Original Article FORMULATION AND OPTIMIZATION OF CHITOSAN NANOPARTICLES OF DIMETHYL FUMARATE USING BOX-BEHNKEN DESIGN SMRITI OJHA *1 , BABITA KUMAR 2 1 Vishveshwarya Institute of Medical Sciences, Greater Noida, 2 Shri Ganpati Institute of Technology, Ghaziabad Email: smrititripathi23@gmail.com Received: 13 Jun 2016, Revised and Accepted: 07 Sep 2016 ABSTRACT Objective: Dimethyl fumarate (DMF) is a methyl ester of fumaric acid. It has been approved by USFDA recently for the treatment of an autoimmune disorder, multiple sclerosis (MS). The objective of present study was to synthesize and optimize chitosan loaded nanoparticles of DMF by box- behnken design (BBD), to provide a better drug delivery system for the management and treatment of MS. Methods: Polyelectrolyte complex coacervation technique was used to prepare Chitosan (CS) loaded DMF nanoparticles and box behnken design using 3 factors and 3 levels were selected for optimization of the formulation. Effect of three independent factors that is, polymer CS concentration, polymer dextran sulfate (DS) concentration and the amount of drug were studied on two dependent responses that is particle size and % drug entrapment efficiency. The analysis of variance (ANOVA) was performed to evaluate the significant differences between the independent variables. Results: The optimized batch showed the highest % drug entrapment (65.36) and an average particle size (355 nm). Zeta potential value was optimum to maintain the stability of the formulation. In vitro drug release behavior followed Korsmeyer-Peppas model which showed the initial release of 21.7±1.3% with prolonged drug release of 69.5±0.8% from optimized CS nanoparticle up to 24 h. The % cumulative drug release (% CDR) of optimized nanoparticles was 84%. Conclusion: The optimized nanoparticles of DMF with improved properties could be a promising formulation for the treatment and management of MS. Keywords: Multiple sclerosis, dimethyl fumarate, chitosan nanoparticle, optimization, box behnken design, complex polyelectrolyte conservation. © 2016 The Authors. Published by Innovare Academic Sciences Pvt Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/) DOI: http://dx.doi.org/10.22159/ijap.2016v8i4.13450 INTRODUCTION Nanoparticles represent an effective nanocarrier platform for the delivery of hydrophilic and hydrophobic drugs since the drugs are protected from possible degradation by enzymes [1]. MS is an autoimmune disease the body’s own immune system spearheads the attacks. The disorder is mediated by a complex interaction of individual’s genetics and as yet unidentified environmental insults. In multiple regions, the myelin sheaths deteriorate to sclerosis, which are hardened scar or plaques [2, 3]. Nanotechnology by manipulation of characteristics of materials such as polymers and fabrication of nanostructures is able to provide superior drug delivery systems for better management and treatment of diseases [2]. Drug targeting by nanoparticles has been getting much attention by the researchers for the treatment of various central nervous system disorders [4]. DMF is a white, nonhygroscopic BCS class 1 drug [5]. DMF has been approved by USFDA in 2014 as the first-line oral treatment for Multiple Sclerosis [6]. DMF is almost completely absorbed in the small intestine and extensively metabolized by esterases before it reaches the systemic circulation. The half-life of DMF is approximately 1 hour. CS is a promising candidate for preparation of nano and microparticulate drug delivery systems owing to its low toxicity, better stability, simple and reproducible preparation methods and provides versatile routes of administration as drug delivery carrier [7]. CS is one of the most abundant biopolymers, poly [β-(1,4)-2-amino-2- deoxy-d-glucopyranose], possesses unique structural features. In the present method, an organic phase containing the polymer and drug is added dropwise to a dispersing phase which is a nonsolvent for the dispersed polymer but is miscible with the diffusing solvent. The formation of nanoparticles happens spontaneously [8]. This method does not require vigorous shearing or stirring rates, ultrasonication and is mostly suitable for the compounds having hydrophobic nature [9-11]. In the present study, CS loaded DMF nanoparticles were formulated and optimized by box-behnken design. This work has a novel and promising approach for the use of DMF in the treatment and management of MS. MATERIALS AND METHODS Materials CS (degree of acetylation=80.45%) and dextran sulphate (DS) were procured from chemsworth chemicals, Surat. DMF was obtained from Alfa Aesar; a Johnson matthey company. Methanol, glacial acetic acid, and acetone were of the suitable analytical grade. Double distilled water was used in the preparation of solutions and dispersion of chitosan nanoparticles. Preparation of CS DS nanoparticle CS Nanoparticles were prepared by polyelectrolyte complex coaservation technique [12-15]. A solution of CS was prepared by dissolving required quantity of CS in 2% v/v acetic acid solution. DS solution was prepared by dissolving required quantity of DS in double distilled water. To DS solution required a quantity of DMF was added and dissolved completely. Now DS containing dissolved drug solution was added dropwise to CS solution under magnetic stirrer for 1 hour. Tween 80 was added to stabilize the resultant particles followed by continuous stirring. The ratio between the volumes of DS Solution and CS solution was 1:4. The nanoparticle batches were prepared as per box-behnken design. Optimization of CS nanoparticles by box Behnken design Design Expert® 9.0.5.1 software was used to developing a box- behnken statistical design, response surface methodology (RSM) with 3 factors, 3 levels, and 15 runs for the optimization of CS nanoparticles [16-18]. Optimization was performed to investigate the level of independent variables (X1, X2, and X3) that would yield a minimum value of the particle size (R1) and the maximum value of EE (R2). The design was used to explore the quadratic response surfaces, and the polynomial equation was generated by the experimental design is as follows: Y = b 0 + b 1 x 1 + b 2 x 2 + b 3 x 3 + b 12 x 1 x 2 + b 13 x 1 x 3 + b 23 x 2 x 3 + b 11 X1 2 1 1 + b 22 X2 2 1 1 + b 33 X3 2 1 1 International Journal of Applied Pharmaceutics ISSN- 0975-7058 Vol 8, Issue 4, 2016