Preparation and Statistical Modeling of Solid Lipid Nanoparticles of Dimethyl Fumarate for Better Management of Multiple Sclerosis

Purpose: The objective of this study was to synthesize and statistically optimize dimethyl fumarate (DMF) loaded solid lipid nanoparticles (SLNs) for better management of multiple sclerosis (MS). Methods: SLNs were formulated by hot emulsion, ultrasonication method and optimized with response surfac...

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Main Authors: Smriti Ojha, Babita Kumar
Format: Article
Language:English
Published: Tabriz University of Medical Sciences 2018-06-01
Series:Advanced Pharmaceutical Bulletin
Subjects:
Online Access:http://apb.tbzmed.ac.ir/PDF/apb-8-225.pdf
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author Smriti Ojha
Babita Kumar
author_facet Smriti Ojha
Babita Kumar
author_sort Smriti Ojha
collection DOAJ
description Purpose: The objective of this study was to synthesize and statistically optimize dimethyl fumarate (DMF) loaded solid lipid nanoparticles (SLNs) for better management of multiple sclerosis (MS). Methods: SLNs were formulated by hot emulsion, ultrasonication method and optimized with response surface methodology (RSM). A three factor and three level box-behnken design was used to demonstrate the role of polynomial quadratic equation and contour plots in predicting the effect of independent variables on dependent responses that were particle size and % entrapment efficiency (%EE). Results: The results were analyzed by analysis of variance (ANOVA) to evaluate the significant differences between the independent variables. The optimized SLNs were characterized and found to have an average particle size of 300 nm, zeta potential value of -34.89 mv and polydispersity index value < 0.3. Entrapment efficiency was found to be 59% and drug loading was 15%. TEM microphotograph revealed spherical shape and no aggregation of nanoparticles. In-vitro drug release profile was an indicative of prolonged therapy. In-vivo pharmacokinetic data revealed that the relative bioavailability was enhanced in DMF loaded SLNs in Wistar rats. Conclusion: This study showed that the present formulation with improved characteristics can be a promising formulation with a longer half-life for the better management of MS.
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spelling doaj.art-8fb4cd45bc144b008906e12fe1f70bbc2022-12-21T21:05:16ZengTabriz University of Medical SciencesAdvanced Pharmaceutical Bulletin2228-58812251-73082018-06-018222523310.15171/apb.2018.027APB_19393_20170520131522Preparation and Statistical Modeling of Solid Lipid Nanoparticles of Dimethyl Fumarate for Better Management of Multiple SclerosisSmriti Ojha0Babita Kumar1Vishveshwarya Group of Institutions, Department of Pharmacy, G.B. Nagar, Uttar Pradesh 203207.Sanskar Educational Group, Department of Pharmacy, Ghaziabad, Uttar Pradesh 201302.Purpose: The objective of this study was to synthesize and statistically optimize dimethyl fumarate (DMF) loaded solid lipid nanoparticles (SLNs) for better management of multiple sclerosis (MS). Methods: SLNs were formulated by hot emulsion, ultrasonication method and optimized with response surface methodology (RSM). A three factor and three level box-behnken design was used to demonstrate the role of polynomial quadratic equation and contour plots in predicting the effect of independent variables on dependent responses that were particle size and % entrapment efficiency (%EE). Results: The results were analyzed by analysis of variance (ANOVA) to evaluate the significant differences between the independent variables. The optimized SLNs were characterized and found to have an average particle size of 300 nm, zeta potential value of -34.89 mv and polydispersity index value < 0.3. Entrapment efficiency was found to be 59% and drug loading was 15%. TEM microphotograph revealed spherical shape and no aggregation of nanoparticles. In-vitro drug release profile was an indicative of prolonged therapy. In-vivo pharmacokinetic data revealed that the relative bioavailability was enhanced in DMF loaded SLNs in Wistar rats. Conclusion: This study showed that the present formulation with improved characteristics can be a promising formulation with a longer half-life for the better management of MS.http://apb.tbzmed.ac.ir/PDF/apb-8-225.pdfBox-behnken designDimethyl FumarateMultiple SclerosisResponse Surface MethodSolid lipid nanoparticlesPolydispersity index
spellingShingle Smriti Ojha
Babita Kumar
Preparation and Statistical Modeling of Solid Lipid Nanoparticles of Dimethyl Fumarate for Better Management of Multiple Sclerosis
Advanced Pharmaceutical Bulletin
Box-behnken design
Dimethyl Fumarate
Multiple Sclerosis
Response Surface Method
Solid lipid nanoparticles
Polydispersity index
title Preparation and Statistical Modeling of Solid Lipid Nanoparticles of Dimethyl Fumarate for Better Management of Multiple Sclerosis
title_full Preparation and Statistical Modeling of Solid Lipid Nanoparticles of Dimethyl Fumarate for Better Management of Multiple Sclerosis
title_fullStr Preparation and Statistical Modeling of Solid Lipid Nanoparticles of Dimethyl Fumarate for Better Management of Multiple Sclerosis
title_full_unstemmed Preparation and Statistical Modeling of Solid Lipid Nanoparticles of Dimethyl Fumarate for Better Management of Multiple Sclerosis
title_short Preparation and Statistical Modeling of Solid Lipid Nanoparticles of Dimethyl Fumarate for Better Management of Multiple Sclerosis
title_sort preparation and statistical modeling of solid lipid nanoparticles of dimethyl fumarate for better management of multiple sclerosis
topic Box-behnken design
Dimethyl Fumarate
Multiple Sclerosis
Response Surface Method
Solid lipid nanoparticles
Polydispersity index
url http://apb.tbzmed.ac.ir/PDF/apb-8-225.pdf
work_keys_str_mv AT smritiojha preparationandstatisticalmodelingofsolidlipidnanoparticlesofdimethylfumarateforbettermanagementofmultiplesclerosis
AT babitakumar preparationandstatisticalmodelingofsolidlipidnanoparticlesofdimethylfumarateforbettermanagementofmultiplesclerosis