Literature DB >> 27480117

Loteprednol Etabonate Nanoparticles: Optimization via Box-Behnken Design Response Surface Methodology and Physicochemical Characterization.

Abhishek K Sah1, Preeti K Suresh1.   

Abstract

BACKGROUND: Abstract: The objective of the present work was to prepare and optimize the loteprednoletabonate (LE) loaded poly (D,L-lactide co-glycolide) (PLGA) polymer based nanoparticle carrier. The review on recent patents (US9006241, US20130224302A1, US2012/0028947A1) assisted in the selection of drug and polymer for designing nanoparticles for ocular delivery applications.
METHODS: The nanoparticles were prepared by solvent evaporation followed by high speed homogenization. Biodegradable polymer PLGA (50:50) grade was utilized to develop various formulations with different drug:polymer ratio. A Box-Behnken design with 33 factorial design was selected for the present study and 17 runs were carried out in totality. The influence of various process variables (viz., polymer concentration, homogenization speed and sonication time) on the characteristics of nanoparticles including the in vitro drug release profile were studied.
RESULTS: The nanoparticulate formulations were evaluated for mean spherical diameter, polydispersity index (PDI), zeta potential, surface morphology, drug entrapment and in-vitro drug release profile. The entrapment efficiency, drug loading and mean particle size were found to be 96.31±1.68 %, 35.46±0.35 % and 167.6±2.1 nm respectively.
CONCLUSION: The investigated process and formulation variables were found to have significant effect on the particle size, drug loading (DL), entrapment efficiency (EE), and in vitro drug release profile. A biphasic in vitro drug release profile was apparent from the optimized nanoparticles (NPs) for 24 hours. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Entities:  

Keywords:  Box-behnken design; PLGA; corticosteroid; loteprednol etabonate; nanoparticle; ocular delivery; optimization; surfacezzm321990response methodology

Mesh:

Substances:

Year:  2017        PMID: 27480117     DOI: 10.2174/1567201813666160801125235

Source DB:  PubMed          Journal:  Curr Drug Deliv        ISSN: 1567-2018            Impact factor:   2.565


  2 in total

1.  Application of statistical design to evaluate critical process parameters and optimize formulation technique of polymeric nanoparticles.

Authors:  Pradipta Sarkar; Saswati Bhattacharya; Tapan Kumar Pal
Journal:  R Soc Open Sci       Date:  2019-07-24       Impact factor: 2.963

2.  Preparation of psoralen polymer-lipid hybrid nanoparticles and their reversal of multidrug resistance in MCF-7/ADR cells.

Authors:  Qingqing Huang; Tiange Cai; Qianwen Li; Yinghong Huang; Qian Liu; Bingyue Wang; Xi Xia; Qi Wang; John C C Whitney; Susan P C Cole; Yu Cai
Journal:  Drug Deliv       Date:  2018-11       Impact factor: 6.419

  2 in total

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