RESEARCH ARTICLE
OPTIMIZATION OF SUBLINGUAL TABLETS OF ZALEPLON
MANNITOL SOLID DISPERSION SYSTEM USING CENTRAL
COMPOSITE DESIGN
Darade Smita *, Kakad Prakash, Narkhede Minal
Dept of Pharmaceutics,
MGV’S Pharmacy College, Panchavati, Nasik, Maharashtra, India
*Corresponding author Email Id: smitadarade87@gmail.com
ABSTRACT
Due to presystemic metabolism Zaleplon, pyrazolopyrimidine class nonbenzodiazepine
hypnotic, shows 30 % bioavailability, hence in this study attempt has been done to develop
and optimize Zaleplon Mannitol solid dispersion contaning sublingual tablets by central
composite design.Superdisintegrants - Sodium starch glycolate and Croscarmellose Sodium
were used as independent variables and their effect on dependant variables- wetting time and
in-vitro dispersion time was studied. A quadratic model was used to evaluate the main
effects and interaction. Interaction of independent variables and dependent variables are
presented by Surface response plots. On the basis of desirability approach optimum level of
SSG 3.83 mg and CCS 4.12 mg were selected as optimized tablet formulation which gives
the predicted values of wetting
time and in-vitro dispersion time 20 sec and 24 sec
respectively. Further optimized formula tablet was showed 18± 1.73 sec wetting time and
25± 2.64 sec in-vitro dispersion time in evaluation. These observed responses were in close
accord with the predicted values of the optimized formulation, thereby demonstrating the
feasibility of the optimization procedure in developing sublingual tablets. All the
formulations showed hardness in the range 3.5 – 4.5 kg/cm2 and friability not more than 0.72
% , the theoretical value of drug content was found to be uniform in ranges from 97.70 to
100.48 % with average percentage deviation in acceptable Pharmacopoeial limits.
Keywords: Central composite design, wetting time, dispersion time, zaleplon sublingual
tablet
1
INTRODUCTION
Tablets that disintegrate or dissolve rapidly in the patient’s mouth are convenient for young
children, the elderly and patients with swallowing difficulties, and in situations where potable
liquids are not available. Since the drug can be absorbed partially or entirely into the system
circulation from blood vessels in the sublingual mucosa, the sublingual route bypasses the
hepatic first pass metabolic processes, thus producing rapid onset of action. The sublingual
route is appropriate for drugs with short delivery period requirements, for drugs which are
inactivated by first pass–intestinal or hepatic metabolism or inactivated by the proteolytic
enzymes in the GI tract, the highly vascularised oral mucosa through which drugs enter the
systemic circulation directly, thus bypassing the gastrointestinal tract and the first pass effect
in the liver.1, 2, 3
Zaleplon is a new nonbenzodiazepine hypnotic agent indicated for the short- term
treatment of insomnia. Work by interacting with benzodiazepine receptors.
4
Although
Zaleplon is well absorbed, its absolute bioavailability is approximately 30% because it
undergoes significant presystemic metabolism. It thereby makes it a suitable candidate for
sublingual dosage form.
5,6,7,8
The objective of the present investigation is to analyze the
effect of formulation variables on the properties such as wetting time, dispersion time in the
preparation of Zaleplon sublingual tablets.
Experimental designs also called designs of experiments, is an approach in the development
and optimization of drug delivery devices, by this method it is feasible to obtain the desired
formulation as quickly as possible while avoiding unnecessary experiments. The major
advantage of this method to develop pharmaceutical formulation is that the potential factors
could be studied simultaneously, systematically and quickly. By using design of experiments,
the effect of each formulation factor on each response can be evaluated and critical factors
can be identified based on statistical analysis. When the formulation and manufacturing
process of a pharmaceutical product are optimized by a systematic approach scale up and
process validation can be very efficient because of the robustness of the formulation and
manufacturing process. In a mixture experiments which is suitable for pharmaceutical
formulations, the independent factors are the components of mixture and the response is
dependant on the relative proportions of each ingredient. It involves changing mixture
composition and exploring how such change will affect the properties of mixture. 9
2
MATERIALS and METHODS
Materials
Zaleplon was supplied by Precise Chemipharma Pvt. Ltd. Mumbai, Mannitol, Sodium starch
glycolate, Croscarmellose sodium and aerosil purchased from Research Fine Chem, Mumbai.
All other materials were of analytical grade.
Methods
Traditionally pharmaceutical formulations are developed by changing one variable at a time.
