CC BY-NC-ND
0Bulletin of Faculty of Pharmacy, Cairo University (2013) xxx, xxx-xxx
Cairo University Bulletin of Faculty of Pharmacy, Cairo University
www.elsevier.com/locate/bfopcu www.sciencedirect.com
ORIGINAL ARTICLE
Development and optimization of fast dissolving oro-dispersible films of Granisetron HCl using Box-Behnken statistical design
Hema Chaudhary *, Samita Gauri, Permender Rathee, Vikash Kumar
P.D.M. College of Pharmacy, Sector 3A, Sarai Aurangabad, Bahadurgarh, India Received 19 December 2012; accepted 20 May 2013
KEYWORDS
Fast oro-dispersible film; Drug design; Box-Behnken design; Optimization
Abstract The aim was to develop and optimize fast dissolving oro-dispersible films of Granisetron hydrochloride (GH) by two-factor, three-level Box-Behnken design as the two independent variables such as X1 (polymer) and X2 (plasticizer) were selected on the basis of the preliminary studies carried out before the experimental design is being implemented. A second-order polynomial equation to construct contour plots for the prediction of responses of the dependent variables such as drug release (Yj), Disintegration time (Y2), and Y3 (Tensile strength) was studied. The Response surface plots were drawn, statistical validity of the polynomials was established to find the compositions of optimized formulation which was evaluated using the Franz-type diffusion cell. The designs establish the role of the derived polynomial equation and contour plots in predicting the values of dependent variables for the preparation and optimization.
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1. Introduction
The ultimate goal of any drug delivery system is the success-
ful delivery of the drug, in which almost 90% of the drugs are
administered to the body for the treatment of various disor-
ders and diseases as it is regarded as the safest, most convenient and most economical method of drug delivery having the highest patient compliance.1-3 In this the drug is dissolved
Corresponding author. E-mail address: hema.manan@gmail.com (H. Chaudhary). Peer review under responsibility of Faculty of Pharmacy, Cairo University.
or swallowed and then enters into the systemic circulation to produce the desired effect.4'5 Despite of astounding advancement in drug delivery the oral route of drug administration is considered as the most important method of administration of drug for systemic effect because of self medication, ease of administration and avoidance of pain compared to paren-teral route.6-9
1.1. Anatomy of oral cavity
Oral cavity offers a unique environment for delivering the drugs (Fig. 1). The oral mucosa allows direct access of drug to the systemic circulation and avoids first pass metabolism. The epithelium of the oral cavity is quite similar to that of the skin, with slight differences with regard to keratinization, protective and lubricant mucous which is spread across its sur-
1110-0931 © 2013 Production and hosting by Elsevier B.V. on behalf of Faculty of Pharmacy, Cairo University. http://dx.doi.Org/10.1016/j.bfopcu.2013.05.002
Figure 1 Sectional view of oral cavity and anatomy of oral cavity (http://www.edoctoronline .com/zmedical-atlas.asp?c = 4&id = 21667).
