Formulation Development and Optimization of Sustained Release Tablets of Gliclazide using Central Composite Design

Danga Neelima, Vasavi Laveti, Karakavalasa SVVS Sai Sampath, Geethika Gorinka,

Rama Devi Korni*

Department of Pharmaceutical Technology, Raghu College of Pharmacy,

Visakhapatnam 531162, Andhra Pradesh, India.

*Corresponding Author E-mail: ramakalyank@gmail.com

ABSTRACT:

To treat non-insulin dependent diabetic mellitus (NIDDM), it is intended to optimize and produce gliclazide sustained release tablets. A medicine to meet its objective, it should ideally reach the receptor quickly, at the ideal concentration; stay there for the predetermined amount of time, be rejected from other sites, and be quickly eliminated. The wet granulation process was utilized to make gliclazide tablets with sustained release, including two hydrophilic polymers, guar gum and karaya gum. Talc, magnesium stearate and Aerosil, were added to the formulation as glidants and lubricants, while PVP served as the binding agent. An optimal formulation was found through the application of a central composite design. Statistically significant results were obtained for the main impacts (p<0.05) in the contour and 3D plots. Multiple linear regression analysis was used for constructing polynomial mathematical models for the dependent variables. A batch was prepared at a checkpoint to confirm the identification of the optimal formulation. Because of the improved control over release rate, it was determined from the studies that formulation F14, with polymer levels of guar gum 55.018 mg and karaya gum 28.409 mg, satisfied all maximum requirements for an ideal formulation. The ideal formulation demonstrated cumulative percentage drug release at 20 hours of 82.194 and t₅₀ indicated 10.120 hours, with higher desirability and reduced error. Consequently, FTIR spectra were utilized to verify that gliclazide was compatible with the different polymers that were used to make the gliclazide sustained release tablets. In summary, the formulation of sustained release tablets was facilitated by an optimized strategy, which also helped to understand how formulation processing variables affected that development.

KEYWORDS: Central composite design, Gliclazide, Optimization, Response surface methodology, Sustained release tablets.

INTRODUCTION: 

One of the most reliable and often used oral dose forms is the tablet. Tablets have been around since the latter half of the 1800s, and their appeal is still strong today. Tablets continue to be a widely used dosage form due to the benefits they provide to patients as well as pharmaceutical makers.

Reducing the frequency of dosing or increasing the drug's effectiveness by localizing the medication at the site of action, lowering the dosage needed, and ensuring consistent drug delivery are the main objectives of building sustained or controlled delivery systems¹. There are two things that one would need to envision the perfect medicine delivery system. For the first part of the treatment, there would only be one dose, whether that be for a few days or weeks (for an illness, for example) or the patient's lifetime (for conditions like diabetes or hypertension, for example). To reduce or completely eradicate side effects, the medication should be delivered straight to the site of action. Delivery to receptors, localization to cells, or distribution to bodily regions might all be necessary for this. When it comes to studies on pharmacological and physiological restrictions, product design, and testing, oral administration has gotten most of the attention when it comes to sustained release systems. The reason for this is that the creation of dosage forms for oral administration is more feasible than for parenteral or any other route. A few interrelated factors of significant importance are involved in the design of oral sustained release delivery systems².

Modelling a curved quadratic surface to continuous factors can be accomplished with response surface designs. A response surface model can identify whether a minimum or maximum response is present within the factor region. Curved surfaces cannot be fitted by the typical two-level designs because a quadratic function requires three different values for each independent variable. The central composite design (CCD) is the response surface design that is most often used^3,4. The response surface method (RSM) design that is most frequently used is central composite design. Without requiring the use of a full three level factorial experiment, a central composite design is an experimental strategy for developing a second order model for the response variables. With the addition of centre points and axial points, it is constructed using a two-level factorial design. Standard central composite designs consist of five levels for every factor; however, this can be adjusted by selecting a face-centred CCD, alpha = 1.0. It is designed for quadratic model estimation⁵. Missing data is not detected by CCDs. Near the centre of the design area, the CCD replicated centre point offers exceptional prediction capabilities⁶.

Gliclazide is an oral hypoglycaemic medication of the second generation that is used in the treatment of non-insulin dependent diabetic mellitus (NIDDM). It enhances ineffective insulin production and effectively treats insulin resistance seen in NIDDM patients, also referred to as type 2 diabetes. These actions are manifested in the blood glucose level, which is equivalent to that attained with other sulphonyl urea agents and is sustained throughout both short- and long-term treatments. Gliclazide corrects peripheral insulin resistance and faulty insulin production to lower blood glucose levels in NIDDM patients^7-10.