By this method it is difficult to develop an optimized formulation, as it does not give an idea
about the interactions among the variables. A central composite design (CCD) is an effective
second-order experimental design associated with minimum of experiments to estimate the
influence of individual variables (main effects) and their second-order effects. Further, this
design has an added advantage of determining the quadratic response surface, not estimable
using a factorial design (FD) at two levels 10 .Hence, a central composite experimental design
with 2 factors, 2levels and 13 runs was selected for the optimization study. This design
consists of 4 full factorial design points, 4 axial points, and 5 center points 11. In this study,
amount of SSG and CCS were chosen as the independent formulation variables. The
dependent variables included wetting time (WT) and in vitro dispersion time (DT). The effect
of formulation variables on the response variables were statically evaluated by applying oneway ANOVA at 0.05 level using Design-Expert® 8 (Stat Ease, USA). The design was
evaluated using a quadratic model, which bears the form of the equation:
Y= b0 + b1 X1+ b2 X2 + b3 X1 X2 + b4 X1 2+ b5 X2 2
Where Y is the response variable, b0 the constant and b1 , b2, b3, b4, b5 is the regression
coefficients and X1, X2 are the independent variables levels of which were selected from the
preliminary experiments,X1 and X2 stand for the main effect; X1 X2 are the interaction terms
that shows how the response changes when two factors are simultaneously changed. X1 2 and
X2 2 are quadratic terms of the independent variables to evaluate the nonlinearity. 1, 11, 12
Experiments were carried out systematically to analyze the effect of different concentrations
of disintegrants on the wetting time and in-vitro dispersion time of the tablets, using a
response surface methodology and to develop an optimized formulation. As per composition
shown in Table 1, formulations were prepared according to the rotatable central composite
3
design by direct compression with 8mm punch (General Machinery Co., Mumbai) using
different proportions of studied superdisintegrants, mannitol as a diluent, sodium saccharin as
sweetening agent, aerosil with talc as a flow promoter. Mango flavor was used as flavoring
agent in tablet.
EVALUATION OF TABLETS
Hardness: The crushing strength of the tablets was measured using a Pfizer hardness tester.
Three tablets from each formulation batch were tested randomly and the average reading was
noted.13, 14
Friability: Friability test was performed according to I.P. using a Roche Friabilator (Kumar
Mfg. Ltd).Previously weighed twenty tablets were rotated at 25 rpm for four minute. The
weight loss of the tablets after measurement was calculated using the following formula13,14
Percentage friability = Initial weight – Final weight x 100
Initial weight
Weight variation: After compression, twenty tablets from prepared formulations were
selected randomly, weighed individually and calculated average weight. As per
Pharmacopoeial weight variation test, the individual tablet weights are compared with their
average weight.13,14
Content uniformity: To assure uniform potency for tablets of low dose drugs, content
uniformity test is performed. From each formulation batch, ten tablets were randomly
sampled, powdered, dissolved in methanol and sonicated for 20 min. The volume was make
up to 100 ml with distilled water. The solution was filtered through Whatman fil ter paper no.
41, suitably diluted and individually estimated for the drug content, using UV-VIS
spectrophotometer(UV-2450, Shimadzu) at 230 nm. The mean percent drug content was
calculated as an average of three determinations.1,15,21
Wetting time: This study is performed according to previously reported method by Sindhu
Abraham et al. Twice folded tissue paper (12cmx10.75cm )was placed in 9ml pH 6.8
simulating saliva in Petri dish having internal diameter 9cm.A tablet was placed on the paper
and the time taken for complete wetting was noted. Three tablets from each formulation were
randomly selected and the average wetting time was noted. 1,7
4
In-vitro dispersion time: In vitro dispersion time was measured according to previously
reported method by Sindhu Abraham et al. This method was performed by dropping a tablet
in a 10ml measuring cylinder containing 6ml of pH 6.8 simulating saliva fluid buffer
solution.
1, 7
Preparation and evaluation of optimized tablets batch (F): A numerical optimization
procedure using desirability approach was used to identify the optimal settings of the
formulation variables to obtain the target response. The optimized formula of the batch F is
given in Table 4, by direct compression. Further this batch was evauated, as per given in
previous section , for dispersion time, wetting time, hardness, friability, weight variation,
content uniformity tests.
