INTERNATIONAL JOURNAL OF PHARMACEUTICAL … 1205.pdf · Research Article CODEN: IJPRNK ISSN: 2277-8713

Research Article CODEN: IJPRNK ISSN: 2277-8713 Hassan M. Elsabbagh., IJPRBS, 2016; Volume 5(1): 45-67 IJPRBS

Available Online at www.ijprbs.com 45

ADOPTING FACTORIAL DESIGN FOR FORMULATION AND OPTIMIZATION OF POLYMERIC SPIRONOLACTONE- LOADED NANOPARTICLES

HASSAN M. ELSABBAGH*, OSAMA A. SOLIMAN, WALAA E. A. EL-HADY

Department of Pharmaceutics, Faculty of Pharmacy, Mansoura University, Mansoura, Egypt,

35516.

Accepted Date: 08/01/2016; Published Date: 27/02/2016

Abstract: The aim of the work in this study was to prepare eudragit RL100 based nanoparticles of spironolactone (SPL) by emulsification-solvent diffusion/evaporation technique. This technique was used to prepare the nanoparticles and then studying the effect of some independent variables viz drug concentration, polymer concentration and surfactant concentration on the dependent variables like particle size, polydespersity index (PDI), drug content (Q), drug entrapment efficiency % (DEE%) and percentage yield (%yield) with 23 full factorial design. The optimized nanoparticles formulations were subjected to evaluation by making in-vitro drug release, scanning electron microscope (SEM), transmission electron microscope (TEM), fourier transform infrared spectroscopy (FTIR), x-ray diffractometry (XRD), differential scanning calorimetry (DSC), and zeta potential (ZP) determination. The results revealed that the drug and polymer were not interacting together. The obtained nanoparticles were found to be smooth and spherical. Also the crystallinity of nanoparticles was found to be less than the pure SPL and the nanoparticles have a size ranged from 60 to 300 nm. The polymer controlled the drug release from nanoparticles but with an initial fast release to give immediate rapid effect in-vivo followed by a slow release phase.

Keywords: Spironolactone; Eudragit RL100; Nanoparticles; Emulsification-solvent diffusion/evaporation

technique; 23 full factorial design.

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1. INTRODUCTION

Spironolactone (SPL) is a low water soluble drug, chemically named as 7-acetylthio-3-oxo-17-

pregn-4-ene- 21, 17-carbolactone. It is a steroidal diuretic which is described as a light, cream-

colored to light tan, crystalline powder with a faint to mild mercaptan-like odor, practically

insoluble in water, soluble in alcohol and in ethyl acetate, freely soluble in chloroform and in

benzene, and slightly soluble in methyl alcohol and in fixed oils [1]. It is extensively metabolized

to 7-a-thiospirolactone, canrenone, 7-a-thiomethylspirolactone and 6-b-hydroxy-7-a-

thiomethylspirolactone. In man, 7-athiomethylspirolactone has been found to be the main and

active metabolite, followed by canrenone [2].

The purpose of this study was to formulate a delivery system for SPL using nanotechnology to

optimize its therapeutic benefit .Also the control of the drug release were one of our objectives

for the patient compliance.

Eudragits have been widely used for the formation of different sustained and controlled release

formulations [3]. Eudragit RL 100 is insoluble at physiological pH and capable of limited swelling,

thus appears to be a good polymeric carrier for the dispersion of drugs. It is a copolymer of poly

(ethylacrylate, methyl-methacrylate, and chloro trimethyl-ammonioethyl methacrylate)

containing an amount of quaternary ammonium groups between 8.8% and 12%. [4].

Optimized nanoparticles were prepared by adopting factorial design 23 with three

different independent variables at two levels. The independent variables were the concentration

of each of eudragit RL100 (XA), sodium dodecyl sulphate (SDS) (XB) and SPL (XC). The dependent

variables were drug entrapment efficiency % (DEE %), drug content (Q), percentage yield (%

yield), particle size and polydispersity index (PDI) from the prepared nanoparticles.

