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Year : 2015  |  Volume : 6  |  Issue : 1  |  Page : 20-26

Formulation variable study and optimization of taste masked mouth dissolving tablets using design of experiment

Department of Pharmaceutics, SRMS CET, Pharmacy, Bareilly, Uttar Pradesh, India

Date of Web Publication8-Jan-2015

Correspondence Address:
Vijay Sharma
Department of Pharmaceutics, SRMS CET, Pharmacy, Bareilly, Uttar Pradesh
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/2394-2002.148887

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Background: Aim of present work is to prepare and optimized mouth dissolving tablets (MDTs) by using tasteless complex of levocetirizine. Materials and Methods: Formulation and optimization of tablets was done by using computer optimization technique. Formulated taste masked complex of drug was characterized by taste evaluation, percentage drug loading, thermal analysis and X-ray diffraction pattern. Optimization of MDTs was done by considering concentration of binder (polyvinylpyrrolidone [PVP] K30) and super-disintegrant (Kyron T-314) as independent variables whereas wetting time (WT), friability (Fr) and amount of drug release in 15 m (Q 15 ) as dependent variables. Response surface plots and contour plots were drawn, and optimum formulations were selected by feasibility and grid searches. Result and Discussion: By using 3 2 central composite design (CCD) optimized batch was obtained for which value of independent variable, PVP K30 (X1) and Kyron T-314 (X2) was 15 mg and 21 mg respectively and for dependent response, that is, Fr, WT and Q 15 to be 0.42%, 11.8 s. and 91.16% respectively. Validation of optimization study indicated very high degree of prognostic ability of response surface methodology (RSM). By analyzing the observed value to predicted value for Fr, WT and Q 15 the regression coefficient value was found to be 0.950, 0.961 and 0.957. Linearity of plot concluded that desired predicted response of all check-point batches were close to the predicted values and show the validity of data. Conclusion: Hence, optimized formulated batches were formulated by proper balancing of concentration of independent variables to attain desired dependent response using 3 2 CCD. Thus, 3 2 CCDs is an efficient tool in optimization experiments. High degree of outcome obtained using RSM concludes that 3 2 CCD is quite efficient in optimizing drug delivery systems that exhibit nonlinearity in response.

Keywords: Central composite design, drug resin complex, levocetirizine, Tulsion-335

How to cite this article:
Sharma V, Singh L. Formulation variable study and optimization of taste masked mouth dissolving tablets using design of experiment. Drug Dev Ther 2015;6:20-6

How to cite this URL:
Sharma V, Singh L. Formulation variable study and optimization of taste masked mouth dissolving tablets using design of experiment. Drug Dev Ther [serial online] 2015 [cited 2019 Aug 18];6:20-6. Available from: http://www.ddtjournal.org/text.asp?2015/6/1/20/148887

  Introduction Top

Among all route of administration, an oral route is most important and preferable route of administration for solid dosage forms. [1] Tablets are the most common solid dosage form, administered orally, but many patients specially children, mentally ill patients and geriatrics have problem in swallowing the tablets. [2],[3] Mouth dissolving tablets (MDTs) have the advantage of the ease of administration and rapid onset of action. Further, there is an advantage of rapid disintegration without use of water in the oral cavity. When MDT is kept in the oral cavity then saliva quickly penetrates into tablet pores and causes rapid disintegration. [4]

Levocetirizine is a selective, potent, third-generation and nonsedative oral antihistamine H1 receptor antagonist of the latest generation that is licensed for the symptomatic treatment of allergic rhinitis. [5] The therapeutic efficacy of oral levocetirizine has been calculated in several clinical studies in patients with allergic rhinitis. [6] Levocetirizine is rapidly and extensively absorbed following oral administration, with a peak plasma concentration usually attained in 0.9 h. Antihistaminic effects occur within 1-h. Symptomatic improvement is observed as early as 1-day after the initiation of therapy for allergic rhinitis or chronic idiopathic urticaria. The duration of antihistaminic effects persist for at least 24 h. [7],[8],[9],[10],[11] It is seen that most of the drugs are extremely bitter in taste, such drugs are loaded in ion exchange resin (IER) to make tasteless either by batch process or column process. A number of techniques are available to mask the bitter taste of drug, among those most popular and commercial technique is taste masking by using IER. [12] A number of super-disintegrants such as croscarmellose sodium, Kyron T-314 and sodium starch glycolate are used for rapid disintegration of the tablet. [13],[14],[15],[16],[17],[18],[19],[20] Hence, the objective of this work was to formulate and optimize MDTs of levocetirizine hydrochloride (LVZ), after taste masking with help of suitable IER, to check the combined effect of dry binder (polyvinylpyrrolidone [PVP] K30) and super-disintegrant (Kyron T-314) by applying 3 2 central composite design (CCD) to get a formula of tablet which disintegrate in a least seconds with less friability (Fr) and still have maximum drug release in least time.