The current study is aimed to formulate, develop, and optimize gliclazide sustained release tablet using central composite design. Sustained release matrix delivery systems are designed to decrease the dosage frequency or improve the treatment by localizing at the site of action, lowering the amount required, or guaranteeing unvarying drug distribution¹¹. It might be feasible to raise the therapeutic concentration of gliclazide by developing a sustained release formulation. This would decrease the frequency of dosing requirements, improve patient compliance, and boost drug efficiency. Thus, an attempt was undertaken to produce Gliclazide with extended release. The best formulation for this study is created by combining karaya and guar gum in different ratios using design expert software.

MATERIALS AND METHODS:

Materials:

The supplier of Gliclazide was (Dr. Reddy’s Laboratories, Hyderabad). We bought talc, guar gum, and karaya gum from Yarrow Chemicals in Mumbai. Finar Chemicals is where lactose, Aerosil, and polyvinylpyrrolidone (PVP) were acquired. Magnesium stearate was obtained from Moly Chem Pvt. Ltd.

Central composite design:

Central composite design is used to construct a second order model for the dependent variables without requiring the use of a full three-level factorial experiment. An attempt was made to use the response surface method and central composite design to formulate, develop, and optimize gliclazide sustained release (SR) matrix tablets. The wet granulation process was utilized to create the gliclazide SR matrix tablets. Using design expert statistical software, trial version of Design Expert 23.1.1, the sustained release formulation of gliclazide was optimized¹². Karaya gum (X1) and guar gum (X2) were selected as independent factors based on the pre-formulation studies conducted prior to the project. These factors were compared to four responses: drug release in 8 hours (Y1), drug release in 14 hours (Y2), drug release in 20 hours (Y3), and time to 50% drug release (Y4). The conversion of coded levels in actual units are given in (Table 1). The results were analysed using ANOVA to determine significance. The software provided three projected formulations with the corresponding specified criteria in the numerical prediction. With the specified polymer ratios, three anticipated formulations were created, and in-vitro dissolution was removed. The anticipated formulation values for t_50, 8 hours, 14 hours, and 20 hours were compared to the experimental value, and the error was recorded^13-17.

Table 1. Translation of Coded levels in Actual units

Coded Level	-1	0	+1
Independent variables
X1: Karaya Gum (%)	20	30	40
X2: Guar Gum (%)	20	40	60
Dependent variables
Y1	Drug release in 8 h (%)
Y2	Drug release in 14 h (%)
Y3	Drug release in 20 h (%)
Y4	t50 (h)

Table 2. Formulations of gliclazide

Formulations	Gliclazide (mg)	Karaya gum (mg)	Guar gum (mg)	Lactose (mg)	PVP 5% (mg)	Talc 1% (mg)	Mg. Stearate 2% (mg)	Aerosil 1% (mg)	Total (mg)
F1	40	20	20	102	10	2	4	2	200
F2	40	40	20	82	10	2	4	2	200
F3	40	20	60	62	10	2	4	2	200
F4	40	40	60	42	10	2	4	2	200
F5	40	20	40	84	10	2	4	2	200
F6	40	40	40	64	10	2	4	2	200
F7	40	20	40	80	10	2	4	2	200
F8	40	40	40	60	10	2	4	2	200
F9	40	30	20	94	10	2	4	2	200
F10	40	30	60	54	10	2	4	2	200
F11	40	30	20	90	10	2	4	2	200
F12	40	30	60	50	10	2	4	2	200
F13	40	30	40	72	10	2	4	2	200

Preparation of sustained release tablets:

The active pharmaceutical ingredient, gliclazide; the diluent, lactose and the sustained release polymers, karaya gum and guar gum were mixed thoroughly in a mortar and the binder PVP was added to the above mixture. The  dough mass was allowed to pass through sieve number 16 and the wet granules were dried for 30 minutes at 60°C in hot air oven. The dried granules were passed through sieve number 20. The dried granules were combined with the lubricant magnesium stearate, and glidants Aerosil and talc, and properly mixed. The mixture was compressed using 8 station tablet machine with tablet diameter 10 mm and tablet weight 200          mg^18-20. The composition of the formulation is given in (Table 2).

Evaluation:

The drug excipient compatibility was observed using FT-IR spectroscopy. The hardness and friability of the tablets were assessed using a Monsanto hardness tester and a Roche friabilator, respectively.

