (QSPR) to identify cyclodextrin molecular properties important in complex formation and provide a predictive tool which would be valuable during preformulation studies. The QSPR developed indicates that the major driving forces for nifedipine complexation, in addition to cyclodextrin concentration, are hydrophobicity and Van der Waals interactions (3D solubility parameters, hydrophilic surface area and differential connectivity index).
Keywords: Artificial neural networks (ANN), cyclodextrin (CD), complexation, nifedipine, phase solubility studies, quantitative structure property relationship (QSPR)
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