Physicochemical characterization of the nanosuspension was performed by measuring particle

size, zeta potential (ZP), PDI. Solid state characterization of the freeze dried nanoparticles was

performed by drug entrapment efficiency % (DEE %), in-vitro drug release, fourier transform

infrared spectroscopy (FTIR), differential scanning calorimetry (DSC) and x-ray diffraction analysis

(XRD). These techniques allow understanding the thermal behavior, drug crystallinity and

possible occurrence of drug polymer interaction for the freeze dried nanoparticles.



2. MATERIALS AND METHODS

2.1. MATERIALS

SPL was purchased from Sigma-Aldrich (Saint Louis, MO, USA). Eudragit RL 100 was obtained from

Röhm Pharma GmbH (Darmstadt, Germany). Acetone and methanol were obtained from El-Nasr

Pharmaceutical Chemical Co. (Cairo, Egypt). Sodium dodecyl sulphate (SDS) (Merck, Germany).

2.2. METHODS

Emulsification-solvent diffusion/evaporation technique [4-6] was used to prepare nanoparticles.

The drug and polymer were dissolved in acetone. This solution was dropped into aqueous SDS

solution using glass dropper at distance of 5 cm above the surface of external aqueous phase

under magnetic stirring (Heidolph, U.S.A.) after that, the solution was sonicated for 5 min using

ultrasonic homogenizer (Cole-Parmer Instrument Co., Chicago Illinos 60648) then magnetically

stirred at room temperature over night to evaporate the organic solvent. The obtained

nanoparticles were collected by centrifugation (10,000 rpm) for 1-h using a centrifuge (Sigma, D-

37520, Germany) and then washed with distilled water. The pure nanoparticles were freeze dried

using freeze dryer (SIM FD8-8T, SIM International, USA). The final lyophilized product of

nanoparticles was collected and stored at 4 OC for evaluation (Table 1, 2).

2.3. Characterization of the prepared nanoparticles

All the nanoparticles of the prepared eight formulae were subjected to evaluation for the Q, DEE

%, % yield, particle size analysis and PDI analysis.

2.3.1. Estimation of drug content (Q)

A standard calibration plot was used and is based on making standard solutions of the drug in a

mixture of methanol and 0.1 N HCL (1:4). Actual drug content (Q) was determined by dissolving

an accurately weighed sample (equivalent to the yield of each formula) of the dry nanoparticles

in 10 mL of methanol. The solution was then filtered and diluted with methanol and measured

spectrophotometrically at 242 nm [7] using UV–Visible double beam scanning

spectrophotometer (Labomed, INC, UVD-2950, USA). Each formula was evaluated in triplicate

and then the mean was taken.

2.3.2. Determination of drug entrapment efficiency % (DEE %)

DEE % was calculated for each formula according to the following equation [8];



DEE % = mass of drug in nanoparticles

mass of drug used in formulations × 100

2.3.3. Determination of percentage yield (% yield)

% Yield was calculated as the total weight of dry nanoparticles prepared for each formula in

relation to its sum of starting materials (drug and polymer) using the following equation [9];

% yield =Wm

W𝑡 × 100

Where, Wm and Wt represent weights of dry nanoparticles prepared and calculated weights of

drug and polymer, respectively.

2.3.4. Particle size analysis and polydispersity index (PDI)

Particle size and PDI of nanoparticles were measured using photon correlation spectroscopy

instrument (Zetasizer, ZEN 3600, Malvern Instruments limited, UK). Samples were diluted with

deionized water (1: 2). All experiments in this study were performed three times and the average

was taken.

3. Evaluation of nanoparticles of formula six (NP6)

Since nanoparticles of formula six (Table 3) experienced optimized independent variables with

the highest Q, DEE %, % yield and low particle size. The nanoparticles of this formula was selected

and subjected after preparation to in- vitro drug release, scanning electron microscope (SEM),

transmission electron microscope (TEM), fourier transform infrared spectroscopy (FTIR), x-ray

diffractometry (XRD), differential scanning calorimetry (DSC), and zeta potential (ZP)

determination.

