INTRODUCTION:

The oral route is the most preferred route of administration because of its patient compliance. In the development of oral controlled drug delivery system, one of the main challenges is to modify the GI retention time. It offers number of advantages including improvement in reduced dosing frequency, therapeutic efficacy, safety and patient compliance. Gastric retention time is one of the important factor which can adversely affect the performance of the drugs when administered simply by an oral controlled drug delivery system^[1]. One of the approach to enhance the GI retention time is to develop gastro-retentive drug delivery systems (GRDDS) which provide an effective plasma drug concentration for longer period thereby reducing the dosing frequency^[2,3].

It also has an advantage of minimizing the fluctuations in plasma drug concentration by delivering the drug in a controlled and reproducible manner for prolonged period of time^[4,5}. It is important to note that, the drug has to released in controlled manner after administration and prediction of drug release mechanism is necessary.

The present research is focused to develop Nicorandil floating tablets by melt granulation technique using combination of hydrophilic gum like almond gum (hereinafter called as AG) and hydrophobic polymer like cetosteryl alcohol (hereinafter called as CSA) selected to develop floating tablets because the drug is highly water soluble^[6]. Nicorandil is common choice of drug in cardiovascular diseases like hypertension and angina pectoris, which require constant monitoring. Nicorandil has a short steady state half-life (1.33 hr)^[7], and necessitating the administration of 2 to 4 times daily^[8] so as to maintain adequate plasma levels of drug. The prepared tablets are evaluated for drug release mechanism and the obtained values are compared with theoretical percentage of drug released in order to determine the percentage deviation.

MATERIALS AND METHODS:

Materials:

Nicorandil was obtained as a gift sample from Torrent Pharmaceuticals (P) Ltd., Gujrat, India; Cetosteryl alcohol obtained from Loba Chemical, Mumbai, India; Sodium bicarbonate, Citric acid and Lactose were purchased from SD fine chemicals, Mumbai, India; Talc from Accord labs, Hyderabad, India. All other chemicals and reagents used were analytical grade.

Calculation of theoretical release profile of Nicorandil from controlled release formulations ^[9,10]

The following procedure are commonly used to calculate Loading (Immediate release) dose and Maintenance dose from Robinson-Erickson equation:

Where, X_o = Conventional dose (20 mg), K_e = First order elimination rate constant^[7] (0.521 hr^-1), (Toe) = Dosing interval (24 hr), T_p = Time to reach peak plasma concentration^[11] (0.448 hr). By substituting the kinetic values of Nicorandil in the above equations the results as follows, DI = 1.599 mg, Dm = 19.173 mg (for rest of 23 hr excluding DI), DI* = 1.226 mg, and DT = 20.399 ≈ 21 mg.

Hence, an oral controlled release floating matrix tablets of Nicorandil should contain a total dose of 21 mg (approximately) for 24 hrs and should release 1.226 mg (6.01 %) in the first hour like conventional dosage form and rest of the dose (20.339 - 1.226 = 19.173 mg) in remaining 23 hrs, i.e. 0.833 mg (4.08%) per hour thereafter (up to 24 hrs). The theoretical drug release profile can be generated using the above value which was shown in Table 5.

Preparation of effervescent floating tablets by melt granulation technique

Nicorandil effervescent floating tablets were prepared by direct compression technique using combination of AG and CSA as retarding polymer. The composition of various formulations of effervescent tablets with their codes is listed in Table 1. All the ingredients except wax were passed through sieve 60 (#). The wax/oil were melted in large china dish on hot plate and drug is added to it. Then to this mixture, other sieved ingredients except talc are added and stirred well to mix. The resultant mixture is allowed to solidify at room temperature and then passed through sieve 44 (#) to form granules. The granules are lubricated by adding talc extra granularly. The lubricated granules were then compressed into a tablet using 10 mm standard flat-face punches on 6 station tabletting machine.