The influence of these variables on the mechanism and kinetics of drug release from a dosage form can be determined using in-vitro tests. This will provide an indication of the behaviour of the dose form in in vivo research. The tablets were taken in vessels of USP type II apparatus filled with freshly prepared 900 mL of pH 7.4 phosphate buffer. The temperature was kept at 37.5 ±1.0°C while the paddle was turned at a speed of 75 rpm. 5 mL of the sample solution was taken out of each vessel and filtered at the designated interval. Using dissolving medium as a blank, the absorbance of the sample solution was measured in a 1 cm cell on an UV spectrophotometer at 223 nm. Using the following formula, note the absorbance and determine the percentage of Gliclazide dissolved in the dissolving medium.

Drug release = (Conc. of gliclazide × Dilution factor × Dissolution volume)/1000

Optimization:

The aim of optimization is to arrive at the "optimal" design in relation to a hierarchy of rules or limitations. There are three steps involved in optimization using the RSM method: first step is statistically planned trials; second step is determining the coefficients in a mathematical model; and third step is forecasting the response and ensuring that the model is adequate given the experimental setup²¹.

RESULTS AND DISCUSSION:

Evaluation of tablets:

The wet granulation process was used to make the tablets. The produced tablets underwent evaluations for thickness, weight variation, hardness, friability, drug content, and in vitro dissolving testing. The created tablets had a thickness ranging from 3.02 to 3.05 mm. The produced tablets had a hardness ranging from 6.7 to 7.4 kg/cm². Although a loss of up to 1% is permitted according to US and European pharmacopoeias, the percentage friability varied from 0.21 to 0.28, suggesting high mechanical resilience of tablets. All 13 formulations had drug contents ranging from 88.95 to 98.90 mg, meaning that all of them were above the 90% threshold. The manufactured tablets passed the test for weight variation. Every batch passed every quality control test, according to the data shown above.

Each of the formulations' in-vitro dissolving values are provided in (Table 3). The amount of gliclazide that was released after 20 hours from all 13 formulations varied from 74.6334% to 81.9684%, indicating that as the concentration of guar gum and karaya gum increased, so did the drug release. As both karaya gum and guar gum were shown to have a significant release-delaying capacity for gliclazide, the values of t₅₀ increased significantly throughout the course of 9.01 hours, when both polymers were seen to be at low levels, to as high as 11 hours, when both polymers were at high levels. When n >1, meaning that drug diffusion is faster than the steady rate of solvent-induced relaxation and swelling in the polymer, the formulations mostly followed case II transport of diffusion, as indicated by the diffusional exponent values (n) derived from Koresmeyer Peppa's equation (case II transport for swellable polymer). On the other hand, certain formulations (F2, F3, F13) demonstrated that Gliclazide released from sustained release matrix tablets showed anomalous transport (non-Fickian diffusion) when n value is between 0.5 and 1, meaning that the rates of solvent penetration and drug release rate fall within the same range.

Mathematical modelling of RSM optimization of gliclazide:

Stat-ease software was used to derive polynomial equation for the responses, release in 8 h, 14 h, 20 h and t₅₀ to determine mathematical relationships. The polynomial equation relating different responses and factors is given below.

Drug release in 8 h = +34.00 + 0.85*X₁ + 1.54*X₂ - 0.080*X₁X₂ - 1.63*X₁² - 0.077*X₂² - 1.26*X₁²X₂ - 0.87*X₁X₂²

Drug release in 14 h = +55.67 + 1.78*X₁ + 1.94*X₂ - 0.079*X₁X₂ - 1.73*X₁² - 0.53*X₂² - 0.76*X₁²X₂ - 1.71*X₁ X₂²

Drug release in 20 h = +81.23 + 1.05*X₁ + 2.42*X₂ + 0.028*X₁X₂ - 1.26*X₁² - 1.57*X₂² + 0.56*X₁²X₂ - 0.30*X₁ X₂²

t₅₀ = +9.77 - 0.11*X₁ + 0.40*X₂ + 0.66*X₁X₂ - 0.24*X₁² + 0.22*X₂² - 0.29*X₁²X₂ + 0.38*X₁ X₂²

The values obtained for main effects of each factor from equations, revealed that guar gum has more pronounced effect on all the response values. The small coefficients of interaction terms and the quadratic terms in the equation indicated that these terms contributed the least in prediction of Y1, Y2, Y3 and Y4 responses²².