face.10 The permeability of oral mucosa is 4-1000 times greater than that of the skin. The oral cavity is divided into two regions: outer being the oral vestibule bounded by the lips and cheeks; the hard and soft palates, the floor of the mouth and tonsils.11 It is the forceful expulsion/discharge of gastric contents, or may be a protective physiological mechanism, that prevents entry of potentially harmful substances into the gastrointestinal tract. Vomiting can lead to dehydration, bleeding, severe alkalosis and rarely esophagus perforation irrespective of the cause of vomiting. Vomiting is to be differentiated from retching, regurgitation or rumination. Retching involves the same physiological mechanisms as vomiting, but it occurs against a closed glottis and there is no expulsion of gastric contents. Regurgitation is the return of small amounts of food or secretions to the pharynx in the form of mechanical obstruction of the esophagus. Rumination is similar to regurgitation, except small amounts of completely swallowed food are returned to the hypopharynx from the stomach and is often re-swallowed. The vomiting reflex is triggered by the stimulation of chemoreceptors in the upper gastrointestinal tract (GIT) and also the mechanoreceptors in the wall of the GIT which are activated by both contraction and distension of the gut as well as by physical damage. A coordinating center which is present in the central nervous system controls the emetic response. This center is located in the lateral medullary region of the brain. Afferent nerves to the vomiting center arise from abdominal splanchnic and vagal nerves, vestibulo-laby-rinthine receptors, the cerebral cortex and the chemoreceptor trigger zone (CTZ). The CTZ is exposed to emetic stimuli of endogenous origin such as hormones associated with pregnancy and to stimuli of exogenous origin such as drugs.12 Oral drug delivery has been known for decades as the most widely utilized route of administration among all the routes that have been explored for the systemic delivery of drugs via various pharmaceutical products of different dosage forms. The development of a pharmaceutical product for oral delivery irrespective of its physical forms (solid, semisolid, or oral liquid dosage form) involves varying extents of optimization of dosage form.13
1.2. Fast dissolving drug delivery system (FDDS)
Fast dissolving drug delivery system is a new generation delivery system also known as fast dissolving/disintegrating film for the oral delivery of the drugs which came into existence in the late 1970's as an alternative to tablets, capsules, syrups and other formulations for pediatric and geriatric patients, who experience difficulties in swallowing traditional solid dosage forms which combines both the advantages of conventional tablet and of liquid formulation.14 FDDS is easy to administer and provides better patient compliance in the elderly, pediatric, mentally retarded, nauseated and uncooperative paients.15 This delivery system consists of the solid dosage forms that dissolve quickly
1.e. within a matter of seconds in the oral cavity without the administration of water. The delivery system consists of a very thin oral strip which is simply placed on the patient's tongue or any other oral mucosal tissue and instantly gets wetted by sal-iva.16 The film rapidly hydrates onto the site of application. It then rapidly dissolves and disintegrates to release the medication for oro-mucosal absorption. Fast dissolving oral thin films are widely accepted by patients and also to the caregiver for their ease-of-delivery, portability and accurate dosing.17 The robustness of the film depends upon the type and amount of polymer used and general dissolution time for orally dissolving film is 5-20 min. as per pharmacopoeia.18'19 They also provide quick onset of action within few seconds as the oro-mucosal absorption of drug occurs directly from the site of administration to the systemic circulation avoiding first pass metabolism to produce the desired effect.20
2. Materials and methods
Granisetron Hydrochloride (GH) was pure (100.2% w/w Granisetron according to analysis by manufacturer) and was received from Natco Pharma, Hyderabad (India). Hydroxypropyl methyl cellulose 15 cps, Saccharin sodium and polyvinyl pyrrolidone K-30 were obtained from Central Drug House (Delhi, India). Oil of peppermint and glycerin
was bought from SD Fine-Chem limited, Mumbai, India. All the analytical grade materials and double distilled water were used throughout the study.
2.1. Preliminary trials
2.1.1. Selection of polymer
Polymers such as, HPMC and pullulan were tried for the preparation of fast dissolving oro-dispersible films (FDF). Pullulan did not show a good result at 40-50% concentration, whereas films of HPMC in a range of 40% did not give a good film (the film was not easily peelable) and at 50% concentration, the film was sticky in nature. Hence all the percentage between 40-50% was trailed of HPMC. A range of 45-50% was selected for the formulation of films.
2.1.2. Selection of plasticizer
Various plasticizers were selected and trails were done. Propylene glycol below 15% did not show good film properties as was tested by the folding endurance of the film. Hence, a range of plasticizer (propylene glycol) was used in the range of 15-20%.