Table 1: Composition of Nicorandil floating tablets using different amounts of AG and CSA

Ingredients	Quantity per tablet (mg)
Ingredients	MCS 1	MCS 2	MCS 3	MCS 4	MCS 5	MCS 6	MCS 7	MCS 8	MCS 9	MCS 10	MCS 11	MCS 12
NCRD	21	21	21	21	21	21	21	21	21	21	21	21
AG	100	90	80	70	60	50	70	70	70	80	90	100
CSA	50	60	70	80	90	100	90	100	110	80	80	80
NaHCO₃	30	30	30	30	30	30	30	30	30	30	30	30
CA	10	10	10	10	10	10	10	10	10	10	10	10
SA	5	5	5	5	5	5	5	5	5	5	5	5
Lactose	78	78	78	78	78	78	68	58	48	68	58	48
Talc	6	6	6	6	6	6	6	6	6	6	6	6

NCRD = Nicorandil, AG = Almond gum, CSA = Cetosteryl alcohol, NaHCO₃ = Sodium bicarbonate, CA = Citric acid, SA = Stearic acid

In vitro release studies of prepared tablets^[12]

The release rate of Nicorandil from prepared floating matrix tablets was determined using USP dissolution testing apparatus II (Paddle type). The dissolution test was performed using 900 ml of 0.1N HCL, at 37 ± 0.5°C and 50 rpm. A sample (5ml) of the specimen was withdrawn from the dissolution apparatus periodically, and the samples were replaced with fresh dissolution medium. After filtration and appropriate dilution (if necessary), the absorbance of sample preparations was measured in 1cm cell on UV spectrophotometer at 272 nm using 0.1N hydrochloric acid as blank. Triplicate runs were carried out and the results were averaged.

RESULTS AND DISCUSSION:

Drug release from Nicorandil floating tablets evaluated at 0.1N HCl (pH 1.2) influenced by polymer concentration. Release rate usually depends upon the presence of drug closer to the surface which decreases with increasing hydrophobic polymer concentration and decreases the amount of uncoated drug^[13]. When in vitro drug release studies of Nicorandil floating tablets using different polymers were compared then all the formulation showed maximum amount of drug release for prolonged period of time about 24 hr. From Table 2 it can be observed that, the drug release for the formulations MCS1, MCS2, MCS3, MCS4, MCS5, and MCS6 is found to be 99.686 %, 99.174 %, 98.786 %, 97.264 %, 94.042 % and 91.528 %, respectively at the end of 24 hours. The fact can be reasoned in the way that, an increase in the hydrophobic polymer content results in decrease the drug release rate due to decrease in the total porosity of the matrices (initial porosity plus porosity due to the dissolution of the drug) and also increases the tortuosity of the matrix and drug diffusion path-length which in turn slows down diffusion and erosion from/of the matrix. These behaviour can be explained in terms of release mechanism and suggested that, because of the high hydrophobicity of lipid materials, penetration of dissolution fluid was hindered through the matrix and can progress in the dosage form by dissolving the grains of drug in contact with it and leading to diminished drug release over an extended period. Further, the dissolution of the drug particles on the surface of the matrix allows the formation of channels, from which the drug was slowly released followed by formation of a denser gel and slower erosion. The formulations MCS7, MCS8 and MCS9 were prepared with ascending concentration of CSA by maintaining static concentration of AG (70 mg) and the drug release at the end of 24 hr was observed approximately as 95.361%, 92.763 % and 89.325 %, respectively. The formulations MCS10, MCS11 and MCS12 were prepared with ascending concentration of AG (80 mg, 90 mg and 100 mg, respectively) by maintaining static concentration of CSA (80 mg) and the drug release at the end of 24 hr was observed as 96.463%, 92.763 % and 89.325 %, respectively. It was observed that, at constant level of AG (70 mg), increment of CSA significantly retard the drug release. The release profiles of Nicorandil from floating tablets made at different lipid-wax concentrations showed that the increase in the amount of CSA when maintained a static AG concentration yielded a slower drug release. Interestingly, the same result was observed with ascending concentration of AG when maintained a static concentration of CSA i.e. with increased AG concentration and at a constant level of CSA, yielded a slower drug release. The reason in former case may be, when the CSA content in the matrix was increased may cause slower penetration of the dissolution medium in matrices as a result of increased lipophilicity and leading to diminished drug release. The reason in later case may be, an increase in hydrophilic polymer concentration causes higher degree of swelling when contact with dissolution media which was accountable for increased viscosity of gel as well as gel layer with long diffusion path which cause a decrease in effective diffusion coefficient of drug and reduction in drug release rate from the swelled tablet containing higher concentration of hydrophilic polymer. The drug release mechanism is identified by comparing the square of correlation coefficient values for Higuchi model and Hixson-Crowell model.

