Role of Aminated derivatives of Natural Gum in Release Modulating Matrix Systems of Losartan Potassium:
Optimization of Formulation using BoxBehnken Design
Shankar B. Kalbhare^{1}*, Dr. Vivek Kumar Redasani^{2}, Mandar J. Bhandwalkar^{3}, Rohit K. Pawar^{3},
Avinash M. Bhagwat^{1}
^{1}Assistant Professor, YSPM’s Yashoda Technical Campus, Satara (M.S.) India.
^{2}Director, YSPM’s Yashoda Technical Campus, Satara (M.S.) India.
^{3}Assistant Professor, Late Narayandas Bhawandas Chhabada Institute of Pharmacy, Satara (M.S.) India.
*Corresponding Author Email: kirankal786@gmail.com
ABSTRACT:
The aim of the present research work was to systemically device a model of factors that would yield an optimized release modulating dosage form of an antihypertensive agent, losartan potassium, using response surface methodology by employing a 3factor, 3level BoxBehnken statistical design. Independent variables studied were the amount of the release retardant polymers – aminated fenugreek gum (X_{1}), aminated tamarind gum (X_{2}) and aminated xanthan gum (X_{3}). The dependent variables were the burst release in 15 min (Y_{1}), cumulative percentage release of drug after 60 min (Y_{2}) and hardness (Y_{3}) of the tablets with constraints on the Y_{2} = 31–35%. Statistical validity of the polynomials was established. In vitro release and swelling studies were carried out for the optimized formulation and the data were fitted to kinetic equations. The polynomial mathematical relationship obtained Y_{2}=32.912.29X_{1}5.68X_{2}0.97X_{3}+0.20X_{1}X_{3}0.005X_{2}X_{3}0.92X_{1}^{2}1.89X_{2}^{2} explained the main and quadratic effects, and the interactions of factors influencing the drug release from matrix tablets. The adjusted (0.9842) and predicted values (0.9600) of r^{2} for Y_{2} were in close agreement. Validation of the optimization study indicated high degree of prognostic ability of response surface methodology. The BoxBehnken experimental design facilitated the formulation and optimization of release modulating matrix systems of losartan potassium.
KEYWORDS: Release modulating matrix tablets; Amination of natural polymers; Losartan potassium; Box Behnken statistical design; Response surface methodology.
INTRODUCTION:
A polymer is a large molecule (macromolecules) composed of repeating structural units. These subunits are typically connected by covalent chemical bonds. Both synthetic and natural polymers are available but the use of natural polymers tier pharmaceutical applications is attractive because they are economical, readily available and nontoxic. They are capable of chemical modifications, potentially biodegradable and with few exceptions, also biocompatible [5]. Derivatization of native polymer led to enhancement in bioadhesive and drug release characteristics [6]. Recently, chemical modification or derivatization of natural polysaccharides has been reported to improve the functional properties of native gums. Reports in the literature suggest that the derivatives of polysaccharides (amine, thiol, carboxymethyl) can be employed to manipulate swelling, bioadhesion and drug release [7]. A few examples of polysaccharide derivatives already reported in literature include aminated fenugreek gum [6], aminated tamarind kernel polysaccharide [8] and aminated xanthan gum [9]. Polymeric material have fulfilled different roles such as binders, matrix formers or drug release modifiers, film coating formers, thickeners, viscosity enhancers, stabilizers, disintegrants, Solubilisers, emulsifiers, suspending agents, gelling agents and bioadhesive.
Losartan potassium (LP) is a potent, highly specific angiotensin II type 1 (AT1) receptor antagonist with antihypertensive activity [10], [11]. It is readily absorbed from the gastrointestinal tract with oral bioavailability of about 33% and a plasma elimination halflife ranging from 1.5 to 2.5 h. Administration of LP in a controlled release dosage form with dual release characteristics i.e., burst release followed by an extended release over 8 h, would be more desirable as these characteristics would allow a rapid onset followed by protracted antihypertensive effects by maintaining the plasma concentrations of the drug well above the therapeutic concentration [12].
Response surface methodology (RSM) is one of the popular methods in the development and optimization of drug delivery systems [13]. Based on the principles of design of experiments (DOE), the methodology involves the use of various types of experimental designs, generation of polynomial mathematical relationships and mapping of the response over the experimental domain to select the optimum formulation [14]. Central composite design (CCD), 3level factorial design, Box Behnken design and Doptimal design are the different types of RSM designs available for statistical optimization of the formulations [13]. BoxBehnken statistical design is one type of RSM design that is an independent, rotatable or nearly rotatable, quadratic design having the treatment combinations at the midpoints of the edges of the process space and at the center. Additionally, it requires fewer experimental runs and less time a and optimized thus provides a far more effective and costeffective technique than the conventional processes of formulating and optimization of dosage forms [15].