3.1. Fourier transform infrared spectroscopy (FTIR)

Spectroscopic studies of SPL, eudragit RL 100, their corresponding physical mixture and drug-

loaded nanoparticles for NP6 were done by using Mattson 5000 FTIR Spectrophotometer

(Madison Instruments, Middleton, Wisconsin, USA). The samples were homogeneously mixed

with potassium bromide and infrared spectra were traced in the region of 4000- 400 cm-1.



3.2. Zeta potential determination of nanoparticles (ZP)

ZP measurement was performed on freshly prepared sample of optimized nanoparticles of

formula six by photon correlation spectroscopy instrument at 25 OC. For the determination of the

electrophoretic mobility, a sample was diluted with deionized water then placed in

electrophoretic cell and measured.

3.3. X-ray diffractometry (XRD)

X-ray diffraction patterns (XRD) of SPL, eudragit RL100, their corresponding physical mixture and

drug-loaded nanoparticles for NP6 were obtained using x-ray diffractometer (Diano X-ray

diffractometer equipped with Co Kα (USA), operated at 40 kV, 30 mA). The diffraction pattern

was recorded over a 2θ angular range of 5-80o with a step size of 0.05o in 2θ and a 0.5 Sec

counting per step at room temperature.

3.4. Scanning electron microscopy (SEM)

The shape and surface characteristics of dried nanoparticles of formula six were examined and

photographed using scanning electron microscopy (SEM) (S4800, Hitachi, Japan). Appropriate

samples were mounted on metal stub, using double sided adhesive carbon tapes. Samples were

gold coated and stubs were visualized under SEM at different acceleration voltage (15, 25, 30

kV).

3.5. Transmission electron microscopy (TEM)

The morphological examination of freshly prepared nanoparticles of formula six was performed

using transmission electron microscope (TEM) (JEOL-TEM, 100 CX, Japan). One mL of the freshly

prepared nanoparticles suspension was diluted tenfold with deionized water and sonicated for 5

min using an ultrasonic bath (Sonix, SS101H230, USA). One drop of sample obtained after dilution

was dropped onto Formvar-coated copper grids (200 mesh, Science Services, Munich, Germany)

and the excess material was removed with a filter paper leaving a thin film stretched over the

holes. After complete drying at room temperature, the image capture and analysis were

performed using digital micrograph and soft imaging viewer software.

3.6. Differential scanning calorimetry (DSC)

DSC was performed using differential scanning calorimeter model (Perkin-Elmer, New York, USA).

It was calibrated with indium (99.99% purity, melting point 156.6 OC). Ten mg samples of each of

SPL, eudragit RL100, their corresponding physical mixture (eudragit RL100: SPL in ratio of 10:3)



and drug-loaded nanoparticles of formula six were crimped in standard aluminum pans. Then,

they were heated from 35 to 300 OC at a heating rate of 10 OC/min under constant purging of dry

nitrogen at 20 mL/min. An empty aluminum pan was used as a reference pan.

3.7. In-vitro drug release

The release of SPL from nanoparticles was carried out using a USP type II dissolution apparatus

(paddle method) (Six-jars, USP rotating basket, dissolution test apparatus, DA-6D, India). A total

volume of 250 mL hydrochloric acid (HCl) as a dissolution medium of pH 1.2 was kept at 37±0.5oC

and rotated at 100 rpm. Accurately weighed sample of the dried nanoparticles (130 mg)

containing a known amount of SPL (20 mg) were introduced to the dissolution tester cells. At

predetermined time intervals (10, 20, 30, 45, 60, 90, 120, 180, 240, 300, 360 min) 3 mL of the

dissolution medium were taken and replaced with an equal volume of fresh dissolution medium

in order to maintain the sink condition throughout the experiment constant. The collected

aliquots were filtered and further analyzed for drug concentration using a UV–Vis

spectrophotometer at 242 nm. Each experiment was done in triplicate and the average

percentage dissolved was calculated at each time interval. Also the experiment was repeated

using 250 mL 0.1N HCl (pH 1.2) containing 0.1% SDS as surfactant [1, 7].