Table 2:Drug release profiles of Nicorandil from floating tablets

Time (hr)	MCS 1	MCS2	MCS3	MCS4	MCS5	MCS6	MCS7	MCS8	MCS9	MCS10	MCS11	MCS12
1	0	0	0	0	0	0	0	0	0	0	0	0
2	4.79	5.11	5.36	5.81	5.22	4.53	5.43	4.86	3.99	5.65	5.12	4.16
3	6.85	7.865	8.27	9.718	8.184	6.937	8.648	7.974	6.115	9.215	8.426	6.472
4	9.09	10.21	11.14	13.99	13.79	10.27	11.57	12.37	8.97	12.37	13.53	9.63
5	11.87	13.79	15.47	17.82	18.39	13.63	15.66	14.27	12.65	17.48	16.58	13.37
6	15.46	17.69	19.54	21.61	20.38	18.53	20.87	22.86	14.26	27.16	25.35	15.74
9	20.44	22.14	23.16	25.02	28.63	20.86	27.43	28.52	16.89	33.25	30.56	18.77
12	30.55	32.66	34.74	36.02	37.73	32.52	36.53	35.25	33.46	41.53	37.62	32.66
15	43.26	45.37	47.27	49.62	51.27	41.27	48.66	43.31	38.54	50.27	47.42	42.825
18	57.46	60.66	62.55	60.02	58.64	55.37	58.32	57.47	56.33	63.46	60.33	59.17
24	70.63	73.46	75.25	73.16	69.27	68.37	70.66	70.56	61.17	73.65	72.15	65.72

Higuchi type drug release mechanism is followed by the formulation MCS1, MCS2, MCS3, MCS4 and MCS10 because the R²value closed to one for Higuchi model than Hixson-Crowell model. The rest of the formulations followed by Hixson-Crowell model, because the R²value closed to one for Hixson-Crowell model than Higuchi model (Table 6). The linearity in Higuchi equation describes that, the mechanism of drug release from the swellable matrix is diffusion, where as the linearity in Hixson-Crowell equation describes that the mechanism of drug release is dissolution which results a change in surface area and diameter of particles or tablets. Further, the drug release profile of MCS4 is closed to theoretical drug profile among all the formulations which follows Higuchi model for drug release. So, the formulation MCS4 is selected as the best formulation and further the percentage of drug release deviation from an ideal Higuchi model is calculated.

MATHEMATICAL METHOD FOR QUANTITATIVE EXPRESSION OF DEVIATION FROM HIGUCHI MODEL

Theoretical computation

The first step is to calculate the theoretical percentage of drug released using the Higuchi equation. The straight line of percent drug released versus square root of time is considered as a reference line (Figure 1). Because the relationship between the percent drug released and square root of time is linear, the entire dissolution profile may be compared using area under the curve (AUC), calculated by the Trapezoidal rule. The precision of prediction can be increased by a large number of data points. To predict proportionality between cumulative percentage of drug released and the square root of time from an ideal Higuchi drug release profile, the shaded area (time period from 't' to 't- a') of Figure 1, with zero percent deviation can be calculated by the following equations,

Where, K_H = Higuchi rate constant, t = time in hr, and a = difference between two successive sampling time points. As the above equation is independent of time, AUCs are constant at all the time points and depends only on difference between two successive sampling time points.

