Preparation, Design for Optimization and in Vitro Evaluation of Insulin Nanoparticles Integrating Thiolated Chitosan Derivatives

J. DRUG DEL. SCI. TECH., 24 (1) 40-49 2014

Preparation, design for optimization and in vitro evaluation of insulin nanoparticles integrating thiolated chitosan derivatives E. Mortazavian1, M. Amini2, 6, F.A. Dorkoosh1, H. Amini8, M.R. Khoshayand3, T. Amini7, M. Rafiee-Tehrani1, 4, 5* 1

Department of Pharmaceutics, 2Department of Medicinal Chemistry, 3Department of Food and Drug Control and Pharmaceutical Quality Assurance Research Centre, 4Nanotechnology Research Centre, 5School of Pharmacy, 6Drug Design and Development Research Centre, Tehran University of Medical Sciences, PO Box 14395/459, Tehran 14, Iran 7 Nobleceuticals Ltd., Birmingham, United Kingdom 8 Department of Pharmacology, Neuroscience Research Center, Golestan University of Medical Sciences, Gorgan, Iran *Correspondence: [email protected]

This study aims at the statistical optimization and in vitro characterization of insulin nanoparticles containing thiolatd N-diethyl methyl chitosan (DEMC-Cys) and N-dimethyl ethyl chitosan (DMEC-Cys) conjugates. Insulin nanoparticles containing these conjugates were prepared by polyelectrolyte complexation (PEC) method. Further optimization of nanoparticles was continued by Box-Behnken design. Morphological studies of optimized nanopaticles were performed by scanning electron microscopy (SEM). In vitro release study was carried out in phosphate buffer solution pH 6.8. Insulin nanoparticles composed of DMEC-Cys (35 % degree of quaternization and 155 µmole thiol group/gram polymer) had more effect on minimizing particle size of insulin nanoparticles compared to DEMC-Cys (12 % degree of quaternization and 165 µmole thiol group/gram polymer). Optimized nanoparticles were shown to have mean particle size diameter of 174 nm, zeta potential of 24.04 mV, PdI of 0.196 and EE of 98.35 %. In vitro release study of the optimized nanoparticles showed 71.29 % within 240 min. Key words: Insulin nanoparticles – Plackett-Burman design – Box-Behnken response surface methodology – Thiolated chitosan – Drug delivery.

Peptides and proteins as macromolecular drugs are poorly absorbed across gastrointestinal (GI) tract due to their high molecular weight. In addition, they are highly exposed to enzymatic degradation in GI tract. Micro- and nanoparticulate delivery systems can overcome these drawbacks as they can protect the drugs against the unpleasant environment of the GI tract, increase the chance of drug contact with the absorption sites and promote drug absorption via intestinal mucosa. Moreover, using mucoadhesive polymers in delivery system prolongs the remaining of the particles on the surface of the mocusa which leads to high local drug concentration in the mucus layer, decreases drug dilution and refusal by the luminal constituents [1, 2]. Tactics to increase the absorption of drug are based on mucoadhesive delivery system affording a sharp concentration gradient between delivery system and absorption membrane leading the driving force for passive drug uptake. So that uptake and bioavailability of drug may be increased which result in improve patient acceptability. Hence, mucoadhesion is a principle method for drug immobilization and controlled drug delivery [3-5]. The methods for producing nanoparticles are very divergent and contain solvent evaporation, interfacial polymerization and emulsion polymerizations. However, these methods have disadvantages such as; organic solvents residue, heat and strong agitation which are detrimental to sensitive biomaterials. Therefore, polyelectrolyte complexation (PEC) method, self-assembly between oppositely charged polymers and drugs, can be a good approach to produce nanoparticles. These types of nanoparticles make colloidal suspensions which have more stability and homogenous dispersity. Further advantages of this type of preparation are elimination of sonication and organic solvent. Also, PEC method can reduce the risk of drug degradation during the nanoparticle preparation [6]. Chitosan is biocompatible, biodegradable and non toxic with mucoadhesive and permeation enhancing properties. However, the major disadvantage of chitosan is its poor solubility at pH above 6.0 that prevents its permeation enhancing effect at the sites of absorption. To enhance the solubility of this polymer at a wide pH range and to

improve its mucoadhesion and permeation enhancing effects, different derivatives such as trimethyl chitosan (TMC) [7] triethyl chitosan (TEC) [8] N-diethyl methyl chitosan (DEMC) [9], N-dimethyl ethyl chitosan (DMEC) [10], trimethylated and triethylated 6-NH2-6-deoxy chitosan [11] have been synthesized. In recent years, thiolated chitosan has been developed and has been utilised for oral controlled drug delivery. This approach was based on the immobilization of thiol bearing moieties on the polymeric backbone of chitosan [12]. Such modification resulted in enhanced mucoadhesion and improved permeation [4]. Since, by thiolation of chitosan, the mucoadhesion is improved 140 folds as compared with unmodified chitosan, this polymer can be used for drug delivery via different mucosal routs such as buccal, ocular, nasal and oral [13-15]. The enhanced mucoadhesion is primarily due to the formation of covalent disulfide bonds between the thiolated chitosan and cysteine-rich subdomains of mucus glycoproteins due to disulfide exchange that leads to a gradient of drug concentration at the absorption site [3]. Until now, several thiolated chitosan derivatives including chitosan-thioglycolic acid [16-18], chitosan-thio butyl amidine [19], chitosan cysteine [20] and so on have been synthesized. Thiolated chitosan exhibits hydrophilic nature due to the presence of thiol groups with cationic properties on their side chains that lead to substantial electrostatic interaction between positively charged polymers and negatively charged molecules like DNA [3]. Therefore thiolated chitosan can be an efficient vector for gene delivery. In this work, two new generations of thiolated N-diethyl methyl chitosan and N-dimethyl ethyl chitosan were synthesized. Insulin nanoparticles were then prepared using PEC method. Following the screening study by Plackett-Burman design, critical variables such as; pH of the polymer, stirring rate and concentration ratio of the polymer/ insulin and their effect on particle size, zeta potential, polydispersity index (PdI) and entrapment efficiency (EE %), were also studied. Insulin nanoparticles were then optimized by Box-Behnken experimental design surface methodology. Stability of nanoparticles was studied for further in vitro, ex vivo and in vivo investigations.