3.8. Kinetic analysis of the drug release data

To examine the kinetics of drug release, the release data were fitted into kinetic models like zero-

order, first-order, Higuchi's square root of time [10] and Korsmeyer-Peppas equation [11] in

order to determine the release mechanism and regression coefficients (r2).

The coefficients of determination were determined from regression plots of m vs. t, log (mO–m)

vs. t and m vs. t1/2, for zero-order, first-order, and Higuchi's model respectively. In these plots, m

represents the cumulative percent of drug released at time t and mO–m is the percentage of the

drug remained after time t. For Korsmeyer-Peppas, the equation was:

Mt/M∞= ktn

Where Mt /M∞ is the fraction of the drug released after time t and n is a characteristic exponent

for the release mechanism. According to Korsmeyer theory, if ‘n’ is 0.45 the drug release will

follow Fickian diffusion mechanism, for 0.45 < n < 0.89 follows Anomalous (non-Fickian) diffusion,

for n = 0.89 case II transport and for n > 0.89 diffusion mechanism will super case II transport

[11]. On the other hand, a unity value for n would be expected for zero-order release. Models

were evaluated using GraphPad Prism 5 software (GraphPad Software Inc., San Diego, CA, version

5.03) computer program.



4. Design of Experiment and Statistical Analysis

The design of experiment (DOE) technique was used to provide an efficient means to optimize

the emulsion solvent evaporation process. DOE is an approach for effectively and efficiently

explore the cause and effect relationship between numerous processes variables and the output.

An experimental design (23full factorial design) was followed to investigate the main effects and

interactions of independent variables on the physicochemical properties of SPL-eudragit RL100

nanoparticles, namely: eudragit RL100 concentration (XA), SDS concentration (XB) and SPL

concentration (XC) as shown in Table 1. Eight formulae (Table 2) each with three runs of SPL-

eudragit RL100 nanoparticles were prepared. The complete first order polynomial regression

equation was generated as follows:

Y=β0 +β1 XA +β2 XB +β3 XC +β4 XAXB+ β5 XAXC +β6 XBXC + β7XAXBXC

Where Y is the dependent variable, β0 is the arithmetic mean response of the eight runs, βï

corresponds to the multiple regression coefficients representing estimates of main effects and

interactions (including two and three variable interactions) of XA, XB and XC the independent

variables as reported in Table 1 (βï = estimated coefficient of the factor ).

The model was evaluated in terms of statistical significance using analysis of variance (ANOVA)

by Design Expert v.9.(Stat-Ease, Inc, Minneapolis, Min-nesota, USA). The surface-response plots

and contour plots were analyzed by fixing the XC factor at its high and low levels and varying XA

and XB over the range used in the study.

Table 1- Independent formulation variables and levels of a 23 full factorial design:

Maximum coded

Level

Minimum coded

level

Maximum

level

Minimum

level

Independent variable

concentration (%w/v)

+1 -1 3 2 Eudragit RL 100 (%w/v) XA

+1 -1 0.5 0.2 SDS (%w/v) XB

+1 -1 0.6 0.3 SPL (%w/v) XC



Table 2- The independent formulation variables and levels of a 23 full factorial design:

5. RESULTS AND DISCUSSION

5.1. Polynomial equations for five dependant variables

The five dependent variables which include Q, DEE %, % yield, Particle size and PDI were taken as

an indication of the reproducibility and efficiency of the processing technique. From the data of

experimental design and Parameters (Table 3) for factorial formulations NP1 to NP8, polynomial

equations for five dependent variables are as follows respectively:

Q= +11.84 +0.57XA -1.98 XB +4.18 XC -0.53XAB+0.28XAC -1.04XBC - 0.077XABC

Where F= 482.43, p< 0.0001, and adjusted R2=0.9932

DEE% = +52.11+2.48XA – 8.09XB +1.26XC -2.61XAB+0.36XAC- 1.98XBC+0.59XABC

Where F= 93.42, p< 0.0001, and adjusted R2=0.9657

% yield= +51.41 +4.26XA -17.44 XB +3.34 XC +2.72XAB +2.21 XAC- 2.31XBC - 2.67XABC

Where F= 183.93, p < 0.0001, and adjusted R2= 0.9823

Particle size= +172.22 -7.55XA +94.26 XB +13.87 XC +0.72XAB+7.83XAC +18.20XBC+3.78XABC

Independent variables levels in coded form Formula code

XC XB XA

-1 -1 -1 NP1

1 -1 -1 NP2

-1 1 -1 NP3

1 1 -1 NP4

-1 -1 1 NP5

1 -1 1 NP6

-1 1 1 NP7

1 1 1 NP8




PDI = +0.62 – 0.044XA +0.078 XB +0.079 XC - 0.045XAB+0.045XAC +0.064XBC+0.046XABC


The high R2 values indicate good fit.

The above equations represent the quantitative effects of process variables XA (eudragit RL100),

XB (SDS) and XC (SPL) and their interactions on the different responses. A coefficient with positive

sign represents a positive effect. This is depicted in the case of SPL concentration (XC) which was

the major factor affecting positively the above responses, where increasing SPL (XC) from 0.3 to

0.6% w/v and keeping XA and XB constant, increased Q from 9.34+0.2 to 20.48+0.3 mg (NP5 and

NP6, Table 3). Similarly, positive interactions between the independent variables represent a

synergistic one as XAC in the equations of all responses. The quantity of drug (Q) increased from

7.86+0.4 (NP1) to 20.48+0.3 mg (NP6) when XA and XC were at the highest concentrations of 3%

and 0.6% w/v respectively, while XB was constant at 0.2% w/v (Table 3).

On the other hand, the concentration of eudragit RL100 (XA) experienced a positive effect on Q,

DEE %, % yield with variable levels and a negative effect on particle size. Increasing eudragit

RL100 (XA) from 2 to 3% w/v and keeping XB and XC constant (NP2 and NP6) increased Q, DEE%

and % yield from 17.57+0.5 to 20.48+0.3 mg, 58.58+1.8 to 68.29+1.3% and 68.08+2.7 to

80.92+4.6%, respectively but decreased particle size from 77.85+ 2.6 to 69.41+1.5 nm (Table

3).

For the concentration of SDS (XB) experienced a positive effect on particle size and PDI but a

negative effect on Q, DEE %, % yield. Increasing SDS (XB) from 0.2% to 0.5% and keeping XA and

XC constant (NP1 and NP3) increased particle size and PDI from 94.59+3.7 to 252.83+22.4 nm and

0.52+ 0.02 to 0.73+0.1, respectively but decreased Q, DEE% and % yield from 7.86+0.4 to

6.87+0.13 mg, 52.45+2.7 to 45.82+0.9% and 66.53+1.1 to 25.5+1.8%, respectively. The amount

of stabilizer used has an effect on the properties of nanoparticles. If the concentration of

stabilizer is too low, aggregation of the polymer will happen, whereas, if too much stabilizer is

used, drug entrapment could be reduced as a result of the interaction between the drug and

stabilizer [12].

5.2. Particle size analysis

The particle size affects the biopharmaceutical, physicochemical and drug release properties of

the nanopaticles. A graphical representation of the particle size of eudragit RL100 nanoparticles



(NP6) obtained is given in Fig.1. Particle size is an important parameter because it has a direct

effect on the stability of the formulation. Larger particles tend to aggregate more than smaller

particles, resulting in sedimentation [12]. SDS above 0.25% w/v which is close to the critical

micelle concentration (CMC) of 0.23% w/v [13], when drug: polymer ratio is constant and

concentration of stabilizer increased from 0.2% to 0.5% particle size increased. This may be due

to the micelle formation of SDS which did not act any more to decrease the size.

