The aim of the present study was to develop stable nanoparticulate formulation for sustained release of Prednisolone. Chitosan nanoparticles were prepared by ionic gelation method using tripolyphosphate as cross-linking agent. Different nanoparticulate formulations were prepared by using 32 factorial design in which varying the concentration of chitosan (0.1% to 0.3%), concentration of tripolyphosphate (0.02% to 0.03%) as two factors. The effect of these factors on the particle size, % entrapment efficiency and in vitro drug release was evaluated to develop an optimized formulation.
Particle size, % entrapment efficiency and in vitro release of optimized formulation were found to be 168.1nm, 78.53% and 70.80% respectively. ANOVA study applied with p < 0.01 suggests that model is significant & Contour, Surface response & overlay plot was contract to optimize the formulation. Optimized formulation (C-10) showed sustained drug release at the end of 11th hour compared to other formulations. Based on release kinetic model, the drug release data fit well to higuchi model (r2 = 0.9935) indicating the diffusion limited drug release from nanoparticles. Drug release mechanism according to Korsmeyer-Peppas model was found anomalous transport (n = 0.5847). Scanning electron microscopy (SEM) revealed that the nanoparticles were spherical in shape and there was no crystallization of drug and other excipients. Drug-excipients compatibility confirmed by FTIR study.
Keywords: Prednisolone; Chitosan; Nanoparticles; Ionic gelation method; SEM
Inflammatory bowel disease (IBD) represents a group of idiopathic chronic inflammatory intestinal conditions that covers a group of disorders in which the intestines become inflamed (red and swollen), major type of IBD as crohns & ulcerative colitis [1-3]. Oral drug delivery system play promising role to treat above disease but having some limitation such as presystemic elimination, absorption drug through stomach unable to target the intestine as site of action. Nanoparticles are defined as particulate dispersions or solid particles with a size in the range of 10-1000nm. Prednisolone is anti-inflammatory actions of glucocorticoids are thought to involve phospholipase A2 inhibitory proteins, lipocortins, which control the biosynthesis of potent mediators of inflammation such as prostaglandins and leukotrienes [4-6]. Present research has been focused on the preparation of nanoparticles using biodegradable hydrophilic polymers such as chitosan by ionic gelation method.
The method involves a mixture of two aqueous phases, of which one is the polymer chitosan, a di-block co-polymer ethylene oxide or propylene oxide (PEO-PPO) and the other is a polyanion sodium tripolyphosphate. In this method, positively charged amino group of chitosan interacts with negative charged tripolyphosphate to form coacervates with a size in the range of nanometer. Coacervates are formed as a result of electrostatic interaction between two aqueous phases, whereas, ionic gelation involves the material undergoing transition from liquid to gel due to ionic interaction conditions at room temperature [7-8]. Resulting approach used for prolonged and/or controlled drug delivery, Improvement of oral bioavailability, Targeted drug delivery to the specific sites, Minimize fluctuation within a therapeutic range, Decreasing dosing frequency, Patient compliance is also improved [9-12]..
Prednisolone was obtained from Cadila healthcare pvt ltd Ahmadabad, Chitoson, Schiff’s reagent purchased from Chemdyes Corporation, Rajkot, India. Sodium tripolyphosphate purchased from Molychem, Bombay, India, Pluronic F-127, Mucin was obtained from Sigma Aldrich, Mumbai, India All other solvent and reagents were of analytical grade.
In the present work, Prednisolone was estimated by UVVisible
Spectrophotometric method using dissolution media
phosphate buffer saline (PBS) pH 7.4. Preparation of phosphate
buffer saline (pH 7.4)  All ingredients were dissolved in 1
liter of distilled water and pH was adjusted to 7.4 with 1M NaOH
(Sodium hydroxide) (Table 1).
100 mg Prednisolone was weighed accurately using digital
analytical balance and transferred to 100 ml volumetric flask
dissolved in phosphate buffer saline pH 7.4 and the final volume
was made up to 100 ml with phosphate buffer saline pH 7.4 to
get a stock solution A (1000 μg/ml). From the stock solution A,
10 ml was pipette out into 100 ml volumetric flask and the final
volume was made up to 100 ml with phosphate buffer saline pH
7.4, to get stock solution B (100 μg/ml) .
From the stock solution B, further serial dilutions were
made with phosphate buffer saline pH 7.4 to get the solutions
in the range of 4-20 μg/ml concentration. The absorbance
of the samples was recorded at 248 nm using UV-Visible
spectrophotometer against phosphate buffer saline pH 7.4
solution as blank.