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Preparation, design for optimization and in vitro evaluation of insulin nanoparticles integrating thiolated chitosan derivatives E. Mortazavian, M. Amini, F.A. Dorkoosh, H. Amini, M.R. Khoshayand, T. Amini, M. Rafiee-Tehrani

J. DRUG DEL. SCI. TECH., 24 (1) 40-49 2014

I. MATERIALS AND METHODS 1. Materials

Medium molecular weight of chitosan (95 % degree of deacetylation) was purchased from Primex (Iceland). N-methyl pyrrolidone (NMP), sodium chloride, triethylamine, methyl iodide, ethyl iodide were purchased from Merck (Darmstadt, Germany). Sodium borohydride (NaBH4) was obtained from Aldrich (UK). Formaldehyde, acetaldehyde and sodium hydroxide were obtained from Merck (Darmstadt, Germany). 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride (EDAC), N-hydroxysuccinimide (NHS) and L-Cysteine hydrochloride (Cys) were purchased from Sigma (St. Louis, Mo, USA). Insulin was obtained from Exir Pharmaceutical (Lorestan, Iran). Dialysing tube with a molecular cutoff of 12 kDa (D0530) was obtained from Sigma. Analytical grade Lichrosolve acetonitrile was purchased from Merck (Darmstadt, Germany). Ellman’s reagent [DTNB, 5, 5’-dithiobis (2-nitrobenzoic acid)] was purchased from Sigma. All other materials were of analytical grade and were used as received.

2. Synthesis of thiolated chitosan derivatives

2.1. Synthesis of quaternized ammonium of chitosan N-diethyl methyl chitosan (DEMC) and N-dimethyl ethyl chitosan (DMEC) were synthesized as previously described by Avadi et al. [9] and Bayat et al. [10], with minor modification. N-alkyl chitosan was synthesized via Schiff’s base reaction method. In the first step, 1 g of chitosan was dissolved in 100 mL of 1 % acetic acid then 2 mL formaldehyde (37 %) and acetaldehyde solution was added to achieve methyl chitosan and ethyl chitosan, respectively. After 1 h stirring, the pH was adjusted to 4.5 using 1 M NaOH and 2 g NaBH4 was added and stirring continued for 1 day. Then by adding 1 M NaOH and adjusting the pH of solution to 10, precipitate (methyl chitosan or ethyl chitosan) was obtained.The precipitant was removed by a 0.020 mm filter (Whatman, UK) and was washed with methanol for 2 days. In the second step, 500 mg of methyl chitosan or ethyl chitosan were dispersed in 25 mL NMP at room temperature while being magnetically stirred for 3 h. Ethyl iodide or methyl iodide was then added to obtain DEMC and DMEC, respectively. No sodium hydroxide and sodium iodide (NaI) were included at this stage in order to decrease O-methylation of chitosan. This dispersion was refluxed at 60 ˚C for 24h. Thereafter acetone was added and the precipitant (DEMC and DMEC) was obtained by filtration. Finally, purification of DEMC and DMEC was carried out through ion exchange of I- to Cl- with dialysis membrane against 10 % NaCl solution for 24 h. The purified polymers were precipitated with acetone. Quaternized ammonium of chitosan was then characterised by 1H-NMR using D2O as solvent.

Figure 1 - Chemical structure of a) chitosan, b) DEMC-Cys, c) DMEC-Cys.

3. Determination of the thiol group content

The amount of thiol groups on the thiolated polymer was determined using Ellman’s reagent as described previously by Marschuts et al. [19]. Briefly, 0.5 mg of thiolated polymer was dissolved in 500 µL of 0.5 M phosphate buffer pH 8.0. Then 500 µL of 0.03 % (m/v) of DTNB dissolved in 0.5 M phosphate buffer pH 8.0 was added. After incubation for 2 h at room temperature, the thiol group was determined spectrophotometrically at 405 nm wavelength (Optizen 2120UV Plus). The amount of thiol groups was estimated from the corresponding standard curve elaborated under increasing amounts of Cys.

2.2. Synthesis of thiolated quaternized ammonium of chitosan The chemical structure of thiolated polymers is shown in Figure 1. Thiolated polymers were synthesized by formation of amide bond between residual primary amino group of quaternized chitosan (i.e., DEMC, DMEC) and carboxylic group of Cys. Briefly, 800 mg of Cys was dissolved in 20 mL of demineralised water. To activate the carboxylic acid group of Cys, 760 mg of EDAC and 460 mg of NHS were added to achieve a final concentration of 200 mM. The solution was then incubated at room temprature for 2 h while stirred. Four hundred milligrams quaternized chitosan synthesized in previous section, was added to this solution. The pH of the whole solution was adjusted to 5.0 by 1 M NaOH and the reaction was conducted at room temperature for 5 h under light protection. The obtained DEMC-Cys and DMEC-Cys were dialyzed at 4 ˚C against aqueous HCl solution (pH 5.0) for 5 days. In the same way controls were prepared without EDAC and NHS. Polymer solutions were lyophilized and stored at 4 ˚C. The amount of free thiol group was determined by Ellman’s reagent [21].

4. Formation of disulfide bond

A 3 % (m/v) solution of each conjugate (i.e., DEMC-Cys and DMEC-CYS) was hydrated in 50 mM phosphate buffer pH 6.8 and incubated at 37 ± 5 ˚C under permanent shaking. At predetermined time intervals, aliquots of 200 µL of hydrated conjugates were withdrawn and 50 µL of 1M HCl was added to quench further reactions. The amount of remaining thiol groups was determined using Ellman’s reagent [21].

5. Determination of the molecular weight of derivatives by gel permeation chromatography

The molecular weight of chitosan, DEMC, DMEC, DEMC-Cys and DMEC-Cys was accurately determined using Knauer Gel permeation chromatography system which consists of G3000SWXL 300* 7 mm column, 5 um particle size and Knauer differential refractive index detector. The mobile phase, 0.2 M acetic acid and 0.1 M sodium acetate (acetate buffer pH 4.0), were used at a flow rate of 0.5 mL/min 41

Preparation, design for optimization and in vitro evaluation of insulin nanoparticles integrating thiolated chitosan derivatives E. Mortazavian, M. Amini, F.A. Dorkoosh, H. Amini, M.R. Khoshayand, T. Amini, M. Rafiee-Tehrani

J. DRUG DEL. SCI. TECH., 24 (1) 40-49 2014

7.1. Screening study Preliminary experiments were carried out based on prior knowledge from literature. Since by using change only one separate factor at a time study includes lots of tests and it is time consuming, so this method is not useful for gathering valuable information. PlackettBurman design is of particular help to eliminate the above problem. The Plackett-Burman design is a powerful and useful tool in searching for the key factors rapidly from a multivariable system [22]. It can provide some important information about each factor by relatively few experiments. In this study, Plackett-Burman design was employed to evaluate all main effective factors (independent variables) and to determine which factor affects the responses (dependent variables). In this design, 6 factors were examined in 17 trials at high level (+1) and low level (-1) (Table I). Also 4 dummy variables were used which allowed to estimate the variance of an effect and to verify the fitness of the first order model. The total number of dummy variables should not be less than one-third of all factors [23]. All the experiments were performed in triplicate. As shown in Table II, pH of insulin solution (X1), pH of polymer solution (X2), concentration ratio of polymer/insulin (X3), stirring rate (X4) and stirring time (X5) were considered as quantitative factors whereas polymer type (X6) was investigated as a categorical factor that has been analyzed in two levels. Y1, Y2, Y3 and Y4 were studied as responses including particle size, zeta potential, PdI and EE %, respectively.

at 25 ˚C. All samples used were filtered with a 0.22 µm filter. The chromatograms were collected and integrated by Chromgate software compatible with Knauer chromatographic systems.