For an ideal 24 hr drug release from the dosage form, the Higuchi release rate constant may be calculated by,

For example, at 0 % deviation from ideal 24 hr Higuchi model (a = 1), AUC calculated as follows,

The same shaded area (time period from '√t' to '√(t-a)') of Figure 1, with 'α' percent deviation from the Higuchi release profile can be represented by the following equations,

For example, at +5 % deviation (α =5 %) from ideal 24 hr Higuchi release profile (a = 1), AUC at any time calculated as follows,

Similarly, for -5 % deviation with n = 1,

Similarly, the AUCs calculated for the reference line and the lines showing ±5, ±10, ±15, ±20, ±25 and ±30 % deviations from the reference line are shown in Table 3.

Figure 1: Area under the curve for an ideal Higuchi release profile

From the above equation (Eq.8), it is evident that the AUCs for +α % deviation independent of time point (t); however, it depends on the difference between two successive sampling time points (n). It is important to note that the AUCs increases with an increase in percentage deviation from the reference line (Table 3). The average absolute difference between AUCs (AADA) of the reference line and that of lines showing ± α % deviations, at any time point can be calculated by the following equation (Eq.10).

Table 3: Area under the curve (AUC) at different percentage deviations from ideal Higuchi model of drug release.

Time(hr)	Area under the curve at positive percent deviation
Time(hr)	0	+5%	+10%	+15%	+20%	+25%	+30%
0	0	0	0	0	0	0	0
1	10.2062	10.7165	11.2268	11.7371	12.2474	12.7578	13.2681
2	10.2062	10.7165	11.2268	11.7371	12.2474	12.7578	13.2681
3	10.2062	10.7165	11.2268	11.7371	12.2474	12.7578	13.2681
4	10.2062	10.7165	11.2268	11.7371	12.2474	12.7578	13.2681
5	10.2062	10.7165	11.2268	11.7371	12.2474	12.7578	13.2681
6	10.2062	10.7165	11.2268	11.7371	12.2474	12.7578	13.2681
9	30.6186	32.1495	33.6805	35.2114	36.7423	38.2733	39.8042
12	30.6186	32.1495	33.6805	35.2114	36.7423	38.2733	39.8042
15	30.6186	32.1495	33.6805	35.2114	36.7423	38.2733	39.8042
18	30.6186	32.1495	33.6805	35.2114	36.7423	38.2733	39.8042
24	61.2372	64.2991	67.3609	70.4228	73.4846	76.5465	79.6084
Time(hr)	Area under the curve at negative percent deviation
Time(hr)	0	-5%	-10%	-15%	-20%	-25%	-30%
0	0	0	0	0	0	0	0
1	10.2062	9.6959	9.1856	8.6753	8.1650	7.6547	7.1443
2	10.2062	9.6959	9.1856	8.6753	8.1650	7.6547	7.1443
3	10.2062	9.6959	9.1856	8.6753	8.1650	7.6547	7.1443
4	10.2062	9.6959	9.1856	8.6753	8.1650	7.6547	7.1443
5	10.2062	9.6959	9.1856	8.6753	8.1650	7.6547	7.1443
6	10.2062	9.6959	9.1856	8.6753	8.1650	7.6547	7.1443
9	30.6186	29.0877	27.5567	26.0258	24.4949	22.9640	21.4330
12	30.6186	29.0877	27.5567	26.0258	24.4949	22.9640	21.4330
15	30.6186	29.0877	27.5567	26.0258	24.4949	22.9640	21.4330
18	30.6186	29.0877	27.5567	26.0258	24.4949	22.9640	21.4330
24	61.2372	58.1753	55.1135	52.0516	48.9898	45.9279	42.8660

Figure 2: Comparative dissolution profiles of the ideal Higuchi model and test product

Table 4: Average absolute difference of AUCs (AADA) at different percentage deviations from ideal Higuchi model