Fourier transform infrared spectroscopy was carried out for
solid samples to detect if any interactions were present between
the drug and polymers . The samples were prepared by the
potassium bromide disc method. Powders were triturated in a
small size glass mortar and pestle until the powder mixture was
fine and uniform. The pellets were prepared by compressing the
powders at 20 psi for 10 min using potassium bromide - press.
Pure KBr powder was used as background, and for baseline
correction. Prepared sample disc was placed in a sample holder.
Afterwards, the sample was transferred to sample compartment.
Samples were scanned in the region of 4000-400 cm-1 using a
brucker FTIR spectrometer.
Chitosan Nanoparticles were prepared by ionic gelation
method. First of all measured quantity of chitosan polymer
was dissolved in 1%v/v acetic acid solution in one beaker.
Solublize Pluronic F-127 in above solution. In another beaker,
prepare solution of tripolyphosphate containing drug in
distilled water. Add chitosan solution drop wise to the solution
of tripolyphosphate under gentle magnetic stirring at room
temperature for 1 hr. In all cases, the volume ratio of Chi: TPP
solution was 2:1. Nanoparticles formed spontaneously in
suspension form and freeze dried it  (Table 2).
Preliminary batches further evaluated for to study the
influence of polymer, stabilizer, cryoprotectanat on performance
of Nanoparticle. The particle size & PDI, % Entrapment efficiency
and % drug release study were performed details procedure
mentioned in section of characterization.
To study all the possible combinations of all factors at
all levels, a two-factor, three-level full factorial design was
constructed and conducted in a fully randomized order .
The dependent variables measured were particle size (Y1), %
entrapment efficiency (Y2) and in vitro drug release (Y3) in
phosphate buffer saline (pH 7.4). Two independent variables,
the concentration of chitosan (X1) and the concentration of
tripolyphosphate (X2) were set at three different levels.
High and low levels of each variable were coded as +1 and -1,
respectively and the mean value as zero. 0.1%, 0.2% and 0.3%
are low, medium and high level respectively for concentration of
chitosan and 0.02%, 0.03% and 0.04% are low, medium and high
level respectively for TPP concentration this design was selected
as it provides sufficient degree of freedom to resolve the main
effects as well as the factor interactions. The conc. Of Stepwise
regression analysis was used to find out the control factors that
significantly affect response variables (Table 3).
The mean vesicle size and vesicle size distribution was
obtained by Zeta sizer. 1 ml suspension was diluted to 100 times
with the deionized water. The sample was analyzed using Zeta
sizer (Nano ZS, Malvern) .
% Entrapment efficiency of nanoparticle was determined by
ultra filtration method. 2 ml of Nanoparticles suspension was
placed into a centrifugal tube which was centrifuged at 10,000
rpm for 15 min at 25°C. The amount of free drug in supernatant
was detected by Shimadzu UV1800. The amount entrapped drug
was calculated as a result of initial drug minus free drug .
Entrapment efficiency = weight of initial drug weight of free drug
Weight of initial drug
Mucoadhesion studies of nanoparticles were performed by
mucus glycoprotein assay. Schiff colometric method was used
for determining the amount of free mucin to find out amount of
adsorbed mucin on the nanoparticles. Calibration curve of mucin
was prepared. For that standard solutions of mucin (125, 250,
325, 500 μg/ml) were prepared in distilled water. These samples
were incubated at 37°C in a water bath for 1 hour. Then, at room
temperature, 0.20 ml Schiff reagent was added to the samples.
After 30 minutes the absorbance of the solution was recorded at
556 nm in an ultraviolet spectrophotometer 
A standard calibration curve was plotted to calculate the
mucin content adsorbed to nanoparticles. Secondly determine
the mucoadhesion of the nanoparticles, for that 10 mg of the
nanoparticles were dispersed in 20 ml of the mucin solution (0.5
mg/ml). The suspensions were incubated for 1 hour at 37°C with
shaking. 0.2 ml Schiff reagent was added to the above solution
and kept it at room temperature for 30 min. In order to analyze
unadsorbed free mucin, the suspensions were then centrifuged
at 12,000 rpm for 5 minutes, and the supernatants were analyzed
by spectrophotometer at the visible wavelength of 556 nm.
Phosphate buffer saline (PBS) pH 7.4 was selected for
the release medium. The lyophilized Prednisolone loaded
nanoparticles were suspended in 5 ml phosphate buffer saline
(PBS) at pH 7.4 to form the suspension and transferred into
a pre- swelled dialysis bag (MW cut-off: 12,000-14,000 Da).