2.2. Preparation of fast dissolving films (FDF)
The required percentage of polymer solution was prepared by dispersing the polymer powder in distilled water with continuous stirring. After continuous stirring the solution was left undisturbed for three to four hours to remove all the air bubbles. Accurately weighed quantity of drug, plasticizer and all other excipients was separately dissolved in distilled water in another beaker. After complete hydration of the polymer with
water, drug-plasticizer and all other excipient solutions were added and mixed thoroughly, and the volume was made up ten milliliters with distilled water. The polymeric solutions were then poured on the mold, allowed to dry and stored in aluminum foil. The different formulations were prepared incorporating polymer (45-50% w/w), plasticizer (15-20% w/ w), and water using Box-Behnken experimental design and optimized formulation was generated using statistical screening. The thirteen runs of the experiment were evaluated for the percentage drug release (Y1), disintegration time (Y2), and tensile strength (Y3) and are listed in Table 2.
2.3. Determination of evaluation parameters
Properties such as homogeneity, color, transparency and surface of the oral films were evaluated by visually inspection.2 The film strip (2 x 2 cm) of GH was dissolved in phosphate buffer pH 6.8. The solution was suitably diluted and was analyzed by UV-Visible spectrophotometer at 302 nm.21 The thicknesses of film formulation were evaluated by using micrometer screw gauge. The thicknesses of six films were taken and then average thickness was calculated.22 The film (2 x 2 cm) was cut and weight of each film was taken in triplicate and the difference in weight variation of film was noted.23 The surface pH of films was evaluated by placing the film in a petridish, slightly wet with the help of distilled water (as an acidic or alkaline pH may cause irritation of the oral mucosa, the surface pH of the film was kept neutral) at room temperature. The pH was noted by bringing the surface of the film in contact with pH meter electrode for one min. and average of fast dissolving films (FDF) was taken in triplicate.2 The prepared films were folded at the same place number of times until
Table 1 Independent variables in design.
Factor Level Used, Actual (Coded)
Independent Variables Low (-1) Medium (0) High(+1)
X1 = Concentration of polymer (% w/w) 45.0 47.5 50.0
X2 = Concentration of plasticizer (% w/w) 15.0 17.5 20.0
Table 2 Design (Box-Behnken) of experiments with results.
Runs Batch Independent variable Dependent variables
Observed value Predicted value
X1 X2 Y1 Y2 Y3 Y1 Y2 Y3
1 FF1 -1 -1 98.0 28.0 0.161 97.98 28.12 0.160
2 FF2 0 0 95.5 26.0 0.179 95.30 26.90 0.180
3 FF3 1 0 92.5 40.0 0.183 92.57 39.43 0.181
4 FF4 0 0 95.2 27.0 0.181 95.30 26.90 0.180
5 FF5 1 -1 92.0 39.0 0.167 91.98 39.45 0.170
6 FF6 0 0 95.2 28.0 0.181 95.30 26.90 0.180
7 FF7 0 1 95.0 30.0 0.185 95.07 30.09 0.190
8 FF8 1 1 92.5 45.0 0.190 92.45 45.12 0.190
9 FF9 0 -1 94.8 30.0 0.167 94.83 29.43 0.170
10 FF10 -1 0 98.3 23.0 0.172 98.33 23.09 0.170
11 FF11 -1 1 98.0 24.0 0.175 97.98 23.79 0.170
12 FF12 0 0 95.4 26.0 0.181 95.30 26.90 0.180
13 FF13 0 0 95.4 27.0 0.181 95.30 26.90 0.180
X1 = Concentration of polymer (% w/w); X2 = concentration of plasticizer (% w/w); Y1 = drug release (%); Y2 = disintegration time (s); Y3 = tensile strength (N/m2).
Figure 2 Fast dissolving film of GH.
it broke. By the number of times a film is folded at the same place without cracking or breaking revealed the best endur-ance.24 The formulated fast dissolving films (FDF) were weighed initially and placed in a desiccator containing anhydrous calcium chloride for three days. After three days, the fast dissolving films (FDF) were taken out and weighed again. The percentage moisture loss was calculated according to the
formula25:
Percentage moisture loss = initial weight
— final weight/initial weight*
The fast dissolving films (FDF) free of imperfections were held between two clamps at a distance of three centimeters with a two kilogram load cell. The film was pulled at a rate of 100 mm/min and force required to break the film was measured when the film broke.26.