The current study aimed at developing and optimizing an oral release modulating matrix tablet of LP using computer aided optimization technique i.e. Box Behnken statistical design with constraints on cumulative percentage release of drug after 60 min (31–35%). The Independent variables for the present study were: amount of release retardant polymers – aminated fenugreek gum (X_{1}), aminated tamarind gum (X_{2}) and aminated xanthan gum (X_{3}). The dependent variables studied were the burst release in 15 min (Y_{1}), cumulative percentage release of drug after 60 min (Y_{2}) and hardness of the tablets (Y_{3}).
MATERIAL AND METHODS:
Materials:
Losartan potassium was provided as a gift sample by Viraj Pharmaceutical. (Mumbai, India). Carbopol, magnesium stearate and microcrystalline cellulose were supplied by Thermosil Fine Chem industry. (Charhol). Feenugreek gum, tamarind gum and xanthan gum were purchased from Phyto Lifesciences Pvt Ltd. (Gandhinagar, Gujarat). Starch, isopropyl alcohol and ethylene diamine as a supplied by SD. Fine Chemicals limited. (Mumbai, India). Sodium borohydride was purchased from Karan enterprise. (Mumbai, India). All other reagent and solvents used were of analytical grade and used as received.
Amination of natural polymers:
In 3000ml water add 60gm of natural gum. To this solution add aminating agent ethylene diamine (25ml) with continuous stirring at constant temperature (2060°C) for (6 hr). Then slowly add reducing agent sodium borohydride (NaBH_{4}) for 2 hr until formation of thick gel. Wash this gel several times with ethyl alcohol and collect the precipitate of aminated derivative [6], [8], [9]. Synthesized aminated polymer was studied under further parameter for determination of flow properties, chemical stability and thermal properties.
Preparation of compressed matrix:
Drug, carbopol (binder) and the MCC (diluent) were sifted through #40 manually and mixed well to ensure the uniformity of premix blend [16]. Several drugdiluents premixes were then mixed with the selected combination and ratio of hydrophilic polymers (Aminated FG, Aminated TG and Aminated XG), previously sifted through #40, for 5 min. Premix blend was wet granulated with isopropyl alcohol and the granules were sized through #18 and were dried at 45°C for 15 min. Dried LP granules were lubricated with starch and magnesium sterate. The tablets were compressed at an average compression weight of 250mg by cold compression technique on dialed hydraulic press (KBR press) at 12.0mm, circular, flat punches at compressional pressure of 5 tons with 15 s dwell time [17],[18].
Different formulations of Losartan potassium 100mg release modulating matrix tablets were prepared using the following excipients: AFG (7.522.5mg), ATG (10–30mg), AXG (12.5–37.5mg), carbopol (30mg), starch (10.25mg), magnesium sterate (1.75mg) and MCC (q.s. to 250mg).
Experimental design:
BoxBehnken statistical screening design was used to optimize and evaluate main effects, interaction effects and quadratic effects of the formulation ingredients on the in vitro release of LP sustained release formulations [17],[19]. A 3factor, 3level design used is suitable for exploring quadratic response surfaces and constructing second order polynomial models with Design Expert® (Version 12.0.1.0, StatEase Inc., Minneapolis, MN). This cubic design is characterized by set of points lying at the midpoint of each edge of a multidimensional cube and center point replicates (n = 3). The nonlinear computergenerated quadratic model is given as,
Y= b_{0} + b_{1}X_{1} + b_{2}X_{2} + b_{3}X_{3} + b_{12}X_{1}X_{2} + b_{13}X_{1}X_{3} + b_{23}X_{2}X_{3} + b_{11}X_{1} ^{2} + b_{22}X_{2}^{2} + b_{33}X_{3}^{2}
Where Y is the measured response associated with each
factor level combination; b_{0} is an intercept; b_{1}
to b_{33} are regression coefficients computed from the
observed experimental values of Y; and X_{1}, X_{2}
and
i
X_{3} are the coded levels of independent
variables. The terms X_{1} X_{2} and X ^{2}
(i = 1, 2 or 3) represent the interaction and quadratic terms,
respectively. The selected dependent and independent variables are shown (Table
1, left column) along with their low, medium and high levels, which were
selected based on the results from preliminary experimentation [20]. The
amounts of Aminated FG (X_{1}), Aminated TG (X_{2}) and
Aminated XG (X_{3}) used to prepare each of the 15 formulations
are given (Table 2).
Table 1: Variables in Box Behnken design
Factor 
Level used, actual (coded) 