The dialysis bag was immersed in 100 ml PBS (pH 7.4). The
release study was performed at 37°C and 100 rpm in a constant
temperature shaker. After selected time intervals, 5 ml dialysis
solution outside the dialysis bag was withdrawn for UV-Vis
analysis and replaced with 5 ml fresh buffer solution. Then
their absorbance was determined at 248nm by UV-Visible
The shape and surface morphology of the nanoparticles
were studied using scanning electron microscopy (SEM).
Nanoparticles were fixed with carbon tape, mounted on metal
stubs and then coated with platinum, keeping the acceleration
voltage at 10 kV .
Korsmeyer et al. (1983) derived a simple relationship which
described drug release from a polymeric system equation
Qt/Q∞ = KKp.tn
Where, Qt/Q∞ = fraction of drug released at time t, KKP =
korsmeyer-peppas rate constant compromising the structural
and geometric characteristics of the device,
n = release exponent, which is indicative of the mechanism of
drug release [24,25]. To study the release kinetics, data obtained
from in vitro drug release studies were plotted as log cumulative
percentage drug release versus log time (Table 4).
Calibration curve of Prednisolone was prepared in phosphate
buffer pH 7.4 at λmax 248 nm. Slope and regression value
(r2) was found to be 0.0493 and 0.9978 respectively (Table 5)
(Figures 1 & 2).
FTIR Spectra of Prednisolone: FTIR spectra of pure drug
Prednisolone is shown in fig. 3 and its interpretation is given in
(Table 6) (Figure 3).
All characteristic peak of drug and polymer were present
in FTIR of drug and excipients (Figure 4). In the FTIR Spectra,
Prednisolone shows characteristic peak at 1653 cm-1 (carbonyl
group), 3455 cm-1 (hydroxyl group), 3045.17, 3356.56 cm-
1(aromatic ring), 1357.08, 1443.59 cm-1(C-H bending vibration).
The peaks were also appearing in mixture in Prednisolone and
chitosan polymer. So FTIR gave conformation about their purity
and showed no interaction between drug and polymer .
Here, concentration of chitosan was increased from batch
F-1 to F-6 respectively and at that time other components were
kept constant. (Table 7) shows the results for particle size and
% entrapment. From the result it was seen that particle size of
chitosan nanoparticles increases as concentration of chitosan
was increased. As concentration of chitosan increased, viscosity
of solution increased which prevents effective ionic interaction
between tripolyphosphate and chitosan solution that increased
the size of nanoparticles and percentage of entrapped drug was
found to be above 60. From above batches F-1, F-2, F-3 were
selected for factorial design which contains 0.1%, 0.2% and
0.3% concentration of chitosan respectively.
Here, concentration of TPP was decreased gradually from
batch F-7 to F-12 and at that time other components were kept
constant (Tables 4 & 5) shows the results for particle size and %
entrapment (Table 8). From the result it was seen that particle
size of chitosan nanoparticles decreases as concentration of TPP
was decreased. This could be due to the decrease in the amount
of anionic groups in the preparation medium, which causes less
electrostatic interaction with positive amino sites on chitosan
and drug entrapped in the nanoparticles was above 60%. From
above batches we show that better results were obtained when
concentration of TPP was between 0.02% to 0.04% so we
selected 0.02%, 0.03% and 0.04% as low, medium and high level
in factorial design respectively.
Screening batches F-13 to F-18 were prepared for screening
of pluronic F-127 as stabilizing agent. Here, concentration
of pluronic F-127 was increased from batch F-13 to F-18
respectively and results are shown in (Table 9). From the result
it was shown that particle size decreased as concentration of
pluronic F-127 increased and polydispersity index (PDI) also
decreased. Stabilizer was used to stabilize the formulation. When
concentration of stabilizer was low, aggregates were formed due
to less stability of particles, so size of particle was increased
and PDI was also reduced as concentration of stabilizer was
increased which indicate presence of monodisperse particle
in formulation. From above batches, F-16 batch contains 3%
pluronic F-127 was selected to use in factorial batches.
Cryoprotectant was added to the formulation before freeze
drying process to prevent damage of internal structure of
formulation and prevent formation of aggregates and stabilize
the nanoparticles. Here different cryoprotectants with different
concentrations were selected and results were showed in (Table
10). From result one showed that lactose gave better results than
PDI value and no aggregates were formed after freeze drying
process (Figure 5).