Fig. 1 - Particle size distribution curve for NP6.

Table 3 - Properties of the SPL-eudragit RL100 nanoparticles prepared according to 23 full

factorial design:

Mean

particle size

(nm)

PDI % Yield Q (mg) DEE% SPL

concentration

(%w/v)

(XC)

SDS

concentration

(%w/v)

(XB)

Eudragit RL100

concentration

(%w/v)

(XA)

Formula

code

94.59+3.7 0.52+0.02 66.53+1.1 7.86+0.4 52.45+2.7 0.3 0.2 2 NP1

77.85+ 2.6 0.55+ 0.01 68.08+2.7 17.57+0.5 58.58+1.8 0.6 0.2 2 NP2

252.83+ 22.4 0.73+ 0.1 25.5+1.8 6.87+0.13 45.82+0.9 0.3 0.5 2 NP3

293.5+ 37.2 0.81 + 0.1 28.4+1.7 12.74+0.4 42.49+1.5 0.6 0.5 2 NP4

69.96+ 2.6 0.52+ 0.01 59.85+3.0 9.34+0.2 62.28+1.5 0.3 0.2 3 NP5



69.41+1.5 0.55+0.03 80.92+4.6 20.48+0.3 68.29+1.3 0.6 0.2 3 NP6

215.96+ 1.4 0.37+ 0.01 40.38+0.9 6.54+0.4 43.65+2.8 0.3 0.5 3 NP7

303.3+ 15.2 0.83+ 0.19 41.51+2.6 13.23+0.4 44.12+1.5 0.6 0.5 3 NP8

5.3. Response surface and contour plots

Graphs gave information similar to that of the mathematical equations obtained from statistical

analysis. The relationship between the dependent and independent variables interactions was

further elucidated using response-surface and contour plots as shown in Fig.2 (a-d) and Fig.3 (a-

d), respectively for Q and particle size values as examples. These types of plots were obtained by

fixing the XC factor (SPL) at its high and low levels and varying XA (eudragit RL100) and XB (SDS)

over the range used in the design. The contour plots reveal that at low level of SDS (XB), the

particle size was low whether SPL (XC) was at its high or its low level. On the other hand, at high

level of SDS (XB), Q was low. This means that in order to produce nanoparticles with high Q and

low particle size, the low concentration of SDS and high concentration of SPL and eudragit RL100

in the concentration range could be used.

Fig. 2 - Three dimensional surface plots showing the effect of the interaction between the

concentrations of both eudragit RL100 (XA) and SDS (XB) on particle size and drug content

at the minimum and maximum levels concentrations of SPL (XC) (a, b) and (c, d),

respectively.



Fig.3 - Contour plots representing the effect of the interaction between the concentrations

of both eudragit RL100 (XA) and SDS (XB) on particle size and drug content at the minimum

and maximum levels concentrations of SPL (XC) (a, b) and (c, d), respectively.

5.4. In-vitro drug release

In the first 10 min 15% drug was released from nanoparticles of formula six (NP6), while only

2.5% of raw drug was released (Fig. 4). This immediate release may be due to the drug present

at the surface of the particles. After the first hour the drug begins to release slowly. These results

revealed that the degradation of eudragit RL100 was a slow process because of its

hydrophobicity. Fig. 4 also shows the release of drug from NP6 and raw SPL in 0.1N Hcl in the

presence of 0.1% SDS. The raw drug was found to dissolve quickly but in the case of NP6 the

polymer controlled its release. This revealed that eudragit RL100 could be used to sustaine the

release of SPL. The result suggests that the drug entrapped in the nanoparticles hinders the drug

release which is biphasic i.e. an initial fast release followed by a slow release phase and this result

agreed with that obtained with Rajesh Katara et.al [4] who prepared eudragit RL 100-based

aceclofenac nanoparticles.