6. Preparation of nanoparticles

Optimized insulin nanoparticles were prepared with experimental design study by PEC method through electrostatic interaction between positively charged polymer and negatively charged insulin [2]. To obtain such a complex, the insulin solution was added drop wise to the equal volume of the polymer solution. Before addition of insulin solution to polymer solution, both solutions were filtered through 0.22 µm pore size filter. Finally, the pH of colloidal nanosuspention was measured. In this study, nanoparticles from chitosan and DMEC were prepared as control samples. Briefly, chitosan, DMEC and insulin were dissolved in 1 % acetic acid, demineralised water and pH 2.0 HCl, respectively. The pH of chitosan and DMEC were adjusted to 5.0 with 1 M NaOH because over 90 % of amino groups were protonated at this pH and the pH of insulin solution was adjusted to 8.0.These nanoparticles were centrifuged at 12,000 rpm for 20 min at 4 ˚C. The supernatant was separated and collected for further experiments, and nanoparticles were resuspended in demineralised water.

7. Experimental design study

In this study, the first step is screening by using Plackett-Burman design. The second step is optimization by Box-Benken experimental design to investigate the physicochemical properties of insulin nanoparticles. Design-Expert (version 7.0.0; Stat-Ease, Inc., Minneapolis, Minnesota, USA) has been used for mathematical modeling and assessment of the responses.

7.2. Optimization After screening process, the most important factors were selected. Then the optimum level of these variables was determined by Box-Behnken design which is the most accepted response surface methodology (RSM). RSM allows estimation of the parameters of the quadratic model and requires fewer runs in case of three variables [24]. These significant factors include: concentration ratio of polymer/ insulin (X1), stirring rate (X2) and pH of polymer (X3). According to Table III, 17 runs were examined. In this design, 12 factorial points with 5 replicates at the center point for calculation of pure error sum of squares were studied. The mathematical relevance between the responses (Y1, Y2, Y3, and Y4) and independent variables (Xi) is displayed in Equation 1:

Table I - Independent variables in Plackett-Burman design. Variables

Low level (-1)

High level (+1)

pH of insulin solution (X1) pH of polymer solution (X2) Concentration ratio of polymer/insulin (X3) Stirring rate (X4) Time (min) (X5) Polymer type (X6) (categorical factor)

7 3 1:1 200 10 DEMCCys

9 6 3:1 700 40 DMECCys

Y = β0 + β1X1 + β2X2 + β3X3 + β12X1X2 + β13X1X3 + β23X2X3 + β11(X1)2 + β22(X2)2 + β33(X3)2

DEMC-Cys: thiolated diethyl. DMEC-Cys: thiolated dimethyl. Table II - Plackett-Burman experimental design. Run No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Independent variables (factors)

Eq. 1

Dependent variables (responses)

X1

X2

X3

X4 (rpm)

X5 (min)

X6

Y1 (nm)*

Y2 (mV)*

Y3 *

Y4 (%)*

9 7 8 9 8 8 9 9 7 7 9 7 8 8 7 7 7 8

6 6 4 3 4.5 4.5 3 6 3 3 6 6 4.5 4.5 3 6 3 4.5

1 3 2 1 2 2 3 1 1 3 3 1 2 2 1 3 3 2

200 700 450 200 450 450 700 700 700 700 200 700 450 450 200 200 200 450

10 10 25 40 25 25 40 40 10 10 10 40 25 25 10 40 40 25

DMEC-Cys DEMC-Cys DMEC-Cys DEMC-Cys DEMC-Cys DEMC-Cys DEMC-Cys DMEC-Cys DMEC-Cys DMEC-Cys DEMC-Cys DEMC-Cys DMEC-Cys DMEC-Cys DEMC-Cys DMEC-Cys DMEC-Cys DEMC-Cys

1980 ± 10 284 ± 15.39 438 ± 10.4 654 ± 25.00 276 ± 12.50 157 ± 17.92 388 ± 35.79 217 ± 30.53 1850 ± 20.2 872 ± 12.09 362 ± 32.31 275 ± 26.27 217 ± 19.42 185 ± 10.01 847 ± 15.09 510 ± 18.08 1340 ± 10.50 318 ± 9.01

15.1 ± 0.30 23.3 ± 2.85 17.4 ± 1.27 3.79 ± 0.63 25.9 ± 3.10 20 ± 1.76 22.2 ± 1.92 17.1 ± 0.8 14.2 ± 2.55 32 ± 0.87 17.6 ± 0.92 14.7 ± 1.45 26 ± 1.60 24.6 ± 1.45 4.01 ± 1.14 18.4 ± 1.43 20.6 ± 0.72 21.7 ± 2.09

0.329 ± 0.01 0.222 ± 0.02 0.299 ± 0.02 0.552 ± 0.01 0.186 ± 0.05 0.186 ± 0.03 0.398 ± 0.01 0.262 ± 0.04 1 0.848 ± 0.05 0.409 ± 0.05 0.33 ± 0.03 0.297 ± 0.02 0.193 ± 0.06 0.119 ± 0.08 0.473 ± 0.03 0.9 ± 0.02 0.227 ± 0.02

71.43 ± 3.6 95.98 ± 2.1 98.69 ± 1.92 73.09 ± 3.56 87.06 ± 2.15 87.33 ± 1.48 96.54 ± 1.93 96.56 ± 3.68 70.23 ± 4.7 50.35 ± 2.9 93.91 ± 1.43 96.83 ± 1.52 95.66 ± 2.66 97.51 ± 3.2 50.35 ± 1.21 96.38 ± 4.22 66.23 ± 2.94 87.6 ± 1.87