In-vitro Dissolution: For optimized tablets dissolution was performed using USP Type II
paddle dissolution apparatus. (Lab India, Mumbai).Dissolution study was carried out at75
rpm in a 900 ml 6.8 pH phosphate buffer at 37±0.5 °C. Aliquots were withdrawn at time
intervals of 2,4,6,8,10…..30 min by replacing fresh dissolution at each interval, filtered
immediately through Whatman filter paper of 41 size, suitably diluted and analysed at
spectrophotometrically at 230nm. 1,7,15
RESULTS and DISCUSSION
An optimization using central composite design for 2 factors,5 levels offers an advantage of
fewer experimental runs (13runs) as compared with that of 2 factors, 5 levels full factorial
design, which requires 32 runs. After generating the model polynomial equation to relate the
dependant and independent variable, the combination was optimized for all 2 responses. The
final optimal experimental parameter were calculated using the optimization technique in this
design expert software which allows to compromise among various responses and searches
for a combination of factor level that jointly optimize a set of responses by satisfying the
requirement of each responses in the set. In the study the optimization was performed with
constraints for the responses. The design expert software gives 6 checkpoint solutions with
desirability value of one.16 The experimental runs and the observed responses of dependant
variables for all the batches are given in Table 2. The different levels of independent variable
combinations resulted in different wetting time and dispersion time values. The wetting time
and dispersion time of the best rapidly dispersing tablet formulation among those tested was
observed to be 7 and 12sec respectively. This indicates selected two independent variables
have a profound effect on the dependant variables. All the formulations showed hardness in
5
the range 3.5 – 4.5 kg/cm2 and friability not more than 0.72 % , the value of drug content was
found to be uniform in ranges from 97.70 to 100.48 % with average percentage deviation in
acceptable Pharmacopoeial limits. The percentage deviation for weight variation was within
the acceptable Pharmacoepial limits (± 7.5%).
The polynomial equation relating the responses and the independent variables was:
Wetting time =16- 3.84 X1-3.12 X2-0.50 X1X2-2.06 X12+0.69 X22 -----(2)
Dispersion time=21- 3.36 X1-3.00 X2-0.75 X1X2-1.88X12+0.87 X22----- (3)
The values of the coefficients X1-X2 are related to the effect of these variables on the WT
and DT. Coefficients of more than one, represents interaction and shows how the response
changes when two factors are simultaneously changed. Coefficients of higher order terms,
represents quadratic relationship and are included to investigate nonlinearity. The polynomial
equation can be used to draw conclusions after considering the magnitude of each coefficient
and the mathematical sign it carries (i.e., positive or negative). A negative sign of coefficient
for SSG(X1) and CCS(X2) represents antagonistic effect of these variables. A positive sign
of the coefficient represents increasing WT and DT with X1 and X2. The significance of the
different formulation variables and their interactions was compared using analysis of variance
(ANOVA) at a significance level of p<0.05. The ANOVA results of lack of fit and pure error
for independant variables provides the mean response and an estimate of pure experimental
uncertainty. The p<0.05 value for independant variables given in Table 3 suggested that the
both superdisintegrants have significant effects on the wetting and dispersion time.
Contour plots: Various RSM computations for the current optimization study were
performed employing Design Expert Software, Two –dimensional (2D) contour plots were
constructed based on the model polynomial functions using Design Expert Software.
Presentation of the data as graphs can help to show the relationship between the independent
and dependent variables. The plot for WT was found to be linear at high levels of X1 and X2
with slight curvature at low levels of X1 and X2. Similar changes observed with dispersion
time graph. It was determined from the contour plot that minimum values of WT and DT
could be obtained with increasing concentrations of an X1 and X2.The addition of
disintegrant to the tablet is usually necessary to achieve or improve the tablet disintegration.
The prediction of disintegration time of tablet formulations by mathematical model can be
difficult because of the numerous parameters influencing such response. In fact, the type and
6
concentration of disintegrant, the disintegration mechanisms (i.e., swelling or capillary
forces), and the compression force can affect the disintegration behavior in different ways17,
20.
However, in this study, this variable showed a satisfactory coefficient of determination.
This can be attributed to the lower level of interaction observed between independent
variables. As expected, due to the wicking action of disintegrants the tablet disintegration
time was primarily affected by the amount of superdisintegrants in the formulation
18,19
. The
SSG and CCS linear term were the primary factors responsible for the decrease in the tablet
wetting and dispersion time. This was followed by, the interaction between the 2 factors
(X1X2) and SSG quadratic term which also showed a negative effect on the response variable
that is decreasing wetting time and dispersion time. However, the increase of the
superdisintegrants concentration resulted in a negative effect, decreasing the disintegration
time .The response surface plots showing the effect of amount of SSG (X1) and amount of
CCS (X2) on the response WT (Y1) and DT (Y2) are shown in Figure 1.