  Experimental Top


Levocetirizine hydrochloride was obtained from Yegna Manojavam Drug and Chemicals ltd.(A.P.) India. Tulsion-335 was gifted by Geneka Healthcare, Hardwar (U.K.), India, PVP K30 was purchased from Rolex chemical industries, Mumbai, India,. Talc, Magnesium stearate and Mannitol were purchased form S.D. Fine Chemicals Ltd. Mumbai, India. Polacrilin Potassium (Kyron T-314) was purchased from Corel Pharma Pvt. Ltd. Ahmedabad, and micro crystalline cellulose (MCC) (Avicel pH 101) from Gujarat Microwax Pvt. Ltd. Ahmedabad, India. All the chemical and solvent used were of analytical grade.

  Materials and Methods Top

Formulation of taste masked drug resin complex

Batch method was used to prepare drug resin complex (DRC). IER, Tulsion-335(600 mg) was placed in a beaker containing deionized water (25 mL) and allowed to swell for desired period (60 m). After that specific quantity (100 mg) of LVZ was added and stirred for a period of 240 m. The mixture was filtered through Whatman filter paper no.41 and residue was washed with deionized water and dried. [21]

Characterization of drug resin complex

A quantity of DRC equivalent to 5 mg of LVZ was added to each of the six volumetric flasks containing 10 mL of phosphate buffer of pH 6.8. The mixtures were shaken for 0, 15, 30, 60, 120, and 300 s and filtered. Content of LVZ in each filtrate was determined. For satisfactory taste masking, the amount of drug dissolved at the end of 120 s should not be more than the threshold bitterness concentration of the drug. [22]

Confirmation of complex formation

Powder X-ray diffraction studies

The powder X-ray diffraction (XRD) pattern of LVZ, Tulsion-335 and DRC were taken by Philips PW 1729 X-ray diffractometer Le group interconnexion, Scient Jurie, Cadlada. Radiation generated from copper source with a wavelength of 30 mA at 40 kV and the range of 5 × 10-3 cycles/s was used. [23],[24]

Thermographic study by differential scanning calorimetry

A mettler Toledo differential scanning calorimeter (DSC) 821 (Mettle Toledo, Griefensci, Switzerland) equipped with an in cooler and refrigerated cooling system was used to analyze the thermal behavior of LVZ and DRC. Sample (5-10 mg) was heated in hermetically sealed aluminum pans at temperature 20°C/m. Nitrogen were purged at 50 mL/m and 100 mL/m through cooling unit. [24],[25]

Drug content study

A total of 100 mg of DRC was stirred well at 100 rpm with 100 mL of 0.1 N hydrochloric acid (HCl) for 60 m to release the entire drug from DRC. This mixture was then filtered, and 1 mL of the filtrate was diluted to 100 mL of 0.1 N HCl. The absorbance of this solution was measured by ultraviolet (U.V) spectrophotometer (Shimadzu 1800, Japan) at 231 nm by using 0.1 N HCl as blank, and the content of LVZ was calculated. [22]

Experimental design

A 3 2 CCD was adopted for optimization study. Two independent variables investigated were functional excipients such as a dry binder (PVP K30, X1) and super-disintegrant (Kyron T-314, X2). The effects of these independent variables were investigated on the dependent responses such as percentage Fr, WT and Q 15 . The experimental points used according to the design shown in [Table 1]. Polynomial equations were generated and used to express the function of independent variables (PVP K30 and Kyron T-314)
Table 1: 32 central composite design layout, experimental runs and their actual combinations

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Y =

b 0 + b 1 X 1 + b 2 X 2 + b 3 X 1 X 2 + b 4 X 1 2 + b 5 X 2 2 +b 6 X 1 X 2 2 + b 7 X 1 2 X 2 (1)

Where Y is the dependent variable, b 0 is the arithmetic mean response of the thirteen runs.