Table 3. Modelling of the responses in the experimental design

		Factor 1	Factor 2	Response 1	Response 2	Response 3	Response 4
Std	Run	Karaya gum concentration	Guar gum concentration	Drug release in 8 h	Drug release in 14 h	Drug release in 20 h	t50
		%	%	%	%	%	h
1	1	20	20	31.989	52.08	74.589	9.236
2	2	40	20	32.107	52.397	76.04	9.864
9	3	30	40	34.0298	55.698	81.149	10.24
11	4	30	40	34.0298	55.678	81.149	10.284
10	5	30	40	34.0298	55.689	81.147	10.236
3	6	20	60	32.6984	54.598	80.4984	9.982
4	7	40	60	32.496	54.598	82.0612	11.009
6	8	44.142135623731	40	33.149	55.6948	81.249	10.013
8	9	30	68.284271247462	35.398	57.0543	82.298	11.01
7	10	30	11.715728752538	32.326	53.168	77.456	9.171
12	11	30	40	34.0278	55.648	81.148	10.256
13	12	30	40	34.0228	55.689	81.149	10.285
5	13	15.857864376269	40	31.459	52.125	79.142	9.223

Table 4. ANOVA for response surface quadratic model for drug release in 8 h

Source	Sum of Squares	df	Mean Square	F-value	p-value
Model	12.22	5	2.44	5.28	0.0250	significant
A-Karaya gum concentration	0.6645	1	0.6645	1.44	0.2698
B-Guar gum concentration	3.70	1	3.70	8.00	0.0254
AB	0.0257	1	0.0257	0.0555	0.8206
A²	7.70	1	7.70	16.64	0.0047
B²	0.5188	1	0.5188	1.12	0.3248
Residual	3.24	7	0.4627
Lack of Fit	3.24	3	1.08	1.174E+05	< 0.0001	significant
Pure Error	0.0000	4	9.200E-06
Cor Total	15.46	12

Table 5. ANOVA for response surface quadratic model for drug release in 14 h

Source	Sum of Squares	df	Mean Square	F-value	p-value
Model	27.17	5	5.43	7.23	0.0109	significant
A-Karaya gum concentration	3.60	1	3.60	4.79	0.0649
B-Guar gum concentration	13.04	1	13.04	17.35	0.0042
AB	0.0251	1	0.0251	0.0334	0.8601
A²	9.33	1	9.33	12.42	0.0097
B²	2.16	1	2.16	2.88	0.1336
Residual	5.26	7	0.7516
Lack of Fit	5.26	3	1.75	4634.72	< 0.0001	Significant
Pure Error	0.0015	4	0.0004
Cor Total	32.43	12

Analysis of variance (ANOVA):

ANOVA was performed in accordance with Design Expert Software's guidelines for estimating the model's significance²³ (Tables 4 to 7). If a model's p-value, or significant probability value, is less than 0.500, it is deemed significant at the 5% significance level.

Table 6. ANOVA for response surface quadratic model for drug release in 20 h

Source	Sum of Squares	df	Mean Square	F-value	p-value
Model	60.76	5	12.15	9.17	0.0056	significant
A-Karaya gum concentration	4.49	1	4.49	3.39	0.1083
B-Guar gum concentration	44.08	1	44.08	33.25	0.0007
AB	0.0031	1	0.0031	0.0024	0.9626
A²	5.78	1	5.78	4.36	0.0752
B²	7.97	1	7.97	6.01	0.0440
Residual	9.28	7	1.33
Lack of Fit	9.28	3	3.09	3.866E+06	< 0.0001	significant
Pure Error	3.200E-06	4	8.000E-07
Cor Total	70.03	12

Table 7. ANOVA for response surface quadratic model for t₅₀

Source	Sum of Squares	df	Mean Square	F-value	p-value
Model	4.06	5	0.8128	35.99	< 0.0001	Significant
A-Karaya gum concentration	0.9607	1	0.9607	42.54	0.0003
B-Guar gum concentration	2.52	1	2.52	111.67	< 0.0001
AB	0.0398	1	0.0398	1.76	0.2260
A²	0.5414	1	0.5414	23.97	0.0018
B²	0.0127	1	0.0127	0.5623	0.4778
Residual	0.1581	7	0.0226
Lack of Fit	0.1559	3	0.0520	94.80	0.0004	Significant
Pure Error	0.0022	4	0.0005
Cor Total	4.22	12

Table 8. Composition of the optimized formulation of gliclazide SR tablets, the predicted and experimental values of response variables

Formulation	Karaya gum (mg)	Guar gum (mg)	Response Variables	Predicted response	Observed response	Percentage Error	Average
F14	28.409	55.018	Drug release in 8 h	35.000	34.985	0.0428	0.0885
			Drug release in 14 h	56.649	56.628	0.0370
			Drug release in 20 h	82.000	82.194	-0.00731
			t50	10.093	10.120	-0.267
F15	32.985	60.000	Drug release in 8 h	35.173	35.276	-0.292	0.2979
			Drug release in 14 h	56.859	56.974	-0.202
			Drug release in 20 h	82.253	82.198	0.066
			t50	10.629	10.625	0.0376
F16	39.327	60.000	Drug release in 8 h	32.848	32.958	-0.334	0.1476
			Drug release in 14 h	54.909	54.903	0.0109
			Drug release in 20 h	82.207	82.356	-0.181
			t50	10.807	10.800	0.0647

Figure 1. Contour plot and 3D surface showing the effect of the amount of polymer karaya gum, guar gum on drug release from gliclazide SR tablet.