Low (1) 
Medium (0) 
High (+1) 

X1=AFG (%) 
3 
6 
9 
X2=ATG (%) 
4 
8 
12 
X3= AXG (%) 
5 
10 
15 
Dependent variables 
Constraints 

Y1 = % Burst release in 15 min 
10 ≤ Y1 ≤ 15 

Y2 = % Dissolution after 60 min 
31 ≤ Y2 ≤ 35 

Y3 = Hardness (kg/cm2) 
Maximize (range 3.5–5.5) 

^{*}All percentages were calculated with respect to total tablet weight of 250mg 
Tablet assay and physical evaluation:
The tablets were assayed for drug content using methanol as the extracting solvent, and the sample were analyzed spectrophotometrically (Shimadzu UV1800, Japan) at 215 nm [17], [20]. Tablets were also evaluated for the hardness (n = 6) (Monsanto hardness tester), friability (n = 6) (Roche Friabilator, 100 rpm), weight variation (n = 20) and thickness (n = 10) (Vernier caliper).
Table 2: Observed responses in Box Behnken design for losartan potassium release modulating matrix tablet
Batch 
Dependent Variables 
Independent variables 

X1 (%) 
X2 (%) 
X3 (%) 
Y1 (%) 
Y2 (%) 
Y3 (kg/cm^{3}) 

