Your browser doesn't support javascript.
loading
Optimization of Meloxicam Nanosuspensions Fast Dissolving Sublingual Films (MLX-NS-Fdsfs) by Box-Behnken Response Surface Methodology / 中国药学杂志
Article in Zh | WPRIM | ID: wpr-858467
Responsible library: WPRO
ABSTRACT
OBJECTIVE: To prepare and optimize meloxicam nanosuspensions fast dissolving sublingual films (MLX-NS-FDSFs) and to evaluate its in vitro dissolution characteristics. METHODS: Meloxicam nanosuspensions (MLX-NS) were prepared by pH-dependent dissolving-precipitating/high speed shearing method and then transformed into fast dissolving sublingual films (FDSFs). The formulations of MLX-NS-FDSFs were optimized by employing Box-Behnken design-response surface methodology with the amount of HPMC-E30, PEG-400 and MLX-NS as investigation factors, and particle size of reconstituted nanoparticles from MLX-NS-FDSFs, disintegration time and stretch length as indexes. The morphology, content uniformity and in vitro dissolution of the optimal formulation were also evaluated. RESULTS: The MLX-NS-FDSFs prepared by optimized formulation (35 mg·mL-1 HPMC-E30, 40 mg·mL-1 PEG-400, 10 mL MLX-NS) could fast disintegrate in (26.08±1.76) s, the tensile length was (1.51±0.13) mm, and the particle size of reconstituted nanoparticles from MLX-NS-FDSFs was (186.4±6.3) nm. There was a little deviation between the theoretically predicted value and the measured value. It showed that this model had a good prediction. Morphological analysis showed that well-dispersed MLX nanoparticles embedded in MLX-NS-FDSFs. The conformity of drug content was up to standard. MLX could be released in vitro as much as (91.75±8.05)% within five minutes. CONCLUSION: Using Box-Behnken design and response surface method to optimize MLX-NS-FDSFs is effective and feasible. MLX-NS-FDSFs can significantly increase the cumulative dissolution of MLX.
Key words
Full text: 1 Database: WPRIM Type of study: Prognostic_studies Language: Zh Journal: Chinese Pharmaceutical Journal Year: 2018 Document type: Article
Full text: 1 Database: WPRIM Type of study: Prognostic_studies Language: Zh Journal: Chinese Pharmaceutical Journal Year: 2018 Document type: Article