The main independent variables, that is, effects X 1 and X 2 represent the average result of changing one factor at a time from its lower values to its higher values.

3 2 CCD is most efficient in estimating the influence of individual variables (main effects) and their interactions using minimum experimentation. In the present study, 3 2 CCD was considered to be better as the values of the response surfaces were not known from the previous findings. Hence, 3 2 CCD was chosen for optimization of formulations. Based on preformulation trials, levels of Kyron T-314 were selected as 7.5, 15, and 22.5 mg; whereas PVP K30 levels were 7.5, 11.25 and 15 mg. Thirteen formulation was formulated by taking nine possible combination among which center point was repeated 4 times and mean values were taken for further study. The responses were analyzed using Design Expert® (trial version). The models were tested for significance. Four formulations (VC1 to VC4) were selected as the confirmatory check-points, and these were validated by response surface methodology. The observed and predicted responses were critically compared. Linear correlation plots were constructed for the chosen check-point formulations. The residual graphs between predicted and observed responses were also constructed separately and the percent bias (% prediction error) was calculated with respect to the observed responses. After studying the responses surfaces for all properties feasibility and grid searches through MS-excel (Microsoft, USA) utility and overlay plot generation method through design, expert were used for finding the optimized product.

Optimized product was validated taking total four formulations selected as check-points. The tablet formulation using the chosen formulation composition from the grid search were formulated and tested for various evaluation parameters. Further linear correlation plots were made between the observed and predicted responses with a line pass through the origin. Plots between predicted and observed responses were compared.

Formulation of mouth dissolving tablets by using 3 2 central composite design

Drug resin complex was used to prepare MDT by direct compression technique. First of all, formulation of MDTs was done by direct compression technique for batch B1 to B13 by taking DRC equivalent to 5 mg of LVZ [Table 2]. MCC was used as diluent, PVP K 30 as a dry binder, mannitol as a soothing agent, talc as an antiadherent and magnesium stearate as a lubricant. All the ingredients were accurately weighed and passed through sieve number 100 and mixed with DRC. The above powder blend was compressed using rotary die press (Rimek, minipress-I, 16 station rotator, Karnawati, India) using 7 mm concave punches.
Table 2: Formulation of LVZ tablets

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Evaluation of tablets

Physicochemical characterization

Hardness of formulated tablets was evaluated by using Monsanto hardness tester, Fr by using Roche friabilator and weight variation also done as per pharmacopieal standards. [26],[27]

Drug content uniformity was determined by taking five tablets, selected randomly, crushed and dissolved in 100 mL of 0.1 N HCl, stirred for 60 min, and filtered. Absorbance of this solution was measured at 231 nm using 0.1 N HCl as blank and content of the drug was estimated. [28]

In-vitro disintegration time (DT) was determined by taking 6 mL of phosphate buffer of pH 6.8 in a 25 mL measuring cylinder. Temperature of which was maintained at about 37 ± 0.5°C. Formulated MDT was put into it, and time in which tablet disintegrated completely was noted. [29]

WT of formulated tablets was measured by placing a tablet on a piece of tissue paper folded twice, and was placed in a small Petri dish containing 6 mL of simulated saliva pH 6.8, and the time for complete wetting was measured a small quantity of amaranth red color was put on the upper surface of the tablet. Time required for the upper surface of the tablet to become red was noted as the wetting time of the tablet. [30]

Dissolution studies

Dissolution test was carried out using USP type II dissolution test apparatus at 37 ± 0.5°C and 50-rpm speed using 900 mL. Of 0.1 N HCl as dissolution medium. Aliquots equal to 5 mL were withdrawn at specific time intervals, and amount of LVZ released in 15 s (Q15) from DRC was determined by U.V. spectrophotometer at 231 nm. [31]

  Results Top

Characterization of formulated drug resin complex

Panel of healthy human volunteers for taste masking evaluation shows satisfactory masking of taste using time intensity method. Formulated DRC shows excellent taste masking effect of the resins. Most of the volunteers reported 20 μg/mL as the threshold bitterness concentration for LVZ HCl.

