Solid dispersions in the development of a nimodipine floating tablet formulation and optimization by artificial neural networks and genetic programming |
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Authors: | Panagiotis BarmpalexisKyriakos Kachrimanis Emanouil Georgarakis |
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Affiliation: | Department of Pharmaceutical Technology, Aristotle University of Thessaloniki, Thessaloniki, Greece |
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Abstract: | The present study investigates the use of nimodipine-polyethylene glycol solid dispersions for the development of effervescent controlled release floating tablet formulations. The physical state of the dispersed nimodipine in the polymer matrix was characterized by differential scanning calorimetry, powder X-ray diffraction, FT-IR spectroscopy and polarized light microscopy, and the mixture proportions of polyethylene glycol (PEG), polyvinyl-pyrrolidone (PVP), hydroxypropylmethylcellulose (HPMC), effervescent agents (EFF) and nimodipine were optimized in relation to drug release (% release at 60 min, and time at which the 90% of the drug was dissolved) and floating properties (tablet’s floating strength and duration), employing a 25-run D-optimal mixture design combined with artificial neural networks (ANNs) and genetic programming (GP). It was found that nimodipine exists as mod I microcrystals in the solid dispersions and is stable for at least a three-month period. The tablets showed good floating properties and controlled release profiles, with drug release proceeding via the concomitant operation of swelling and erosion of the polymer matrix. ANNs and GP both proved to be efficient tools in the optimization of the tablet formulation, and the global optimum formulation suggested by the GP equations consisted of PEG = 9%, PVP = 30%, HPMC = 36%, EFF = 11%, nimodipine = 14%. |
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Keywords: | Solid dispersions Nimodipine Controlled release Effervescent floating tablets Artificial neural networks Genetic programming |
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