*Mean ± SD. 42

Preparation, design for optimization and in vitro evaluation of insulin nanoparticles integrating thiolated chitosan derivatives E. Mortazavian, M. Amini, F.A. Dorkoosh, H. Amini, M.R. Khoshayand, T. Amini, M. Rafiee-Tehrani

J. DRUG DEL. SCI. TECH., 24 (1) 40-49 2014

Table III - Box-Behnken experimental design. Run No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Independent variables (factors)

Dependent variables (responses)

X1

X2 (rpm)

X3

Y1 (nm)*

Y2 (mV)*

Y 3*

Y4 (%)*

3 1 3 2 1 3 2 2 1 2 1 2 2 2 2 3 2

200 700 450 700 450 450 450 450 450 450 200 200 200 700 450 700 450

5 5 6 4 4 4 5 5 6 5 5 4 6 6 5 5 5

185 ± 10.0 1860 ± 17.8 858 ± 15.1 201 ± 21.9 179 ± 35.2 204 ± 12.5 1510 ± 11.22 1900 ± 24.7 1990 ± 23.9 1750 ± 33.54 199 ± 27.65 206 ± 10.7 1210 ± 11.68 314 ± 10.8 1850 ± 31.8 188 ± 28.9 1160 ± 18.12

22.4 ± 2.3 15.5 ± 1.8 17.5 ± 2.75 22.7 ± 0.87 18.1 ± 1.41 29.6 ± 0.95 20.7 ± 0.51 24.6 ± 1.10 15.1 ± 3.10 20 ± 1.50 18.7 ± 2.94 23.2 ± 0.98 18.7 ± 1.94 24.7 ± 0.91 25.9 ± 0.75 23.9 ± 1.85 24.6 ± 1.29

0.649 ± 0.05 0.262 ± 0.02 0.491 ± 0.03 0.15 ± 0.02 0.162 ± 0.02 0.627 ± 0.08 0.23 ± 0.04 0.3 ± 0.03 0.6 ± 0.07 0.185 ± 0.01 0.295 ± 0.02 0.448 ± 0.05 0.322 ± 0.06 0.322 ± 0.03 0.299 ± 0.02 0.149 ± 0.02 0.338 ± 0.09

99.73 ± 1.15 64.55 ± 2.3 85.42 ± 3.4 92.3 ± 3.6 87.27 ± 2.9 99.75 ± 1.35 99.07 ± 3.98 98.84 ± 1.87 85.5 ± 1.00 89.66 ± 1.85 87.5 ± 2.61 90.88 ± 2.19 81.75 ± 3.27 77.23 ± 2.88 98.48 ± 1.31 99.76 ± 1.39 98.57 ± 3.85

*Mean ± SD.

where Y is predicted responses, β0 is intercept, β1, β2 and β3 are linear coefficients, β11, β22 and β33 are squared coefficients, β12, β13 and β23 are interaction coefficients, whereas X1, X2 and X3 are independent variables. With using this equation, it is possible to assess the linear, quadratic, and interactive effects of the independent variables on the responses properly. Equation 1 shows the coefficient of independent variables combined with the effect of these factors and their significance on the dependent variables as the responses. In the regression equation, a positive value displays an effect that favors the optimization because of synergistic effect, while a negative value indicate indirect relationship or antagonistic effect between factor and the responses [25]. The significance of these variables was determined by ANOVA through p-value less than 0.05. Also not significant lack of fit (p-value > 0.05) is favorable because it indicates that the suggested model is properly according to data obtained from different runs. To determine the relationship and interaction between the independent variables and responses graphically, the three dimensional surface plots were used in this study. The optimal points were obtained by solving the equation derived from the final model and grid search of RSM plots considering the constraints in which the particle size and PdI are in minimum whereas, zeta potential and EE % are at maximum levels. All the experiments were carried out in triplicate, and the averages were considered to be response.

EE % = (Total amount of insulin-non encapsulated insulin/Total amount of insulin) * 100

8. Characterization of insulin nanoparticles

10. Circular dichroism analysis

Eq. 2

After centrifuging of nanoparticles at 12000 rpm for 20 min at 4 ˚C, the supernatant was collected for determination of non-encapsulated insulin by HPLC as reported previously [26]. Fifty microliters of each sample were injected to Agilent 1260 infinity equipped with 1260 ALS auto sampler, 1260 Quat pump VL and 1260 DAD VL detector that was set at 214 nm. The column used for chromatography was MZ analytical PerfectSil Target (150*4.6 mm, 5 μm). Run time and flow rate were 10 min and 0.5 mL/min, respectively. Mobile phase was consisted of 30 % acetonitrile and 70 % buffer containing 0.1 M KH2PO4 and 1 % triethylamine adjusted to pH 2.8 with phosphoric acid. The data were obtained using Agilent Chemsation software. All samples were done in triplicate.

9. Determination of the morphology of the nanoparticles

The morphology of nanoparticles was visualized by scanning electron microscopy (SEM Hitachi, S4160, Tokyo, Japon). The nanoparticles were sputter-coated with gold for 10 min at 6 mA and 6 kV (DC) under argon gas and was observed for morphology at an acceleration voltage of 15kV. Particle size diameter was determined using Clemex particle image analysis software package.

8.1. Determination of particle size and zeta potential Particle size and zeta potential of the nanoparticles were measured by photon correlation spectroscopy and laser doppler anemometry, respectively, using a Zetasizer 3000HS (Malvern Instruments, Malvern, UK). The particle size distribution is reported as PdI. Nanoparticles were diluted with demineralized water that was previously passed through 0.22 µm filter. The samples were placed in the electrophoretic cell and the measurements were performed at 25 ˚C with a detection angle of 90 degrees. Each sample was measured three times, and values are presented as the mean ± standard deviation (SD).

Far-UV circular dichroism (Far-UV CD) spactra of insulin was performed after preparation of optimum nanoparticles to investigate potential changes in insulin structure using Aviv 215 spectrophotometer (USA) at room temperature. Far-UV region CD spectra were recorded in 260-190 nm, using a bandwidth of 1.0 nm, a step size of 1.0 nm and averaging time of 1 s. Each spectrum is an accumulation of 5 scans with the lamp housing purged with nitrogen to remove oxygen.