Complexation between the drug and resin is essentially a process of diffusion of ions between the resin and surrounding drug solution. As the reaction is an equilibrium phenomenon, maximum efficacy is best achieved in a batch process. Complexation process in between drug and resin depends on pKa value of both, involves the exchange of ions. A maximum drug loading was found 98.47 ± 19.76 w/w, which was taken for further formulation of tablets.

In [Figure 1], several sharp peaks in XRD spectra of pure drug indicate that crystalline nature of LVZ. XRD pattern of DRC shows the disappearance of characteristic peaks of drug and also found to be broadened, these finding suggest the formation of DRC.
Figure 1: X-ray diffractions pattern of drug resin complex and levocetirizine hydrochloride

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By DSC curves as shown in [Figure 2], the thermal behavior of pure drug LVZ shows peak endotherm at 213.55°C corresponding to the loss of water of crystallization and melting of pure drug. Thermal behavior of DRC shows peak endotherm at 70.29°C the reduction of height and sharpness of endotherm is due to loading of drug in resin. That shown, there was no interaction between drug and complex. It concludes that there is no interaction between drug and resin due to complexation process and indicates the amorphous nature of DRC.
Figure 2: Differential scanning calorimeter thermograms of drug resin complex and levocetirizine hydrochloride

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Characterization of formulated mouth dissolving tablets

Characterization of formulated MDTs was done for different parameters such as weight variation, hardness, Fr, thickness, in-vitro DT, wetting time and in-vitro dissolution study [Figure 3], and results are as shown in [Table 3].
Figure 3: Drug release profile

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Table 3: Characterization of formulated MDTs

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Data analysis

Statistically analyzed data clearly indicate that the WT, Fr and Q 15 values are heavily depending upon the selected independent variables [Table 4]. Equations 1-3, relate the responses of WT, Fr and Q 15 as ANOVA response for various dependent variables are like:
Table 4: ANOVA for selected statistical model

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Y 1 =

22.41-5.0X 1 -13.0X 2 -0.5 X 1 X 2 +1.55X 12 +3.55X 22 +0.50X 12 X 2 +1.50 X 1 X 22 (2)

Y 2 =

0.65-0.09 X 1 -0.22 X 1 +0.015X 1 X 2 +0.00031X 12 +0.018X 22 -0.0005X12
X 2 +0.020X 1 X2 2 (3)


93.28-3.83 X 1 +495X 2 -0.18 X 1 X 2 +1.03 X1 2 +0.223X2 2 +0.58 X1 2 X 2 -0.28 X 1 X2 2 (4)

Y 1 , Y 2 and Y 3 represent WT, Fr and Q15

Response surface analysis

It was observed that WT, Fr and Q 15 were depending on both the factors, that is, Kyron T-314 and PVP K30. There was an almost linear decrease in the WT with increase in the levels of both factors. The counter plot also shows that combine effect although is decreasing but not totally linear for WT [Figure 4]a.
Figure 4: Response surface and counter plot for - (a) (wetting time), (b) (friability) and (c) (Q15) showing influence of concentration of independent variables

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[Figure 4]b suggest that Fr of MDT sharply decreases PVP K30 while its value decreases with an increase in Kyron T-314 but the decrement in the value is not very significant. [Figure 4]c suggest that Q 15 of MDT increases rapidly by increase in Kyron T-314 while its value decreases with an increase in concentration of PVP K30 hence both the independent factors are having significant effect over the drug release.{Figure 4}

Overlay plot obtained from design expert software showing area (Darker area in the plot, [Figure 5]) for optimum desired values; also confirm that optimized product is within the area.
Figure 5: Overlay plot for optimized batch

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Validation of the statistical model