1 
3 
4 
10 
11.87 
37.53 
3.5 
2 
9 
4 
10 
9.63 
34.27 
4 
3 
3 
12 
10 
7.16 
26.76 
5 
4 
9 
12 
10 
6.81 
21.84 
5.5 
5 
3 
8 
5 
10.45 
35.63 
4.5 
6 
9 
8 
5 
8.56 
30.12 
4 
7 
3 
8 
15 
9.27 
33.41 
3.5 
8 
9 
8 
15 
8.13 
28.73 
5.5 
9 
6 
4 
5 
12.41 
37.61 
3.5 
10 
6 
12 
5 
7.23 
26.48 
5.5 
11 
6 
4 
15 
10.71 
35.54 
3.5 
12 
6 
12 
15 
6.69 
24.39 
5.5 
13 
6 
8 
10 
8.87 
33.74 
5 
14 
6 
8 
10 
8.13 
32.21 
4 
15 
6 
8 
10 
7.33 
32.79 
4.5 
In vitro drug release studies:
Dissolution studies were performed using the USP II, paddlerotating method (Electrolab dissolution tester, Electro lab, India) at 37°C ± 0.5°C and 75rpm using 0.1 N HCl (2 hr) and phosphate buffered solution, pH 6.8 (PBS) (10 hr), as the dissolution media. Dissolution studies were carried out in triplicate, maintaining the sink conditions for all the formulations. A 5ml aliquot of sample was withdrawn at regular time intervals, filtered and assayed spectrophotometrically at 205.3nm. The cumulative % drug release was calculated for the formulations [21],[22].
Swelling and erosion studies:
Swelling and erosion studies of the matrix tablets were carried out under conditions identical to those described for the dissolution testing. After 2 hr in 0.1 N HCl and 6 hr in phosphate buffer, pH 6.8, the tablets were removed, gently wiped with a tissue paper to remove surface water and Scanning Electron Microscopy (SEM) study of the hydrated swollen tablets was carried out [17],[23]. Water uptake and mass loss were determined gravimetrically according to the following equations;
Degree of swelling (water uptake)=
(Wet weight  Original dry weight)/(Original dry weight)
Erosion (% mass loss)=
(Original weight  Remaining dry weight)/(Original weight)
Thermal properties:
Differential scanning calorimetry (DSC) experiments were performed on drug, excipients and the optimized formulation using DSC (Perkin–Elmer, Norwalk, CT). The instrument was calibrated using indium standards. Accurately weighed samples (5–10mg) were hermetically sealed in flat bottom aluminum pans and heated from 48 to 300°C at a rate of 10°C per min under an atmosphere of nitrogen. Thermograms were normalized and rescaled as needed before overlapping [11],[24].
Fourier transforms infrared spectroscopy (FTIR):
FTIR studies were performed on drug, excipients and the optimized formulation using Shimadzu FTIR (Shimadzu Corp., India). Background spectrum was collected before running each sample. The samples were analyzed between wavenumbers 4000 and 400 cm^{1}.
Optimization data analysis and validation of optimization model:
Statistical validation of the polynomial equation generated by Design Expert^{®} was established on the basis of ANOVA provision in the software. A total of 15 runs with triplicate center points were generated. The models were evaluated in terms of statistically significant coefficients, standardized main effects (SME) and R^{2} values. Various feasibility and grid searches were conducted to find the compositions of optimized formulation. Various 3D response surface graphs were provided by the Design Expert software. By intensive grid search performed over the whole experimental region, nine optimum checkpoints formulations were selected to validate the chosen experimental domain and polynomial equations. The optimized checkpoint formulations were prepared and evaluated for various response properties. The resultant experimental values of the responses were quantitatively compared with that of the predicted values. Also, linear regression plots between actual and predicted values of the responses were produced using MSExcel.
RESULTS AND DISCUSSION:
Characterizations of derivetized natural polymers:
The synthesis polymers are characterized using ATRFTIR, DSC and XRD studies. In this study, synthesis polymers are confirmed by ATRFTIR study. The ATR FTIR study of aminated fenugreek gum, aminated tamarind gum and aminated xanthan gum is confirmed by the appearance of a new peak at 3271 cm^{1}, 1639.49 cm^{1} and 2899.01 cm^{1} respectively corresponding to NH_{2} group.
Aminated fenugreek gum:
The DSC thermograms of AFG, in that the AFG shows the broad endothermic peak at 9.94°C with heat of fusion 38.33 J/g, and the exothermic peak does not appeared. These transitions occur at a lower temperature as compared with fenugreek gum. The endothermic peak is due to the loss of water content in polymer (Bassi & Kaur, 2015). The disappearance of exothermic peak due to complete degradation of polymer backbone is observed. These peak shows low thermal stability as compared to fenugreek gum i.e. decreased availability of OH groups for intramolecular hydrogen bonding. The Tg of AFG was also observed high in AFG (47.34°C) as compared to FG (47.95°C), indicating a high degree of Crystallinity of polymer.
DSC of Aminated tamarind gum:
The DSC thermograms of aminated tamarind, in that the aminated tamarind shows endothermic peak at 82.40°C and 394.50°C with heat of flow 1.002 w/g and 9.231 w/g or the exothermic peak does not appeared. The endothermic peaks are due to the loss of water content in polymer. The disappearance of exothermic peak was 365.35°C and heat of flow 9.639 w/g, due to complete degradation of polymer backbone. The melting point was showed by 276.49°C.
DSC of aminated xanthan gum:
The DSC thermograms of aminated xanthan gum, in that the aminated xanthan gum shows endothermic peak at 71.74°C and 541.66°C with heat of flow 1.644 w/g and 9.424 w/g or the exothermic peak does not appeared.
Table 3: Flow properties of natural gum and derivetized gum
Polymer 
Bulk density 
Tapped density 
Angle of repose 
Compressibility index (%) 
Hausner’s ratio 
Fenugreek Gum 
0.37 
0.41 
33.6 
18.6 
1.22 
Aminated Fenugreek Gum 
0.39 
0.45 
35.9 
13.33 
1.15 
Tamarind Gum 
0.37 
0.41 
15.4 
9.75 
1.1 
Aminated Tamarind Gum 
0.41 
0.55 
18.2 
25.45 
1.34 
Xanthan Gum 
0.38 
0.45 
16.7 
15.55 
1.18 
Aminated Xanthan Gum 
0.43 
0.52 
19.1 
17.3 
1.2 
^{*}All value calculated in average of five reading.
The endothermic peaks are due to the loss of water content in polymer. The disappearance of exothermic peak was 430.05°C and heat of flow 11.82 w/g, due to complete degradation of polymer backbone. The melting point was showed by 277.20°C.
The Xray ray differactograms (XRD):
The Xray differactograms of aminated fenugreek gum, aminated tamarind gum and aminated xanthan gum. The diffractions curve of aminated fenugreek gum, aminated tamarind gum and aminated xanthan gum was typical of amorphous material with no sharp peaks.
Flow properties and physicochemical evaluation of aminated polymers:
The bulk density, tapped density and angle of repose of synthesized polymers were increased as compared to natural polymer due to reason of chemical modification was done in natural polymer. Compressibility index and Hausner’s ratio describe the flow properties of natural polymers and derivetized polymers. Observations as per compressibility index the aminated fenugreek gum shows good flow properties as compare to natural fenugreek gum and aminated tamarind gum shows poor flow properties as compare to natural tamarind gum. In case of aminated xanthan gum compressibility index is partially an increases shows good flow property. The values of Hausner’s ratio are ˂ 1.25, shows good flow. Here all derivetized polymers show good flow properties except aminated tamarind gum. Evaluation parameters like bulk density, tapped density, angle of repose, compressibility and Hausner’s ratio was carried out for the natural polymers and derivetized polymers and was found to be within the limit as given in Table 3.
Drug content and physical evaluation:
Drug content of the formulations was assayed spectrophotometrically at 215nm. Assayed content of drug in various formulations varied between 98.23% and 100.30% (average 99.35%). Tablet weights varied between 249.29mg and 250.30mg (average 249.93 mg), hardness between 3.5 and 5.5kg/cm^{2} (average 4.46 kg/cm^{2}), thickness between 3.09 and 3.12mm and friability ranged from 0.49% and 0.87% (average 0.73%). Thus all the physical parameters of the compressed matrices were found to be practically within controls.
Fitting of data to model:
A threefactor, threelevel BoxBehnken statistical experimental design as the RSM requires 15 experiments (Polynomial analysis). The independent variable and the response for all 15 experimental run are given in Table 2. Eleven batches showed the burst release (Y1) of less than 10% and the range of Y1 for all batches was 6.69–12.41%. The ranges of other responses, Y2 (% dissolution after 60 min) and Y3 (hardness of the tablets, kg/cm^{2}), were 21.84–37.53% and 3.5–5.5kg/cm^{2}, respectively. All the responses observed for 15 formulations and analyzed with polynomial equation of statistics analysis [17] were simultaneously fitted to first order, second order and quadratic models using Design Expert^{®} and the comparative values of R^{2}, S.D. and % C.V. are given in Table 4 along with the regression equation generated for each response. Responses Y1, Y2 and Y3 were found to follow linear, quadratic and second order model respectively (Table 4, right column). Only statistically significant (p < 0.05) coefficients are included in the equations. A positive value represents an effect that favors the optimization, while a negative value indicates an inverse relationship between the factor and the response. It is evident that the Aminated fenugreek gum (X1), Aminated tamarind gum (X2) and Aminated xanthan gum (X3) have negative effects on the responses Y1 and Y2 in the following order;
ATG (X2) > AFG (X1) > AXG (X3)
Coefficients with higher order terms or more than one factor term in the regression equation represent quadratic relationships or interaction terms, respectively. It also shows that the relationship between responses and factors is not always linear. Used at different levels in a formulation or when more than one factors are changed simultaneously, a factor can produce different degree of response. The interaction effect of X1 was seen with X2 and X3 for response Y2; and between X1 and X3 for response Y3. X2 also showed a higher quadratic effect as compared to X1 on response Y2. Percentage burst release (Y1) and hardness of the tablets (Y3) were found to fit the linear and second order models, respectively. In absence of the quadratic effects, Y1 was mainly dependent upon the amount of ATG. For Y3, the critical parameters were found to be the AFG and the ATG.
Table 4: Summary of regression analysis of Y1, Y2 and Y3
Model 
R^{2} 
Adjusted R^{2} 
Predicted R^{2} 
S. D. 
% C. V. 
Remark 
Response (Y1) 