11. Stability study

Stability study of optimum DMEC-Cys nanoparticles was carried out as described previously by Sadeghi et al. [27]. The freeze dried nanoparticles which kept at - 4 ˚C, were analyzed for the loading efficiency (LE) of insulin at predetermined time points (0, 1, 2, 3, 4, 5, 6 months). The amount of insulin was measured by HPLC as previously described and the results were compared with the initial loading of the nanoparticle. The loading efficiency was measured as following formulation:

8.2. Determination of EE % of the nanoparticles Indirect method was used for determination of insulin encapsulation. In this way, EE % was determined by subtracting the total amount of insulin used for preparation of particles and amount of non-encapsulated insulin present in the supernatant, according to Equation 2:

43

J. DRUG DEL. SCI. TECH., 24 (1) 40-49 2014

Preparation, design for optimization and in vitro evaluation of insulin nanoparticles integrating thiolated chitosan derivatives E. Mortazavian, M. Amini, F.A. Dorkoosh, H. Amini, M.R. Khoshayand, T. Amini, M. Rafiee-Tehrani

LE = [(Total weight of insulin-weight of insulin in supernatant)/total weight of nanoparticle]*100

12. In vitro release study

In vitro release study was performed on the optimum nanoparticles in phosphate buffer pH 6.8 (USP 31 NF 26) compared with control samples. In order to provide sink condition, sufficient amount of freeze dried nanoparticles was placed in a tube containing 10 mL of release medium. The tube was placed on an oscillating water bath and incubated at 37 ± 0.5 ˚C. At predetermined time intervals, aliquot 1 mL of release medium and replaced with an equal volume of release medium preheated at 37 ˚C. The amount of insulin was established by HPLC as described previously. All tests were performed in triplicate.

II. RESULTS 1. Characteriation of thiolated quaternized ammonium of chitosan

1.1. Characterization of quaternized ammonium of chitosan The 1H-NMR spectra of synthesized quaternary ammonium derivatives of chitosan (i.e., DEMC and DMEC) have been illustrated in Figure 2. In 1H-NMR spectrum of DEMC, the signal at 1.3 ppm is attributed to —CH3 group of ethyl substituent (CH3—CH2—) and —CH2 group (CH3—CH2—) superimposed on the H2, H3, H4, H5 and H6 of the polymer backbone, at 3.2-4.2 ppm. The sharp signal at 4.8 ppm is related to D2O. Two different anomeric protons appeared at 5.0 ppm. Also the commentary of 1H-NMR spectrum of DMEC is same as DEMC. In order to diminish the ratio of chitosan O-methylation to N-methylation, NaOH and NaI were not used. Consequently at above conditions, intensity of the peak at 3.4 and 3.5 ppm that could be attributed to O-alky group was substantially decreased (comparing to Verheul’s method) [28]. As illustrated in Table IV, degree of quaternization (DQ) of DEMC is less than DMEC due to space hindrance of ethyl group (CH3—CH2—) in DEMC for attaching to amino group of methyl chitosan.

Figure 2 - 1H-NMR spectra of a) DEMC b) DMEC (without adding NaOH and NaI).

1.3. Characterization of thiolated quaternized ammonium of chitosan Cys was attached covalently to the primary amino groups of DEMC and DMEC under formation of amide bonds. Controls which are synthesized without EDAC and NHS, showed inconsiderable amount of free thiol groups demonstrated covalent bond between DEMC or DMEC and Cys. After lyophilization, thiolated conjugates “i.e. DEMC-Cys and DMEC-Cys” appeared as white, odourless powder with fibrous structure. The amount of thiol substitution and thiol oxidation are summarized in Table IV.

1.2. Characterization of quaternized ammonium of chitosan The 1H-NMR spectra of synthesized quaternary ammonium derivatives of chitosan (i.e., DEMC and DMEC) have been illustrated in Figure 2. In 1H-NMR spectrum of DEMC, the signal at 1.3 ppm is attributed to —CH3 group of ethyl substituent (CH3—CH2—) and —CH2 group (CH3—CH2—) superimposed on the H2, H3, H4, H5 and H6 of the polymer backbone, at 3.2-4.2 ppm. The sharp signal at 4.8 ppm is related to D2O. Two different anomeric protons appeared at 5.0 ppm. Also the commentary of 1H-NMR spectrum of DMEC is same as DEMC. In order to diminish the ratio of chitosan O-methylation to N-methylation, NaOH and NaI were not used. Consequently at above conditions, intensity of the peak at 3.4 and 3.5 ppm that could be attributed to O-alky group was substantially decreased (comparing to Verheul’s method) [28]. As illustrated in Table IV, degree of quaternization (DQ) of DEMC is less than DMEC due to space hindrance of ethyl group (CH3—CH2—) in DEMC for attaching to amino group of methyl chitosan.

2. Determination of molecular weight of derivatives

As previously reported, GPC analysis showed a scarcely decreased molecular weight of TMC due to the presence of NaOH that led to depolymerization of chitosan [28]. In this case, because of avoiding use of NaOH, hydrolysis was not detected. So, as illustrated in Table IV, not only reduction of molecular weight of these derivatives was not observed, but also the molecular weight of conjugates were increased after each reaction which could be attributed to addition of alkyl group and cysteine molecule onto the backbone of chitosan. Therefore, alkylation of chitosan in the absence of alkaline condition has been suggested.

3. Experimental design study

Table IV - Characteristic of chitosan and synthesized derivatives. Polymer

DQ (%)

–SH (µmol/g)

–S–S– (µmol/g)

Zeta potential (mV)

Mw (kg/ mol)

DEMC DMEC DEMC-Cys DMEC-Cys Chitosan

12 35 -

165 155 -

180 150 -

40 42.5 28 35 26.5

400 418 454 481 275

3.1. Placket-Burman design for screening of effective factors on the responses Plackett-Burman design was used for screening important factors to identify the independent variables which affect the responses. According to analysis of variance (ANOVA) table (data not shown) and considering p-value < 0.05, DMEC-Cys was more effective on minimizing particle size than DEMC-Cys polymer. On this basis, DMEC-Cys was used in the remaining studies. Factors affecting the particle size, zeta potential, PdI and EE % are summarized in Table V. To investigate the influence of pH of polymer

DEMC: diethyl methyl chitosan. DMEC: dimethyl ethyl chitosan. 44

Preparation, design for optimization and in vitro evaluation of insulin nanoparticles integrating thiolated chitosan derivatives E. Mortazavian, M. Amini, F.A. Dorkoosh, H. Amini, M.R. Khoshayand, T. Amini, M. Rafiee-Tehrani

J. DRUG DEL. SCI. TECH., 24 (1) 40-49 2014

Table V - Effective factors on responses from Plackett-Burman design. Response

Effective factor

Particle size Zeta potential PdI EE %

Type of polymer (DMEC-Cys) Concentration ratio of polymer/insulin Stirring rate, pH of polymer solution pH of polymer solution

PdI: polydispersity index. EE: entrapment efficiency.

solution, concentration ratio of polymer/insulin, and stirring rate on responses, the next studies were performed at pH range of 4.0 to 6.0, concentration ratio of 1:1 to 3:1, and stirring rate of 200 to 700 rpm while parameters such as pH of insulin solution and time were kept constant at 8.0 and 25 min, respectively.