The particle size and size distribution of the Prednisolone
loaded nanoparticles in aqueous solution were determined by
dynamic light scattering (DLS) and the results were displayed
in (Table 11). Particle size is very useful in understanding
various properties of the nanoparticles for example dispersion,
aggregation and it also affects the biological uptake of the
particles. The nanoparticles should be small enough to improve
drug delivery, lower the toxicity and for longer duration of time
at the site of delivery; they are around 200 nm with particle size
distribution (PDI below 0.500). The polydispersity index (PDI)
suggested that the obtained Prednisolone loaded nanoparticles
were monodisperse and did not aggregate in water. Such ranged
nanoparticles may accumulate more readily at the inflammatory
At least 80% of Prednisolone was entrapped in the
nanoparticles it was observed that there was increase in %E.E
with increase in amount of polymer and cross-linking agent.
Hence more time may require by drug molecules for diffusing
out of polymer matrix as polymer concentration and crosslinking
concentration increases because it form more crosslinked
structure of particle.
As polymer concentration increase, mucoadhesion property
of nanoparticles was also increased. High mucoadhesivity of
the nanoparticles is attributed to the hydrogen bond and ionic
interaction of the positive charge of chitosan amino groups with
mucin chains. Smaller particles show higher mucoadhesion
than for larger paticles because small particles provide large
surface area and increase in mucin adsorption, which lead to a
high mucoadhesive property for the nanoparticles as shown in
(Figure 7) (Table 13).
The release profiles of different Prednisolone loaded
nanoparticles were investigated in phosphate buffer saline pH
7.4 solution at 37°C. All nanoparticles exhibited a fast release of
Prednisolone at the initial stage and a sustained release in the
following time. As concentration of polymer and cross-linking
agent was increased more cross-linked structure was formed
which took more time to diffuse out drug from polymer matrix
so it sustained the release of drug. Drug release from higher
polymer concentration and TPP concentration were slower than
lower polymer concentration and TPP concentration (Table
14) (Figure 8). are show that nanoparticles of Prednisolone
give biphasic release behavior. After the initial burst release
for about 3 hr., the release rate of Prednisolone slow down and
follow Higuchi model. The burst release of nanoparticles might
be due to the diffusion of drug that was adsorbed on the surface
The r2 value is considered as the tool for repressing the
best fitting kinetic model. The value of regression correlation
coefficient for most of the formulations was highest in case of
zero order release, so drug release from nanoparticles followed
zero order release (Table 15). Drug release mechanisms of the
nanoparticles were evaluated using the Korsmeyer -Peppas
model. In this model, the value of n identified the release
mechanism of drug. The n value for most of the batches was
found between 0.5 and 1, which confirmed that mechanism of
drug release follows an anomalous transport.
Statistical analysis was carried out for the data of particle
size, % entrapment efficiency and in vitro release study. These
three factors were considered as dependent variables for the
study. Analysis and optimization were carried out by using
design expert 184.108.40.206 software.
ANOVA for response surface quadratic model for particle size
was found to be significant as p-value for the model is 0.0011
which is less than 0.05 (Table 16). Both the independent factors
are having p-value less than 0.05 indicating the significant effect
of the factors on the response. Interaction p-value was 0.4799
which indicates that there was no significant interaction between
factors. r2 value was found to be 0.9953 indicating the linearity
of the model. Above equation represents the quantitative effect
of the independent factors on the particle size written in terms
of coded factors. Polynomial equation obtained indicated that
both the factors have same effects on the particle size. It showed
that factor A (concentration of chitosan) have positive effect on
particle size i.e. as the A increases particles size also increases.
Factor B (concentration of TPP) also have positive effect on the
particle size i.e. as the B increases particle size also increases.Factor B (concentration of TPP) also have positive effect on the
particle size i.e. as the B increases particle size also increases.
The response (Y1) obtained at various levels of the 2
independent variables (X1 and X2) were subjected to multiple
regression to yield a second-order polynomial equation (full
model). Equation clearly reflects the wide range of values for
Particle size = +182.56 +19.03 * A +0.90 * B +0.75 * A*B -0.93
* A2 +1.37 *B2
The positive effect of concentration of chitosan & TPP on
particle size i.e. increases as concentration increases.
ANOVA for response surface quadratic model for %
entrapment efficiency was found to be significant as p-value
for the model is 0.0110 which is less than 0.05 (Table 16).