Fig. 4- In-vitro drug release of SPL and NP6 in 0.1N HCl and 0.1N HCl containing 0.1% SDS as

surfactant.

5.5. Kinetic analysis and mechanism of drug release

To study the kinetics and mechanism of drug release the dissolution data were fitted in different

kinetic equations. The coefficients of determination of the drug release kinetics (r2) and the

exponent “n” for Korsmeyer-Peppas equation are presented in Table 4. The results reveal that

the r2 values for Korsmeyer-Peppas kinetic were much closer to one than those of zero-order,

first-order and Higuchi's kinetics. So Korsmeyer-Peppas model is the best model to describe the

obtained results. The exponent “n” values were found to be 0.167 and 0.315. The values of n (<

0.5) indicate that the formula six (NP6) could be described as Fickian diffusion mechanism.



Table 4 - Kinetic analysis for the percentage drug released from eudragit RL100 -loaded

nanoparticles*:

Formula code

and release

medium

Coefficient of determination

(r2)

Korsmeyer-Peppas Main

transport

mechanism r2 n** K

Zero-

order

First-

order

Higuchi

model

NP6 in 0.1N

HCL

0.7710 0.8006 0.9426 0.9648 0.315 3.173 Fickian

NP6 in 0.1N

HCL containing

0.1% SDS

0.4430 0.6204 0.7030 0.9272

0.167

5.963 Fickian

*Analyzed by the regression coefficient method **Diffusional exponent indicative of the mechanism of drug release.

Since nanoparticles of formula six (Table 2) experienced optimized independent variables with

the highest Q, DEE% and % yield and low particle size, the nanoparticles were subjected after

preparation to TEM, SEM, XRD, DSC and FTIR and ZP were measured.

5.6. Transmission electron microscopy (TEM)

The photograph of the TEM reveals that the prepared nanoparticles have nearly spherical shape

and smooth surface showing encapsulated drug crystals with spherical shape and nano size

(Fig.5), this result also was found with Swarnali Das et al. who prepared amphotericin-B-loaded

nanoparticles using eudragit RL100 [14].



Fig. 5 - TEM image of SPL- eudragit RL 100 nanoparticles with high concentration of eudragit

RL 100(XA) and SPL (XB) and low concentration of SDS (XC) (NP6).

5.7. Scanning electron microscopy (SEM)

SEM revealed that all particles were spherical in shape. Also, the particles were non-porous and

smooth (Fig.6). This may be due to slow release of acetone during the last stage of the

evaporation process, this also concluded with Naik et al. who prepared glipizide loaded

nanoparticles using polycaprolactone as polymer [15].



Fig. 6 - SEM images of (a) raw SPL under 15kV at magnification power of 5.000 (b) eudragit

RL100 polymer under 15kV at magnification power of 200 (c) lyophilized eudragit RL100

loaded SPL nanoparticles under 25kV at magnification power of 30.000 (d) lyophilized

eudragit RL100 loaded SPL nanoparticles under 30kV at magnification power of 30.000.

5.8. X-ray diffraction studies (XRD)

The physical state of a drug may vary from molecular dispersion (amorphous) to well-defined

crystalline structures. Therefore, XRD was carried out to test the crystallinity of SPL in formula six

nanoparticles and compared with both the pure SPL, and its physical mixture with eudragit RL100

(Fig.7). The diffraction pattern of pure SPL exhibited high intensity peaks at 9.1, 15.9, 16.6, 17.2

and 20.3O (2θ), signifying its crystalline nature, (Fig.7a) and this result compared with that

obtained with Rani et al. [16]. While the polymer is found to be completely amorphous in nature

[17], entrapment of crystalline SPL (sharp intense peaks as seen in Fig.7a) into the polymeric

nanoparticles reduced its crystallinity to a greater extent (Fig. 7d). The intensity of crystal peaks



of SPL was higher in case of physical mixture (Fig. 7c) when compared with formula six

nanoparticles (Fig. 7d).