3.2. Box-Behnken design and response surface methodology for optimization Based on the results of the screening study, significant variables which affect the responses were selected. Then Box-Behnken design was carried out for optimization of nanoparticles composed of DMECCys, in order to find optimum levels of the independent variables (Table III). Three significant variables including concentration ratio of polymer/insulin (X1), stirring rate (X2) and pH of polymer solution (X3) are selected from Plackett-Burman design, and were used to minimize the particle size, PdI and to maximize the zeta potential (in the range of 20 to 30) and EE %.

4. Characterization of nanoparticles

4.1. Nanoparticle size Nanoparticles with sizes ranging from 179 ± 35.2 to 1990 ± 23.9  nm were obtained using different Box-Behnken runs. Results are shown in Table III. Nanoparticles with the minimum particle size were achieved at run No. 5 and the maximum particle size fits to run No. 9. It is concluded from ANOVA results that, only pH of polymer solution (X3) has influence on the size of nanoparticles (p-value = 0.0277) whereas concentration ratio of polymer/insulin (X1) and stirring rate (X2) have no effect on particle size due to the fact that their p-values are more than 0.05. The three dimensional response surface plots are shown in Figure 3a. As can be observed in Figure 3a, at constant concentration ratio of polymer/insulin, the mean diameter of particle size, decreases with decreasing the pH of polymer solution and stirring rate. Quadratic model was the best fitted model for particle size. Lack of fit was not significant (p-value = 0.1099). Hence these results indicated that Equation 3 can be fitted on the data properly: Y = + 1634.00 - 349.13(X1) + 95.38(X2) + 447.75(X3) - 414.50(X1X2) - 289.25(X1X3) - 222.75(X2X3) - 350.50(X1)2 - 675.50(X2)2 - 475.75(X3)2

Eq. 3

where Y is predicted response for particle size, X1, X2 and X3 are concentration ratio of polymer/insulin, stirring rate and pH of polymer solution, respectively, (X1X2) is interaction coefficient of concentration ratio of polymer/insulin and stirring rate, (X1X3) is interaction coefficient of concentration ratio of polymer/insulin and pH of polymer solution, (X2X3) is interaction coefficient of stirring rate and pH of polymer solution, (X1)2, (X2)2 and (X3)2 are square coefficient of concentration ratio of polymer/insulin, stirring rate and pH of polymer solution, respectively.

Figure 3 - 3D response surface plots for a) size, b) zeta potential, c) PdI and d) EE % of nanoparticles composed of DMEC-Cys.

reduction in cell viability has been occurred due to high positive zeta potential [29, 30]. Acceptable range for zeta potential is 20-30 mV. Particles with surface charge more than 30 mV may show cytotoxicity on the epithelial cells whereas particles with surface charge less than 20 mV are more inclined to aggregate which results in instability of the nanosuspension. As described in Table III, zeta potential of particle size changed from 15.1 ± 3.10 mV (run No. 9) to 29.6 ± 0.95 mV (run No. 6).

4.2. Zeta potential Zeta potential is an important character for the stability of nanosuspension. Stability of nanoparticles can be ensured by electrostatic repulsion force between particles. In other words, the stability of nanosuspension can be guaranteed, when zeta potential rises up to 30 mV. On the other hand, cell viability can be influenced by surface charge of particle. Previous reports have been shown that 45

J. DRUG DEL. SCI. TECH., 24 (1) 40-49 2014

Preparation, design for optimization and in vitro evaluation of insulin nanoparticles integrating thiolated chitosan derivatives E. Mortazavian, M. Amini, F.A. Dorkoosh, H. Amini, M.R. Khoshayand, T. Amini, M. Rafiee-Tehrani

Regression analysis of variance showed that concentration ratio of polymer/insulin has the most influence on zeta potential (p-value = 0.0106). The three dimensional response surface plots are shown in Figure 3b. As can be observed in Figure 3b, there is a direct relationship between concentration ratio of polymer/insulin and zeta potential in a manner at constant stirring rate, zeta potential of nanoparticles increases with increasing concentration ratio of polymer/insulin. This can be attributed to an increase in the total mass of positively charged polymer which leads to an increase in zeta potential of nanoparticles. Linear model was the best fitted model for zeta potential. Also lack of fit was not significant (p-value = 0.3596). So, Equation 4 can be used to accurately predict the zeta potential of particles: Y = + 21.52 + 3.25(X1) + 0.48(X2) - 2.20(X3)

Table VI - Comparative values of predicted and experimental responses for optimized nanoparticles.

Eq. 4

Experimental responses (mean ± SD)

Predicted error (%)

Size (nm) Zeta potential (mV) PdI EE %

177 23 0.2 99.83

174 ± 17.94 24.04 ± 0.98 0.196 ± 0.05 98.35 ± 1.57

- 1.7 4.33 - 2.04 - 1.5

5. Optimization and model validation

The optimum nanoparticle formulation was obtained by BoxBehnken design (Table III) based on constraints of the physicochemical parameters for insulin nanoparticles. The optimum condition is at a 3:1 concentration ratio of polymer/insulin, stirring rate of 663 rpm and 4.83 pH of polymer (DMEC-Cys). The predictive and experimental responses for optimized nanoparticle formulation have been illustrated in Table VI. The physicochemical characterization of chitosan nanoparticles was 250 ± 38.8 nm, 18.5 ± 1.3 mV, 0.22 ± 0.04 and 70.74 ± 0.62 % and DMEC nanoparticles was 179 ± 9.5 nm, 22.5 ± 3.8 mV, 0.134 ± 0.03 and 87.33 ± 0.27 % for particle size, zeta potential, PdI and EE, respectively. The validity of Box-Behnken design for the optimization of insulin nanoparticle formulation is demonstrated by predicted error which is lower than 5 %. For validation of the model, five experiments were carried out by using the optimum condition as described above.