Factor A (concentration of chitosan) have p-value of 0.4399
which indicated that factor A has insignificant effect on the %
entrapment efficiency. While p-value for factor B was 0.0014
which indicated that it has significant effect on the % entrapment
efficiency. Interaction p-value was 0.9969 which indicates that there was no significant interaction between factors. r2 value was
found to be 0.9778 indicating the linearity of the model. Above
equation represents the quantitative effect of the independent
factors on the % entrapment efficiency written in terms of coded
factors (Table 17).
The response (Y1) obtained at various levels of the 2
independent variables (X1 and X2) were subjected to multiple
regression to yield a second-order polynomial equation (fullmodel). Equation clearly reflects the wide range of values for
% EE = +72.54 +0.43 * A +5.50 * B +2.500E-003 * A*B +0.54
* A2 -0.12 *B2
Polynomial equation obtained indicated that only factors B
have effect on % entrapment efficiency. It showed that factor B
(concentration of TPP) have positive effect on % entrapment
efficiency i.e. as the B increases % entrapment efficiency also
ANOVA for response surface quadratic model for In vitro
release of drug was found to be significant as p-value for the
model is 0.0044 which is less than 0.05 (Table 17). Both the
independent factors are having p-value less than 0.05 indicating
the significant effect of the factors on the response. Interaction
p-value was 0.3778 which indicates that there was no significant
interaction between factors. r2 value was found to be 0.9880
indicating the linearity of the model. Above equation represents
the quantitative effect of the independent factors on the in vitro
release written in terms of coded factors (Table 18).
Polynomial equation obtained indicated that both the factors
have same effects on the in vitro release. It showed that factor
A (concentration of chitosan) have negative effect on in vitro
release i.e. as the A increases in vitro release decreases. Factor B
(concentration of TPP) also have negative effect on the in vitro
release i.e. as the B increases in vitro release decreases
In vitro release = +71.34 -2.71 * A -2.06 * B +0.28 * A*B -0.94
* A2 -0.23 *B2
(Figures 9 & 10) shows that as the concentration of chitosan
increases particle size also increased and as the concentration of
TPP increases particle size found to be increased slightly means
it has very less effect on particle size. The smallest particle
size area is corresponds to blue region of the graphs which
represents lowest concentration of chitosan and TPP. Contour
plot and response surface plot for % Entrapment efficiency: As
the concentration of TPP increased entrapment efficiency also
increased. Concentration of chitosan does not have any effect
on the entrapment efficiency. Red region in the graph shows
the highest entrapment efficiency which corresponds to higher
concentration of TPP (Figures 11 & 12).
Contour plot and response surface plot for % Drug release:
As the concentration of chitosan increases in vitro release
is decreasing and as the concentration of TPP increased in
vitro release was found to be decreasing. This shows that as
concentration of chitosan and TPP increased it sustained the
release of drug for longer duration of time because of cross
linking between polymer and cross-linking agent. The slower
release of drug is corresponding to blue region of the graphs
which represents highest concentration of chitosan and TPP
(Figures 13 & 14).
Overlay plot was obtained by superimposing the critical
response contours on a contour plot. Graphical optimization
displays the area of feasible response values in the factor space.
Regions that do not fit the optimization criteria are shaded. The
yellow region indicates the area in which optimized formulation
can be formulated. The yellow portion covered one point that
near to (-1,+1) value that means formulation C-7 (Figure 15).
Evaluation of Check Point Batch
To determine, whether the selected model was correct or
not, check point batch was prepared. Quantity of the ingredients
was chosen from the Design- Expert version 220.127.116.11 software. It
provides theoretical results. Same quantities of ingredients were
taken and check point batch was formulated and evaluated for
the desired responses (Figures 16 & 17) (Table 19).
Shape and surface morphology were investigated using
scanning electron microscopy (Figures 19 & 20) of check point
batch indicates that the cross-linked chitosan nanoparticle
possessed a nearly smooth surface and spherical shape.
Prednisolone loaded chitosan nanoparticles were prepared
by ionic gelation method. In this method chitosan was cross
linked with tripolyphosphate. The nanoparticles were spherical
in shape. The optimized formulation showed particle size around
168 nm with good entrapment efficiency. In vitro evaluation
shows that the nanoparticles seem to be a sustained dosage
form of Prednisolone for inflammatory bowel disease. Factorial
design indicates that higher concentration of chitosan leads to
increase in particle size and sustained release of drug and higher
concentration of tripolyphosphate leads to higher entrapment
efficiency and sustained release of drug from nanoparticles.