5.9. Differential scanning calorimetry (DSC)

The diffractograms of pure SPL, eudragit RL100, their physical mixture and formula six

nanoparticles are shown in Fig.8. The thermogram of SPL shows a characteristic endothermic

peak at 206.27 OC, which is in agreement with the enthalpy of fusion of SPL [18]. Although it is

not clearly visualized in the DSC thermogram of the physical mixture of SPL with eudragit RL100,

a small peak of SPL was detected with minimal shift by the DSC apparatus. This confirms its

crystalline nature within the physical mixture. The almost complete masking of SPL endothermic

peak in the physical mixture could be due to the low concentration of the drug compared with

eudragit RL100 (1 : 5) making it hard to detect by using DSC [19], but after SPL encapsulation in

the nanoparticles, Fig. 8D showed no endothermic peak of SPL due to the presence of very small

quantity of SPL in the lyophilized powder or because of the decreased crystallinity in the

formulation. Also, XRD and DSC studies verified the decrease in crystallinity of drug in polymeric

matrix. It indicates that SPL was encapsulated in eudragit RL100 nanoparticles. On the other

hand, the thermal curve of eudragit RL 100 is characterized by a broad endotherm at 66.663 OC

(Fig. 8B) [4].

5.10. FTIR spectroscopic analysis

Fig. 9A demonstrates the principal peaks of SPL at wave numbers 1769 cm-1, 1685 cm-1, 1188 cm-

1, 1137 cm-1, and at 1117 cm-1. The observed peaks were compared with Islam et al. [20]. The

FTIR spectrum of eudragit RL 100 (Fig.7B) exhibited FTIR absorption at 3447cm−1 (OH stretch),

2955.11 cm−1 (CH stretch), 1739cm−1 (CO stretch for ester) The observed peaks were comparable

with the findings of Basu et al [21]. The spectrum of the physical mixture (Fig.9C) of eudragit

RL100 with SPL shows the same bands of SPL and eudragit RL100. Thus, it could be confirmed

that no interaction existed between the drug and the polymer used. The spectrum of freeze dried

NP6 showed the characteristic peaks of eudragit RL100 at 3448 cm−1, 2952 cm−1 and 1733 cm−1

with disappearance of peaks at the range of 1600-1700 cm-1 corresponding to SPL in Fig. 9D

reveals that the drug is entrapped inside the eudragit RL100 nanoparticles.



Fig. 7 - XRD diffractograms of pure SPL (a), eudragit RL100 (b), physical mixture of SPL and

eudragit RL100 (c) and formula six nanoparticles (d)

Fig. 8 - DSC of pure SPL (A), eudragit RL100 (B), physical mixture of SPL and eudragit RL100 (C)

and formula six nanoparticles (D).



Fig. 9 - FTIR spectra of pure SPL (A), eudragit RL100 (B), physical mixture of SPL and eudragit

RL100 (C) and formula six nanoparticles (D).

5.11. Polydispersity Index Response (PDI)

The PDI value for nanoparticles of formula six was found to be 0.5 indicating a favorable particle

size distribution (PDI < 0.6). PDI which descibes the homogeneity of the nanoparticles. The PDI is

dimensionless and indicate that the sample is or not monodisperse [22].

5.12. Zeta Potential (ZP)

The ZP of nanoparticles is commonly used to characterize their surface charge property. The

polymer provided charges to the nanoparticles, conferring to a positive charge after washing due

to the presence of the quaternary ammonium groups on eudragit RL 100 as reported by

Pignatello et al. [23].



The value of ZP of the optimized nanoparticles of formula six (Fig.10) was found to be +8.04 mV

which is desirable to prevent particles self-association and coalescence. These results agree with

those obtained by Schiffelers et al. who reported that positive charge helps to attach particles to

the negatively charged cell membrane by electrostatic interaction [24].

Fig. 10 - Zetapotential distribution curve for NP6.



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