Time(hr)	AADAs values for percentage deviation from Higuchi model
Time(hr)	5	10	15	20	25	30
0	0	0	0	0	0	0
1	0.5105	1.0210	1.5315	2.0420	2.5525	3.0630
2	0.5105	1.0210	1.5315	2.0420	2.5525	3.0630
3	0.5105	1.0210	1.5315	2.0420	2.5525	3.0630
4	0.5105	1.0210	1.5315	2.0420	2.5525	3.0630
5	0.5105	1.0210	1.5315	2.0420	2.5525	3.0630
6	0.5105	1.0210	1.5315	2.0420	2.5525	3.0630
9	1.5315	3.0630	4.5945	6.1260	7.6575	9.1890
12	1.5315	3.0630	4.5945	6.1260	7.6575	9.1890
15	1.5315	3.0630	4.5945	6.1260	7.6575	9.1890
18	1.5315	3.0630	4.5945	6.1260	7.6575	9.1890
24	3.0630	6.1260	9.1890	12.2520	15.3150	18.3780

Table 5: Percentage deviation for the test product from an ideal 24 hr zero order drug release (CPDR is cumulative percentage of drug release)

Time (hr)	√Time	Ideal zero order		Test product		Absolute difference of AUCs	% deviation from zero-order (α)
Time (hr)	√Time	CPDR	AUC	CPDR	AUC	Absolute difference of AUCs	% deviation from zero-order (α)
0	0	0	0	0	0	0	0
1	1.000	4.167	10.206	5.812	2.906	7.300	71.500
2	1.414	8.334	10.206	9.718	3.216	6.990	68.461
3	1.732	12.501	10.206	13.628	3.710	6.496	63.625
4	2.000	16.668	10.206	17.721	4.200	6.006	58.827
5	2.236	20.835	10.206	21.612	4.643	5.564	54.491
6	2.449	25.002	10.206	25.426	5.019	5.187	50.801
9	3.000	37.503	30.619	36.817	17.133	13.486	44.028
12	3.464	50.004	30.619	49.621	20.058	10.561	34.478
15	3.873	62.505	30.619	60.147	22.441	8.178	26.698
18	4.243	75.006	30.619	73.158	24.639	5.980	19.523
24	4.899	100.008	61.237	97.264	55.927	5.310	8.668

Table 6: Model fitting of test formulation with two-tiered approach

Release model	Time(hr)	R²	SSR	F	Slope	Intercept
Higuchi model	0-24	0.9238	755.186	75.519	20.072	-16.797
	0-6	0.9435	27.215	5.443	10.352	-2.602
	7-24	0.9928	15.479	5.159	31.754	-60.304
Hixson- Crowell model	0-24	0.9159	0.036	0.004	-0.0253	1.042
	0-6	0.9975	1.549	3.099	-0.0151	0.997
	7-24	0.9369	0.0122	0.0041	-0.0369	1.243

CONCLUSION:

The present study is used to develop Nicorandil floating tablets using combination of hydrophilic and hydrophobic polymers. In vitro drug release is calculated for all the formulations and the best formulation (MCS4) is selected which contain the identical drug as that of theoretical profile. The drug release mechanism from the best formulation is confirmed as Higuchi model (drug release by diffusion) rather than Hixson-Crowell model (drug release by dissolution). A quantitative mathematical model is developed for expression of the deviation from Higuchi model, which results the greater deviation from ideal release along with higher value of SSR. Two-tiered method is used to decrease the difference between observed and predicted value. Finally it can be concluded that, the SSR value is reduced by the application of two-tiered method and also confirmed that the first phase follows Hixson-Crowell model up to 6 hr and then confirmed to follow Higuchi model for drug release from tablets.

ACKNOWLEDGMENTS:

The authors wish to thank Torrent Pharmaceuticals (P) Ltd., Gujarat (India), for the supply of Nicorandil as gift sample. The authors also like to thank management of SSPC, for providing facilities used in the research.

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