Studies on Formulation Development of Mucoadhesive Sustained Release Itraconazole Tablet Using Response Surface Methodology

The purpose of this research was to prepare and evaluate sustained release mucoadhesive tablets of Itraconazole. It is practically insoluble in aqueous fluids hence its solid dispersion with Eudragit E100 was prepared by spray drying. This was formulated in matrix of hydrophilic mucoadhesive polymers Carbopol 934P (CP) and Methocel K4M (HPMC). The formulation was optimized using a 32 factorial design. Amounts of CP and HPMC were taken as formulation variables for optimizing response variables i.e. mucoadhesion and dissolution parameters. The optimized mucoadhesive formulation was orally administered to albino rabbits, and blood samples collected were used to determine pharmacokinetic parameters. The solid dispersion markedly enhanced the dissolution rate of itraconazole. The bioadhesive strength of formulation was found to vary linearly with increasing amount of both polymers. Formulations exhibited drug release fitting Peppas model with value of n ranging from 0.61 to 1.18. Optimum combination of polymers was arrived at which provided adequate bioadhesive strength and fairly regulated release profile. The experimental and predicted results for optimum formulations were found to be in close agreement. The formulation showed Cmax 1898 ± 75.23 ng/ml, tmax of the formulation was 2 h and AUC was observed to be 28604.9 ng h/m

Optimization of polylactic-co-glycolic acid nanoparticles containing itraconazole using 23 factorial design

This study investigated the utility of a 23 factorial design and optimization process for polylactic-co-glycolic acid (PLGA) nanoparticles containing itraconazole with 5 replicates at the center of the design. Nanoparticles were prepared by solvent displacement technique with PLGAX1 (10, 100 mg/mL), benzyl benzoateX2 (5, 20 μg/mL), and itraconazoleX3 (200, 1800 μg/mL). Particle size (Y1), the amount of itraconazole entrapped in the nanoparticles (Y2), and encapsulation efficiency (Y3) were used as responses. A validated statistical model having significant coefficient figures (P<.001) for the particle size (Y1), the amount of itraconazole entrapped in the nanoparticles (Y2), and encapsulation efficiency (Y3) as function of the PLGA (X1), benzyl benzoate (X2), and itraconazole (X3) were developed: Y1=373.75+66.54X1+52.09X2+105.06X3−4.73X1X2+46.30X1X3; Y2=472.93+73.45X1+ 169.06X2+333.03X3+62.40X1X3+141.49X2X3; Y3= 57.36+6.53X1+15.52X2−12.59X3+1.01X1X3+ 1.73X2X3.X1,X2, andX3 had a significant effect (P<.001) onY1,Y2, andY3. The particle size, the amount of itraconazole entrapped in the nanoparticles, and the encapsulation efficiency of the 4 formulas were in agreement with the predictions obtained from the models (P<.05). An overlay plot for the 3 responses shows the boundary in whichY1 shows the boundary in which a number of combinations of concentration of PLGA, benzyl benzoate, and itraconazole will result in a satisfactory process. Using the desirability approach with the same constraints, the solution composition having the highest overall desirability (D=0.769) was 10 mg/mL of PLGA, 16.94 μg/mL of benzyl benzoate, and 1001.01 μg/mL of itraconazole. This approach allowed the selection of the optimum formulation ingredients for PLGA nanoparticles containing itraconazole of 500 μg/mL