Linear model 
0.8805 
0.848 
0.8081 
0.7093 
7.98 
Suggested 
Second order 
0.9101 
0.8427 
0.7901 
0.7214 
8.12 
 
Quadratic model 
0.9653 
0.9028 
0.7965 
0.5672 
6.39 
 
Response (Y2) 






Linear model 
0.9441 
0.9288 
0.9046 
1.29 
4.1 
 
Second order 
0.9467 
0.9067 
0.8189 
1.48 
4.7 
 
Quadratic model 
0.9944 
0.9842 
0.96 
0.6069 
1.93 
Suggested 
Response (Y3) 






Linear model 
0.7514 
0.6835 
0.5217 
0.4569 
10.23 
 
Second order 
0.9206 
0.861 
0.8048 
0.3028 
6.78 
Suggested 
Quadratic model 
0.9255 
0.7915 
0.5532 
0.3708 
8.3 
 
Regression equation of the fitted model ^{a} 

Y1=8.880.70X12.09X20.48X3 

Y2=32.912.29X15.68X20.97X3+0.20X1X30.005X2X30.92X1^{2}1.89X2^{2} 

Y3=4.5+0.31X1+0.87X2+0.06X3+0.62X1X3 

^{a} Only the terms with statistical significance are included. 
Table 5: Standardized main effects of the factors on the responses
Factor 
Standardized main effect of the factors on the responses 

Burst release (Y1) linear model 
Dissol. 60 min. (Y2) quadratic model 
Hardness (Y3) second order model 

X1 
2.801441 
10.7008 
2.919371 
X2 
8.339521 
26.4928 
8.174239 
X3 
1.919137 
4.52615 
0.583874 
X1*X2 
 
 
 
X1*X3 
 
0.683756 
4.128614 
X2*X3 
 
0.01648 
 
X1*X1 
 
2.92189 
 
X2*X2 
 
5.98494 
 
X3*X3 
 
 
 
R^{2} 
88.05% 
99.44% 
92.06 
p value of lack of fit 
0.6624 
0.791 
0.9678 
^{a} Only term with statistical significance are included
Standardized main effects and reliability of the models:
Standardized Main Effects (SME), presented in Table 5, SME were calculated by dividing the main effects with the standard error of the main effects [17],[25]. Only statistically significant (p < 0.05) values are given. The larger SME value of X2 suggested the paramount importance of ATG on drug release. R^{2}value signifies the percentage of variability in responses that are fitted to the models. In the present study, the high R^{2}value of > 99% represents the reliability of the design. Additionally, the pvalues of lack of fit were greater than 0.05, which further strengthened the reliability of the models (Table 5).
Contour plots and response surface analysis:
Twodimensional contour plots and threedimensional response surface plots are presented in Figure 1 which is very useful to study the interaction effects of the factors on the responses. These types of plots show the effects of two factors on the response at a time. In all the presented figures, the third factor was kept at a zero level. Figure 1 (B) and (C) exhibits a nearly linear relationship of factor X3 with factors X1 and X2, in the form of almost straight line. Response surface plots show the relationship between these factors even more clearly. However, factor X1 and X2 have non linear relationship Figure 1 (A) and Figure 1 (D) shows that 39.5 % drug is released after 60 min (Y2) when both the AFG and ATG are at lowest level and the decrease in % drug release was polymer concentration dependent. Also the ATG resulted in greater reduction in % release at 12 % level as compared to the AFG at 9% concentration. This indicates a slight nonlinear trend between the factors X1 and X2. Figure 1 (E) and (F) show an increasing trend for Y2 upon the replacement of either of AFG or ATG with AXG.
Figure1: Contour plot showing the effect of (A) AFG (X1) and ATG (X2) on response Y2, (B) AFG (X1) and AXG (X3) on response Y2, (C) ATG (X2) and AXC (X3) on response Y2;
Response surface plot showing the effect of  (D) AFG (X1) and ATG (X2) on response Y2, (E) AFG (X1) and AXG (X3) on response Y2, (F) ATG (X2) and AXC (X3) on response Y2
Optimization:
The optimum formulation was selected based on the criteria of attaining the maximum hardness for tablets and applying constraints on Y1 (10 ≤ Y1 ≤ 15) and Y2 (31 ≤ Y2 ≤ 35). Upon ‘trading off’ various response variables and comprehensive evaluation of feasibility search and exhaustive grid search, the formulation composition with polymer levels of AFG 37.40 mg, ATG 10 mg and AXG 24.91 mg, was found to fulfill the maximum requisite of an optimum formulation because of better regulation of % burst release and % dissolution after 1 hr time interval. The optimized formulation was found to release about 99.12% drug in sustained release manner for 12 hr. Study of the in vitro release profiles in 0.1 N HCl (for 2 hr) and in phosphate buffer, pH 6.8 (for 10 hr), of the formulations showed a burst release of 37.61% during 1 hr followed by a gradual release phase for about 10 hr. Figure 2 shows the complete dissolution profile of the optimized formulation. The optimization of the formulation was carried out from overlay plot. Overlay plot gives the area of interest or area of the experiment. In Figure 3 yellow region reflects the area of experiment.
Figure 2: Dissolution profile of the optimized formulation.
Figure 3: Overlay plot of optimized batch of formulation.
Validation of RSM result:
For all of the checkpoint formulations, the results of the physical evaluation and tablet assay were found to be within limits. Table 6 shows the composition of optimum checkpoint formulations, their predicted and experimental values of all the response variables, and the percentage error in prognosis. Linear correlation plots between the actual and the predicted response variables were plotted and the residual plots, showing the scatter of the residuals versus actual values, are presented in Figure 4. For validation of RSM results, the experimental values of the responses were compared with that of the anticipated values and the prediction error was found to vary between 0.7533% and 0.9541%. The linear correlation plots drawn between the predicted and experimental values demonstrated high values of R^{2} (ranging between 0.9300  0.9950) indicating excellent goodness of fit (p < 0.001) [26]. Thus the low magnitudes of error as well as the significant values of R^{2} in the present investigation prove the high prognostic ability of the RSM [20].
Table 6: Composition of optimum checkpoint formulation, the predicted and experimental values of response variables and percentage prediction error
Formulation composition (X1:X2:X3) 
Response variable 
Experimental value 
Predicted value 
Percentage prediction error 
7.5:10.0:37.5 
Y1 (%) 
6.69 
6.3108 
0.3791 
Y2 (%) 
24.39 
24.3437 
0.04625 