4.3. Polydispersity index Polydispersity index (PdI), an expression of homogeneity of nanosuspension, is ranged from 0 to 1. Where PdI tends to zero, the homogeneity of nanosuspension becomes higher than when PdI equals to 1. As depicted in Table III, PdI was fluctuating between minimum 0.149 ± 0.02 (run No. 16) and maximum 0.649 ± 0.05 (run No. 1). It is obvious from ANOVA Table that stirring rate is the most significant factor that affected PdI (p-value = 0.0026). As shown in Figure 3c, at constant pH, increasing the stirring rate leads to a decrease in PdI. Quadratic model is the best fitted model for PdI. Lack of fit is not significant (p-value = 0.2821). Thus, Equation 5 can be used to predict PdI:

6. Morphology of nanoparticles

Eq. 5

The morphology of insulin nanoparticles composed of chitosan, DMEC and DMEC-Cys, is shown in Figure 4. As it can be seen, particles have spherical shape and no aggregation has been occurred. SEM image showed the size of droplets was almost equal to actual size which was measured by nanosizer.

where Y is predicted response for PdI, X1, X2 and X3 are concentration ratio of polymer/insulin, stirring rate and pH of polymer solution, respectively, (X1X2) is interaction coefficient of concentration ratio of polymer/insulin and stirring rate, (X1X3) is interaction coefficient of concentration ratio of polymer/insulin and pH of polymer solution, (X2X3) is interaction coeffiecient of stiring rate and pH of polymer solution, (X1)2, (X2)2 and (X3)2 are square coefficient of concentration ratio of polymer/insulin, stirring rate and pH of polymer solution, respectively.

Figure 4 - SEM image of a) chitosan b) DMEC and c) DMEC-Cys nanoparticles.

4.4. Entrapment efficiency Entrapment efficiency (EE %) of insulin was over 90 % and was influenced by electrostatic interaction in PEC method. According to Table III, the lowest EE is 64.55 ± 2.3 % (run No. 2) and the highest EE is 99.76 ± 1.39 % (run No. 16). ANOVA results showed that concentration ratio of polymer/insulin has an influence on the EE % (p-value = 0.0179). The linear model is the best fitted model which was stablished for EE % by statistical analysis of the experimental data. Therefore, it is obviuos that there is a direct relationship between concentration ratio of polymer/insulin and entrapment efficiency which is clearly shown with three-dimentional model graph for EE % in Figure 3d. As it can be seen in Figure 3d, by increasing the concentration ratio polymer/insulin from 1:1 to 3:1, EE % was raised until the maximum level has been obtained. Lack of fit is not significant (p-value = 0.0707). Therefore, Equation 6 can be used to predict the EE %: Y = + 90.37 + 7.48(X1) - 3.25(X2) - 5.04(X3)

Predicted responses

where Y is predicted response for EE %, X1, X2 and X3 are concentration ratio of polymer/insulin, stirring rate and pH of polymer solution, respectively.

where Y is predicted response for zeta potential, X1, X2 and X3 are concentration ratio of polymer/insulin, stirring rate and pH of polymer solution, respectively.

Y = + 0.24 + 0.075(X1) - 0.10(X2) + 0.044(X3) - 0.12(X1X2) - 0.14(X1X3) + 0.075(X2X3) + 0.13(X1)2 - 0.031(X2)2 + 0.100(X3)2 E

Dependent variables

7. CD spectra of insulin released from nanoparticles

The CD spectra of the native insulin and insulin entrapped in nanoparticles were shown in Figure 5. In this figure two minima at 208 and 222 nm are observed which corresponded to the α-helix and β-sheet of insulin, respectively. A decrease in θ208 and an increase in θ223 indicated the stabilization of β-sheet structure. This suggest that insulin loaded DMEC-Cys nanoparticles system can carry insulin efficiently with preserving the integrity of structure.

8. Stability study of nanoparticles

The stability of optimum DMEC-Cys, DMEC and chitosan nanoparticles prepared by PEC method was followed up to 6 months and the results revealed that the insulin was stable in this method and a slightly decrease in loading was observed (data not shown).

Eq. 6

46

Preparation, design for optimization and in vitro evaluation of insulin nanoparticles integrating thiolated chitosan derivatives E. Mortazavian, M. Amini, F.A. Dorkoosh, H. Amini, M.R. Khoshayand, T. Amini, M. Rafiee-Tehrani

J. DRUG DEL. SCI. TECH., 24 (1) 40-49 2014

Through thiolation of DEMC and DMEC with cysteine, the obtained thiolated quaternized polymers showed both fixed positive charge and immobilized thiol group on polymeric backbone. Since in neutral and alkaline condition, thiol group (−SH) is capable of oxidation and is simply converted to anions (S−), it is necessary to avoid such conditions. Therefore, it can be concluded that pH value of thiolated polymers is a critical parameter. In addition, due to the presence of light which caused acceleration of oxidation, the reaction is continued in absence of light. In fact, inter and intra disulfide bonds have been occurred within the polymer itself. Also thiolated polymers can also form disulfide bonds with the mucus glycoprotein. Besides, in vivo studies have been proofed the pharmacologically efficacy of thiolated polymers in both oral and buccal delivery of peptides. For example, Bernkop-Schnurch et al. have been substantiated a significant reduction of blood glucose when administered orally by incorporating the insulin in a thiolated polymer [31-33]. On the other hand, previous study has been shown the prosperity of using of thiolated chitosan for buccal delivery of PACAP (pituitary adenylate cyclase-activating peptide) which is useful for treatment of type 2 diabetes [34]. In this study, by utilizing unmodified chitosan, PACAP was not at all uptaken from the buccal mucosa. In contrast, when using thiolated chitosan and administered in the form of buccal patch an absolute bioavailability of 1 % was achieved in pigs. Hence, it is supposed that thiolated quaternized ammonium of chitosan like DMEC-Cys could be a promising polymer to enhance insulin absorption via buccal mucosa in forthcoming studies. If the polymer solution shows a pH value above 5.0, these inter and intra disulfide bonds happen very quickly. Consequently, pH 5.0 is the best agreement between a rapid and slow reaction of thiol groups on the polymer structure [35]. The thiol group of these synthesized polymers is stable towards oxidation in dry form and in aqueous solution below pH 5.0 [36, 37]. In addition, the reaction is continued in absence of light as light can accelerate the oxidation process. Nanoparticulate delivery system has been used for macromolecule drugs like proteins and peptides as a safe carrier for drug delivery. Various methods have been used for preparation of insulin nanoparticles composed of chitosan. Ionotropic gelation of chitosan with tripolyphosphate (TPP) and PEC method are considered for fabrication of nanoparticles. Due to the advantages of PEC method including: easy and simple approach for production of insulin nanoparticle and higher insulin loading efficiency and zeta potential, PEC method seems to be more widely used in preparation insulin nanoparticles than ionotropic gelation [38]. Also, PEC could arrange interaction between chitosan derivatives and insulin in pH range from 6.5 to 8.0, with more than about 90 % of insulin association efficiency [6]. In addition, PEC nanoparticles implemented acceptable effect on particle size, zeta potential, encapsulation efficiency and the release of insulin [2]. Furthermore smaller particle and lower PdI have been accomplished by PEC method. In PEC and ionic gelation method, high pH would result in insulin nanoparticle with large particle size [38]. It is supposed that at low pH, compacted nanoparticles have been fabricated due to electrostatic interaction between polymer and insulin. Also, the experiment should be carried out at pH below 6.0 to avoid the oxidation of thiol group which occurs in neutral and alkaline environment [36]. Therefore, an acidic pH (pH < 6) is a prerequisite when working with these polymers (DEMC-Cys, DMEC-Cys). Due to formation of disulfide bond in pH > 6, it is understood that an increase in disulfide bond would lead to increase in the size of nanoparticles. Among two synthesized polymers in this research, DMEC-Cys was more effective on particle size than DEMC-Cys. This observation can be supported by the fact that DMEC was synthesized with 35 % DQ that leads to compacted particles in comparison with12 % DQ for DEMC and that is why DMEC-Cys conjugate was chosen for the subsequent experiments in this study. Chitosan has influence on zeta potential of nanoparticles. By