The predicted responses of the all formulated batches and its corresponding actually (experimentally) observed values were found to be in close agreement as indicated in [Table 5]. Thus, the models developed to predict the responses were not only significant statistically, but also found to be valid to predict values that were very close to the observations made experimentally [Figure 6].
Figure 6: Predicted versus observed response for (a) friability (b) wetting time (c) Q15

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Table 5: Validation of response surface methodology

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  Discussion Top

Batch process is one of the preferred methods adopted for loading of drug IERs. In a batch process, higher swelling efficiency makes more surface area available for ion exchange. Swelling and hydration increases the rate and extent of ion exchange process. In the case of unswollen resin matrix, the exchangeable groups are latent and coiled towards the backbone. By swelling of the IER surface area get increases, and these groups get oriented towards the outside. pH is also having a dominant effects over drug loading process.

The formation of ion exchange complex between LVZ and Tulsion-335 was confirmed by XRD and DSC studies. Several sharp peaks in XRD spectra of pure drug represent the crystalline nature of drug while a diffused peak in XRD spectra of Tulsion-335 represents amorphous nature of resin. However, on the other hand XRD pattern of DRC shows the disappearance of characteristic peaks of drug and also found to be broadened, these finding suggest the formation of DRC.

By DSC curves, the thermal behavior of pure drug LVZ shows peak endotherm at 213.55°C corresponding to the loss of water of crystallization and melting of pure drug. Thermal behavior of IER (Tulsion-335) shows peak endotherm at 152.28°C while thermal behavior of DRC shows peak endotherm at 70.29°C the reduction of height and sharpness of endotherm is due to loading of drug in resin. That shown, there was no interaction was observed between drug and complex. It concludes that, resin was not affecting the characteristic of drug due to complexation process and indicates the amorphous nature of DRC.

Optimizations of formulated tablets were done by using 3 2 CCD. The outcomes for response parameters, that is, WT and Fr, were subjected to regression analysis and statistical models were found to be significant. Observed responses, WT, Fr and Q 15 indicate good relation between the dependent and independent variables. The WT, Fr and Q 15 for all thirteen batches (B1 to B13) showed a wide variation (i.e., 10-42 s, 0.39-0.99 and 75-99.96 respectively).

The F value in [Table 4] is the ratio of model mean square to the appropriate error mean square. The F distribution is dependent on the degrees of freedom (df) for the variance in the numerator and the df of the variance in the denominator of the F ratio. In the model, F value is 31.88 for WT, 265.19 for Fr and 54.66 for Q15,
and high R 2 values suggest that these models are significant. Values of " P" < 0.05 suggest that model terms are significant. In this case, the models generated for WT, Fr and Q 15 are significant. Adequate precision measures the signal-to-noise ratio. A ratio >4 is desirable. The adequate precision of value 18.168, 55.640 and 24.442 respectively, for WT, Fr and Q 15 models indicate an adequate signal for each. These models can be used to navigate the design space. It was observed that DT was dependent on both independent variables. A linear decrease in the WT was observed with an increase in the levels of both independent variables. It was observed from the response surface and contour plots that both the independent variables influence the Fr of the tablets. There was a linear decrease in the values of Fr, as the levels of Kyron T-314 and PVP K30 were increased. PVP K30, being a binder, decreases the Fr of the tablet. Fr was observed optimum at high levels of both factors. Response curve and counter plot between Q 15 and independent variable PVP shows a significant effect over the Q 15 that is, its decreases the value of Q 15 significantly while in combination its significance increases.{Table 4}

Validation of optimized batch was done by formulating four different batches by considering the optimum value as found in overlay plot as shown in [Figure 5] and by the comparison of observed values with the predicted responses, it was observed that models were found to be valid and showed close agreement.{Figure 5}

  Conclusion Top

The presented research work result in complete taste masking of bitter taste of LVZ by formulating DRC with Tulsion-335 and fulfill the first and foremost requirement of MDT. The work proves that CCD optimization techniques are much helpful for getting optimized product without the need of rigorous experimental work with saves time and a better product may be obtained. Thus the hiccup of balancing the two or more variables may be easily surpassed using the CCD. The method may be used for developing a better MDT and it may pave the way for further work.

  References Top

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  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]


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