Y3 (kg/cm2) 
5.5 
5.4041 
0.09583 

22.5:10.0:25.0 
Y1 (%) 
8.13 
7.6995 
0.4304 
Y2 (%) 
28.73 
28.9125 
0.1825 

Y3 (kg/cm2) 
5.5 
5.4666 
0.03333 

7.5:10.0:37.5 
Y1 (%) 
7.23 
7.2733 
0.0433 
Y2 (%) 
26.48 
26.2962 
0.1837 

Y3 (kg/cm2) 
5.5 
5.2791 
0.2208 

22.5:30.0:25.0 
Y1 (%) 
9.63 
10.272 
0.642 
Y2 (%) 
34.27 
33.9037 
0.3662 

Y3 (kg/cm2) 
4 
3.9041 
0.09583 

7.5:20.0:12.5 
Y1 (%) 
12.41 
11.4558 
0.9541 
Y2 (%) 
37.61 
37.6562 
0.04625 

Y3 (kg/cm2) 
3.5 
3.5291 
0.0291 

22.5:20.0:12.5 
Y1 (%) 
11.87 
11.677 
0.1929 
Y2 (%) 
37.53 
37.6662 
0.1362 

Y3 (kg/cm2) 
3.5 
3.2791 
0.2208 

7.5:20.0:37.5 
Y1 (%) 
7.16 
7.4945 
0.3345 
Y2 (%) 
26.76 
27.1262 
0.36625 

Y3 (kg/cm2) 
5 
5.0291 
0.0291 

22.5:20:37.5 
Y1 (%) 
9.27 
9.1045 
0.1654 
Y2 (%) 
33.41 
33.09 
0.32 

Y3 (kg/cm2) 
3.5 
3.5916 
0.0916 

15.0:10.0:12.5 
Y1 (%) 
8.13 
8.8833 
0.7533 
Y2 (%) 
32.21 
32.9133 
0.7033 

Y3 (kg/cm2) 
4 
4.4666 
0.4666 

15.0:30.0:12.5 
Y1 (%) 
10.71 
10.4933 
0.2166 
Y2 (%) 
35.54 
35.7237 
0.1837 

Y3 (kg/cm2) 
3.5 
3.6541 
0.1541 

15.5:10.0:37.5 
Y1 (%) 
8.56 
8.662 
0.10208 
Y2 (%) 
30.12 
30.44 
0.32 

Y3 (kg/cm2) 
4 
4.0916 
0.0916 

15.0:30.0:37.5 
Y1 (%) 
6.81 
6.0895 
0.7204 
Y2 (%) 
21.84 
21.70375 
0.1362 

Y3 (kg/cm2) 
5.5 
5.6541 
0.1541 

7.5:10:12.5 
Y1 (%) 
10.45 
10.067 
0.3829 
Y2 (%) 
35.63 
35.4475 
0.1825 

Y3 (kg/cm2) 
4.5 
4.7166 
0.2166 

7.5:10:12.5 
Y1 (%) 
7.33 
8.8833 
1.5533 
Y2 (%) 
32.79 
32.9133 
0.1233 

Y3 (kg/cm2) 
4.5 
4.4666 
0.0333 

7.5:10:12.5 
Y1 (%) 
8.87 
8.8833 
0.0133 
Y2 (%) 
33.74 
32.9133 
0.8266 

Y3 (kg/cm2) 
5 
4.4666 
0.5333 
* In bold case value shows optimized batch
Figure 4: Linear correlation plots (A, C, E) between actual and predicted values and the corresponding residual plot (B, D, F) for various responses.
Swelling studies:
The swelling and erosion behavior of the optimized matrix tablet in 0.1N HCl and in PBS, pH 6.8, as a function of time, is shown in Figure 5. It can be observed that the hydrophilic matrix tablets underwent both swelling and erosion at the same time. The tablets achieved maximum swelling after 1 hr, which can be linked to the initial burst release of LP. Constant release can be obtained from such hydrophilic systems because of the simultaneous swelling and erosion of the matrix tablets. Constant release in such situations occurs because the increase in diffusional path length due to swelling is compensated by continuous erosion of the matrix. The crosssectional SEM images of matrix tablets after 2 hr in acidic and 6 hr in basic media are shown in Figure 6 (A) (B). SEM study of the dissolving matrix tablets showed a uniform swelling of the matrix and further supported the fact of drug release by a diffusion process from the highly porous and swollen matrix tablets (figure 6).
Figure 5: Erosion and swelling behavior of optimized formulation.
Figure 6: SEM photomicrographs showing surface topography of hydrated matrices in (A) acidic media, 2 hr (B) basic media, 6 hr.
Thermal properties:
DSC thermogram of the drug, excipients and the optimized formulation were recorded, in order to determine the thermal changes of polymers and drug before and after preparation. The characteristic endothermic peak of the drug at 255.46°C was observed in formulation also. However, the broadening of the drug peak in optimized formulation was related more to the impurities from excipients than physical interaction of the drug with the components.
Compatibility study of Losartan potassium by Fourier transform infrared (ATRFTIR) spectroscopy:
FTIR spectra of the drug, excipients and the optimized formulation were recorded in range of 4000 – 400 cm^{1}. LP showed some prominent and characteristic peaks at 3394 cm^{1}, 1026 cm^{1}, 1643 cm^{1}, and 764 cm^{1}, which could be assigned to stretching vibrations of OH and CO bond of primary alcohols, N=N stretching and CCl bond, respectively. In the optimized formulation, the presence of all the characteristic peaks of the LP indicates lack of any strong interaction between the drug and the excipients.
Figure 7: FTIR spectra of optimized formulation
CONCLUSION:
Release modifier polymer aminated fenugreek gum, aminated tamarind gum and aminated xanthan gum was synthesized and characterized. The synthesis polymers are characterized using ATRFTIR, DSC and XRD studies. In this study, synthesis polymers are confirmed by ATRFTIR study. The ATR FTIR study of aminated fenugreek gum, aminated tamarind gum and aminated xanthan gum is confirmed by the appearance of a new peak at 3271 cm ^{1}, 1639.49 cm^{1} and 2899.01 cm^{1} respectively corresponding to NH2 group in the FTIR spectra of aminated fenugreek gum. Hydrophilic matrix tablets of LP with AFG, ATG and AXG were prepared and optimized using a three factor, threelevel Box Behnken design. The quantitative effect of these factors at different levels on the release rate could be predicted by using polynomial equations. Linearity observed between the actual and predicted values of the response variables suggested the prognostic ability of the RSM design. The quadratic response surface methodology studied for the release rate helped in understanding the interaction effects between the combination and ratio of the three polymers. DSC and FTIR studies combined with the stability study of the optimized formulation proved the integrity of the developed hydrophilic matrix tablets. Thus, high degree of prediction obtained using RSM is quite efficient in optimizing drug delivery systems that exhibit nonlinearity in responses.
ACKNOWLEDGEMENT:
Shankar Kalbhare would like to thank the Viraj Pharmaceutical, Mumbai (India) for providing gift sample of pure losartan potassium.
CONFLICT OF INTEREST:
The authors declare no conflict of interest.
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Received on 17.11.2020 Modified on 25.01.2021
Accepted on 11.03.2021 ©Asian Pharma Press All Right Reserved
Asian Journal of Pharmaceutical Research. 2021; 11(2):7384.
DOI: 10.52711/22315691.2021.00015