Development of Oral Chewable Tablets Containing Montelukast Nanoparticles for the Treatment of Childhood Asthma: Preclinical Study in Animal Model

Abstract

The aim of the present study was to formulate oral chewable tablets of Montelukast (MTL) in the form of nanoparticles (NP’s). The MTL loaded NP’s were formulated by ionotropic external gelation method using tripolyphosphate (TPP) as crosslinking agent and Tween 60 as surfactant. NP’s were characterized for drug loading, encapsulation efficiency, surface morphology, saturation solubility, particle size, zeta potential and polydispersity index. The optimized NP formulation was used for development of chewable tablets using direct compression method. The prepared tablets were characterized for disintegration test, dissolution, thickness, hardness, friability and assay. The optimized formulation was evaluated in asthamatic animals to demonstrate the efficiency in asthama. The encapsulation efficiency of NP’s was found between 91.24 to 98.21% while drug loading was in the range of 10.09–14.25%. All formulations were found of nanosized in nature (110 to 200 nm) with excellent zeta potential (20.12 to 22.27 mV). PDI of all NP formulations were found within acceptable limit (less than 0.3). The nanoparticles were found spherical in shape with smooth surface. The saturation solubility of MTL was enhanced nearly 10 times (92 mg/ml) as compared to pure MTL saturation solubility. All physical parameters of the tablets were found within range. The optimized tablets showed disintegration time of 20 sec while other formulations showed DT in the rage of 35–57 sec. Tab1 (Optimized formulation) showed almost 100% MTL release from chewable tablets within the period of 30 min. Reduction in lung resistance (RI) was found in animals treated with Tab1. This reduction in RI was found nearly two fold and three fold as compare to MTL treated and control group animals. These observations clearly support the efficacy of chewable tablets containing nanoparticulate MTL in asthmatic animals.