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bijps-929
Formulation and Characterization of Itraconazole as Nanosuspension Dosage Form for Enhancement of Solubility
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Abstract

            Itraconazole is a triazole antifungal given orally for the treatment of oropharyngeal and vulvovaginal candidiasis, for systemic infections including aspergillosis, candidiasis,  and for the prophylaxis of fungal infections in immunocompromised patients.

           The study aimed to formulate a practical water-insoluble Itraconazole, with insufficient bioavailability as nanosuspension to increase aqueous solubility and improve its dissolution and oral bioavailability.

          Itraconazole nanosuspension was produced by a solvent-antisolvent nanoprecipitation method in the presence of different stabilisers (Poloxamer-188, HPMCE5) at different ratios with the drug alone or combination with surfactant(tween 80, SLS).

         The results exhibit that the particle sizes of all prepared itraconazole formulations were in the nano size.  The best formula (F6) has a particle size.  ( 42  ) nm and Zeta potential of (- 21.86 ) mV.  In vitro cumulative release from the nanosuspension was (88 %) at (30) min when compared to the pure drug (13%) and lyophilized nanoparticles (98.2%) at (30)min. Effect of different parameters was investigated.

          Fourier transforms infrared spectroscopy(FTIR), Differential scanning calorimetry (DSC) and X-ray diffraction (XRD), Scanning electron microscope( SEM) was done for the optimized  nanoparticles prepared by lyophilization technique

        Thus, Nanosuspension appears to be an encouraging approach to formulate Itraconazole nanosuspension with high solubility and dissolution rate.

 

 

 

 

 

 

 

Keywords: Itraconazole, Nanoprecipitation method, Nanosuspension

         

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Predicting the Sporting Achievement in the Pole Vault for Men Using Artificial Neural Networks
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Tue Jan 01 2019
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Generalized tupled common fixed point theorems for weakly compatible mappings in fuzzy metric space
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Thu Apr 01 2021
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Pushing towards ehealth for iraqi hypertensives: an integrated class association rules into SECI model
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