Chitosan Loaded Mucoadhesive Microspheres of Gliclazide - Journal
Chitosan Loaded Mucoadhesive Microspheres of Gliclazide - Journal
Chitosan Loaded Mucoadhesive Microspheres of Gliclazide - Journal
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Prakash Rao B et al Formulation and Evaluation <strong>of</strong> <strong>Mucoadhesive</strong> Buccal Drug Delivery System <strong>of</strong> Metoprolol Tartrate by Using Central Composite Design<br />
<strong>of</strong> optimized formula found to be 0.673 which indicates the<br />
mechanism <strong>of</strong> release is non Fickian. The factor A with<br />
higher concentration shows the higher effect on value <strong>of</strong> the<br />
release exponent(n) than the factor B. At high level <strong>of</strong> factor A<br />
gave high value <strong>of</strong> n at all level <strong>of</strong> factor B which indicates that<br />
factor A has significant effect.<br />
Kinetics <strong>of</strong> Drug Release<br />
The drug release data was fitted into the different model like<br />
Korsmeyer Peppas , first order, zero order and Higuchi<br />
2<br />
eqation and shown very close and above 0.9 r values (Table 5).<br />
It suggests that the release <strong>of</strong> drug from the formulations may<br />
2<br />
follow any one <strong>of</strong> these models.The r values <strong>of</strong> first order <strong>of</strong><br />
all the formulations shows higher which indicate the drug<br />
release is directly proportional to the amount <strong>of</strong> drug<br />
remaining. But n values range from 0.484 to 0.673 which<br />
indicate non-Fickian diffusion mechanism. According to<br />
Higuchi model, the drug release from matrix is directly<br />
proportional to square root <strong>of</strong> time and explains the Fickian<br />
diffusion. It may be coincident. However, n values <strong>of</strong><br />
Korsmeyer-Peppas strongly indicates that diffusion<br />
mechanism is non-Fickian.<br />
ANOVA, Pure Error, Lack <strong>of</strong> Fit<br />
The result <strong>of</strong> ANOVA demonstrate that the model was<br />
singnificant for all dependent variables (Table 6). Regression<br />
analysis was carried out to determine the regression<br />
coefficients. All the independent variables ( Factors) were<br />
found to be significant for all R1, R2, R3 and R4 response<br />
variables. The quadratic model was found to be significant for<br />
R1. The linear model was found to be significant for R3 and<br />
R4. The 2FI model was found to be significant for R2. So,<br />
above result indicate that both the factors play an important<br />
role in the formulation <strong>of</strong> buccal tablet containing metoprolol<br />
tartrate. The data <strong>of</strong> pure error and lack <strong>of</strong> fit are<br />
demonstrated in (Table 6), which can provide a mean<br />
response and an estimate <strong>of</strong> pure experimental uncertainty.<br />
The residuals are the difference between observed and<br />
predicted value.<br />
Fig 11. DTA thermograms <strong>of</strong> (A) Metoprolol tartrate<br />
(B) HPC (C) Carbopol (D) Drug + HPC (E) Drug + Carbopol.<br />
2<br />
Table 5.Correlation coefficient (R ) <strong>of</strong> different models, drug release exponents(n), zero order release rate<br />
constants(K 0 ), First order release rate constant(K), Korsmeyer Peppas release constant(K KP)<br />
Kinetic pr<strong>of</strong>ile <strong>of</strong> Korsmeyer Peppas Zero order First order Higuchi<br />
formulation n K KP<br />
2<br />
R K 0<br />
2<br />
R K<br />
2<br />
R<br />
2<br />
R<br />
F-1 0.554 2.0792 0.969 0.123 0.989 -0.0021 0.989 0.980<br />
F-2 0.563 1.963 0.985 0.119 0.985 -0.00207 0.998 0.989<br />
F-3 0.488 3.186 0.995 0.112 0.979 -0.00204 0.997 0.996<br />
F-4 0.580 1.760 0.993 0.117 0.981 -0.00201 0.999 0.992<br />
F-5 0.543 2.630 0.964 0.158 0.995 -0.00386 0.923 0.953<br />
F-6 0.485 3.144 0.992 0.110 0.987 -0.00199 0.990 0.990<br />
F-7 0.559 2.0393 0.995 0.118 0.987 -0.00209 0.994 0.991<br />
F-8 0.673 0.888 0.994 0.112 0.996 -0.00176 0.991 0.980<br />
F-9 0.556 1.879 0.9973 0.118 0.984 -0.00203 0.996 0.984<br />
F-10 0.661 1.083 0.998 0.122 0.987 -0.00206 0.996 0.992<br />
F-11 0.506 3.123 0.960 0.150 0.997 -0.00354 0.942 0.959<br />
F-12 0.664 1.038 0.981 0.129 0.994 -0.00221 0.984 0.972<br />
F-13 0.576 1.763 0.973 0.119 0.984 -0.00203 0.996 0.984<br />
153<br />
RJPS, Jul - Sep, 2011/ Vol 1/ Issue 2