The results in Table 5 demonstrated a good relationship between predicted and experimental
values, confirming the validity of the model. The hardness of F formulation batch was found
to be 3(±0.7)kg/cm2. The percentage friability of F was 0.68 %. The average drug content
was found to be 98.35 % of the theoretical value. The percentage deviation for 20 tablets was
within the acceptable Pharmacoepial limits (± 7.5%). The formulation F showed rapid
dissolution rate and 93.75 % cumulative drug release within 30 minutes.
CONCLUSION:
The effect of superdisintegrants on wetting time and in-vitro dispersion time of sublingual
tablets of Zaleplon solid dispersion was studied by central composite design (CCD) and
response surface methodology (RSM). The study demonstrated that SSG and CCS modifies
the wetting time and in vitro dispersion time. The optimum formula containing 2.55 and 2.74
% (w/w) of SSG, CCS respectively showed minimum wetting time and in vitro dispersion
time. At these conditions, the tablet showed a wetting time of 18 (± 1.73 ) sec and dispersion
time of 25 (±2.64) sec. It was observed that responses were in close accord with the predicted
values of optimized formulation, thereby demonstrating the feasibility of the optimization
procedure in developing sublingual tablet formulation.
7
ACKNOWLEDGEMENT:
The authors want to thank Precise Chemipharma Pvt. Ltd. Mumbai for providing gift
samples of Zaleplon.
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10
TABLES AND FIGURES:
Table 1: Composition of sublingual tablets of Zaleplon
a
-solid dispersion equivalent to 10 mg Zaleplon
INGREDIENTS(MG)
F1
F2
F3
F4
F5
F7
F8
F11
F12
70
70
Zaleplon-SDa
70
70
70
70
70
70
70
SSG
9
6
6
1.76
6
3
10.24 9
3
CCS
9
10.24
1.76
6
6
3
6
3
9
Saccharine sodium
3
3
3
3
3
3
3
3
3
Mango flavor
qs
qs
qs
qs
qs
qs
qs
qs
qs
Talc
2
2
2
2
2
2
2
2
2
Aerosil
1
1
1
1
1
1
1
1
1
Mannitol
56
57.76
66.24
66.24 62
68
57.76 62
Total
150
150
150
150
150
150
150
62
150 150
Table 2: CCD with the responses for wetting time and In-vitro dispersion time
Parameters
F1 F2 F3 F4
F5 F6 F7 F8 F9
Wetting Time
(sec) (Y1)
7
16 20 9
In vitro dispersion
time (sec) (Y2)
12 18 30 22
13 25 18
10 15
21 24 15 17 22
11
Table 3: Summary of ANOVA results
Soure
Sum of DF Mean
F
P
Squares
Square Value Value
Prob >F
Wetting time
Model
233.03
5
46.61
9.41
0.0052 Significant
X1
118.03
1
118.03 23.84
0.0018
X2
77.94
1
77.94
15.74
0.0054
X1 X2
1
1
1
0.20
0.6667
X1 2
29.59
1
29.59
5.98
0.0444
X2 2
3.29
1
3.29
0.66
0.4420
Residuals 34.66
7
4.95
Lack of
fit
34.66
3
11.55
Pure
error
0.000
4
0.000
Total
267.69
12
In-vitro dispersion time
Model
197.85
5
39.57
8.87
0.0061 Significant
X1
90.45
1
90.45
20.27
0.0028
X2
71.82
1
71.82
16.10
0.0051
X1 X2
2.25
1
2.25
0.50
0.5006
X1 2
24.46
1
24.46
5.48
0.0517
X2 2
5.33
1
5.33
1.19
0.3107
Residuals 31.23
7
4.46
Lack of
fit
31.23
3
10.41
Pure
error
0.000
4
0.000
Total
229.08
12
12
Table 4: Composition of optimized formulation (F)
Ingredients
Quantities (mg)
Zaleplon-SD
70
SSG
3.83
CCS
4.12
Saccharine sodium 3
Mango flavor
qs
Talc
2
Aerosil
1
Mannitol
66.05
Total
150
Table 5: Comparison chart of predicted and experimental values for optimized formulation
Dependent variables
Optimized formulation
Predicted value
Experimental Value
Wetting time (sec)
20
18 ± 1.73
In vitro dispersion time (sec)
24
25 ±2.64
13
Figure 1: Response surface plots showing the effect of amount of X1 and X2 on wetting time
fig. (A, A’), Dispersion time fig. (B, B’)
14