Contour and 3D-surface plots:

The contour and 3D surface plots are displayed in (figure 1). A contour plot shows the surface in two dimensions. Constant response contour lines are created by connecting points with the same response. An image of the surface in three dimensions is shown in a 3D surface plot. Compared to contour plots, 3D surface plots can give a apparent idea of the response surface²⁴.

Optimization:

The optimal sustained release tablet formulation of gliclazide including guar and karaya gums was determined to be formulation F14, as indicated in the Table 8, because the error for the response of the dependable variables was the lowest.

FTIR studies:

Gliclazide's compatibility with the different polymers utilized to make the sustain release tablets of gliclazide was verified using FTIR spectra depicted in (figure 2). To put it briefly, the FTIR spectrum of the matrix tablets made with various polymer admixtures (karaya gum and guar gum) showed notable gliclazide characteristics, indicating that there were no interactions between the gliclazide, and the polymers being utilized²⁵.

Figure 2. FTIR spectra of gliclazide, karaya gum, guar gum and optimized formulation

DSC studies:

The DSC thermograms of guar gum, karaya gum, and pure gliclazide are displayed in figure 3. The solitary endotherm on the thermogram of pure gliclazide corresponds to the drug's melting point, which is represented by a distinctive peak. The thermogram indicates that the medication and excipients are compatible. It is evident that the drug was present in an amorphous phase because the improved formulation does not show a melting endotherm²⁶.

Figure 3. DSC spectra of gliclazide, karaya gum, guar gum and optimized formulation

CONCLUSION:

An oral hypoglycaemic medication of the second generation that is sulphonyl urea and is used to treat non-insulin dependent diabetic mellitus (NIDDM) is called gliclazide, 1-(4methylbenenesulphonyl) 3-(3azabicyclo [3.3.o] octyl) urea. Improved insulin production can potentially cure insulin resistance seen in people with non-insulin dependent diabetic diabetes (NIDDM), also referred to as type 2 diabetes. Like other sulphonyl urea medicines, these activities are revealed in the blood glucose level, maintained during short-term and long-term treatments. The results of this investigation indicate that the sustained-release matrix tablets of gliclazide, which were made by wet granulation with the help of guar and Karaya gum, can be used as an oral sustained-release drug delivery system once a day. Every polymer was crucial to Gliclazide's prolonged release. The FT-IR analysis revealed that there was no interaction between the formulation's constituents, meaning the medication and every other component worked well together. Post-compression parameter ranges for all formulations were within optimal limits. According to in vitro drug release tests, the rate at which drugs were released tended to decrease as the concentration of either guar gum or karaya gum increased. According to the results of the drug release kinetic investigations, diffusion was the main mechanism of drug release, and the drug released from the formulations followed zero order kinetics. The constructed tablets demonstrated the Super Case II type of drug transport mechanism, meaning that the rate of drug diffusion is faster than the pace at which the solvent-induced relaxing and swelling of the polymer occurs continuously. Grid searches and practicality led to the selection of the optimal formulation. Limitations were imposed during the numerical optimization procedure in accordance with the sustained release matrix tablet composition that would produce the required response values. The objective of the current investigation was to determine the cumulative percentage of drug release at 8 hours (32.848 - 35), at 14 hours (54.909 - 56.649), at 20 hours (82–83), and at t₅₀, which should be approximately 10.010 - 11.00 hours. An assessment of the three checkpoint batches' replies was conducted to validate the optimization technique. When compared to the projected response values, the response values observed in check point batches were extremely close. An extremely high degree of predictive capacity of response surface methodology was revealed by the validation of optimization study utilizing three confirmatory runs. Hence, the high degree of prediction attained through the application of response surface methodology confirms that a central composite design is a highly effective method for systematizing medication administration.

CONFLICT OF INTEREST:

The authors have no conflict of interest regarding this study.

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Received on 06.06.2024      Revised on 10.10.2024

Accepted on 04.01.2025 Published on 02.08.2025

Available online from August 08, 2025

Research J. Pharmacy and Technology. 2025;18(8):3509-3516.

DOI: 10.52711/0974-360X.2025.00505

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