Figure 5 - Far-UV spectra of native insulin and insulin whithin optimum nanoparticles.

Figure 6 - Cumulative release of insulin from nanoparticles in phosphate buffer pH 6.8.

9. In vitro release study

In vitro release profile of insulin nanoparticles was performed in phosphate buffer pH 6.8. Cumulative release of insulin from optimized DMEC-Cys nanparticles compared with chitosan and DMEC nanoparticles which were considered as control samples, is shown in Figure 6. As it can be seen in this figure, insulin released from chitosan, DMEC and DMEC-Cys nanoparticles after 30 min were 6.53, 15.87 and 14.42 %, respectively. These results demonstrate that these nanoparticulate systems have a small burst release and sustain release characteristics, indicating appropriate interaction between insulin and polymers. It has been substantiated previously; loading drugs by PEC method has a relatively small burst release and sustain release characteristics [29]. According to Figure 6, in nanoparticles composed of chitosan, DMEC and DMEC-Cys the cumulative release of insulin was 24.03, 47.37 and 71.29 %, respectively, within 240 min.

III. DISCUSSION

Trimethyl chitosan (TMC) with high degree of quaternization (DQ); has better solubility and mucoadhesive properties compared to chitosan. But there is a challenge with using NaOH and NaI because; NaOH and NaI would lead the reaction to not only N-alkylation but also to O-alkylation. The efforts for increasing DQ; dramatically could increase the O-alkylation which compromises the solubility. Recently, Verheul et al. [28] introduced a two-step method for synthesis of O-methyl free TMC. Literature search did not show any reports detailing the preparation of O-alkyl DEMC and/or DMEC. O-alkylation of chitosan could be noted by the presence of the peak at 3.4 and 3.5 ppm in 1H-NMR spectra. Figure 2 clearly shows an insignificant amount of O-alkyl group at 3.4 and 3.5 ppm indicating that our preparation method has provided a facile and simple procedure for synthesis of trialkyl chitosan with very low O-alkylated degree. 47

J. DRUG DEL. SCI. TECH., 24 (1) 40-49 2014

Preparation, design for optimization and in vitro evaluation of insulin nanoparticles integrating thiolated chitosan derivatives E. Mortazavian, M. Amini, F.A. Dorkoosh, H. Amini, M.R. Khoshayand, T. Amini, M. Rafiee-Tehrani

increasing chitosan concentration, zeta potential increases which is due to availability of positively charged amino groups [29]. Therefore, it is expected that quaternized chitosan displays higher zeta potential than chitosan. As previously mentioned in Table IV, quaternized chitosan “i.e., DEMC and DMEC” had higher zeta potential than chitosan and even thiolated quaternized ammonium of chitosan “i.e., DEMC-Cys and DMEC-Cys”. The difference between zeta potential of quaternized ammonium of chitosan and thiolated quaternized ammonium of chitosan was due to the presence of some disulfide anions in thiolated polymers which lead to a lower zeta potential. In addition, at low pH of polymer, protonation of free amino group of chitosan will occur. Consequently, zeta potential of nanoparticles becomes higher. Formation of disulfide anion in pH > 6 which leads to low or negative zeta potential, is another reason for working in pH < 6 environment in this study. Also, high concentration of polymer; leads to increased zeta potential and EE %. This is due to sufficient supply of polymer which is available to encapsulate the insulin. The thiolated conjugates synthesized in this study show similar particle size, zeta potential and PdI but higher EE % when compared with the results reported by Sadeghi et al. [27] Circular dichroism (CD) spectra of insulin were measured to evaluate conformational changes of insulin after being released from the nanoparticles. Study on physicochemical stability of insulin, is an important issue because different physical forces like stirring, filtration and centrifugation might expose insulin to air/liquid or liquid/solid interfaces resulting in unpleasant effects and reduction of structural integrity. Compared with the native insulin, insulin released from nanoparticles displayed a very slightly difference indicating that no conformational change is induced during loading and encapsulation process [39-41]. Since mild condition has been used for preparation of nanoparticles, insulin remains stable in nanoparticles. Release study has been carried out in phosphate buffer pH 6.8 in which both insulin and polymer have poor solubility. Profile of insulin release can be affected by ionic interaction between insulin and polymer. As it is found in this study, the fast release profile of insulin is related to nanoparticles composed of DMEC-Cys. This observation can be justified by considering the fact that this polymer posses the highest solubility in aqueous media in comparison with control samples.

4. 5.

6. 7. 8. 9.

10.

11.

12. 13.

14. 15. 16.

* In this study, two thiolated quaternary ammonium of chitosan (DEMC-Cys and DMEC-Cys) have been synthesized. Nanoparticles containing DMEC-Cys conjugate has been optimized by experimental design. The most important factors affecting the responses were identified and the relationship between the factors was investigated by the response surface methodology. Using Box-Behnken design leads to optimized nanoparticles with minimum particle size, PdI and maximum zeta potential and entrapment efficiency. Morphological study substantiated the spherical formation of nanoparticle with no aggregation. Insulin preserves its native structure during preparation of nanoparticle. The results of in vitro release revealed suitable interaction between DMEC-Cys conjugate and insulin which seems to be a good candidate for further in vitro, ex vivo and in vivo experiments.

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ACKNOWLEDGMENT This study was part of PhD. Thesis supported by Tehran University of Medical Sciences (grant No: 12844).

MANUSCRIPT Received 23 May 2013, accepted for publication 5 September 2013.

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