2.4. Design of experiments
Box-Behnken designs are experimental designs for response surface methodology devised by George E.P. Box and D. Behnken in 1960. The Box-Behnken design for three factors involves three blocks in each of which 2 factors are varied through the four possible combinations of high and low. It is necessary to include center points as well (in which all factors are at their central values). A 2-factor, 3-level design used is
suitable for exploring quadratic response surfaces and constructing polynomial models with Design Expert® version 8.0.7.1 The two independent variables such as polymer (X1) and plasticizer (X2) were selected on the basis of the preliminary studies carried out before the experimental design is being implemented. The experimental design was applied to investigate the effect of different independent variables such as X1, and X2. The interaction term (X1X2) shows how the response changes when two factors are changed simultaneously. The polynomial terms (xJx2) are included to investigate nonlinear-ity.27,28 The design of experiments generated polynomial equation, is given as;
Y = be + b X1 + b2X2 + ^2X1X2 + bn X? + b2iX22
where, Yo is the dependent variable; bo is the intercept; b1-b22 are the regression coefficients computed from the observed experimental values of Y; and X1, X2 are the coded levels of independent variables. A total of 13 runs were generated, selected independent variables were polymer concentration (X1) and plasticizer concentration (X2) and the levels of each factor were low, medium, and high as listed in Table 1. The amount of polymer concentration (X1) and plasticizer (X2) used to prepare each of the formulations and their observed and predicted responses are given in Table 2.
2.5. In-vitro drug permeation
Permeation studies were carried out in order to calculate the percentage amount of drug permeating through the oral mucosa.
2.5.1. Selection of oral mucosa
A specific methodology was employed to study buccal drug absorption/permeation characteristics, special attention is warranted to the choice of experimental animal species for such experiment. For investigations, many researchers have used rats and hamsters.29,30 The oral mucosa of larger experimental animals that has been used for permeability and drug delivery studies include monkey, dog and pigs.31 Porcine oral mucosa was used as the model membrane. The buccal pouch of the freshly killed pig was procured from the local slaughter house. The buccal mucosa was excised and trimmed evenly from the sides and then washed in an isotonic phosphate buffer of pH 6.8 and used.
Table 3 Data of evaluation parameters.
Formulation code Drug content (%) Thickness (mm) Weight variation (mg) Surface pH Folding moisture Endurance Loss (%)
FF1 98.91 0.18 67.33 7.13 192 7.12
FF2 98.63 0.23 67.00 6.90 202 4.47
FF3 99.45 0.26 69.33 6.70 392 4.61
FF4 98.91 0.23 67.00 6.90 202 4.47
FF5 98.63 0.23 70.00 6.63 356 7.14
FF6 98.63 0.23 67.00 6.90 202 4.47
FF7 99.45 0.24 69.33 6.73 237 7.50
FF8 98.91 0.30 68.67 6.70 402 4.65
FF9 98.91 0.24 69.33 6.73 237 7.50
FF10 99.72 0.21 68.67 6.87 202 6.98
FF11 99.72 0.22 69.33 6.87 260 3.89
FF12 98.63 0.23 67.00 6.90 202 4.47
FF13 98.63 0.23 67.00 6.90 202 4.47
Figure 3 In-vitro drug release profiles of fast dissolving films.
2.5.2. Permeation studies
Ex-vivo permeation studies were carried out through porcine oral mucosa using modified Franz diffusion cell. The system consisted of donor chamber and receptor chamber, jacket, and sampling port. The buffer was warmed with the in built heater and then assembly was set thermostatically at 37 0C. A Teflon coated mini magnetic bead was placed in the receiver compartment for agitating the contained vehicle at 50 rpm (i.e. rotations/min of magnetic bead within diffusion cell). The receptor compartment was filled with vehicle, containing phosphate buffer pH 6.8. Receptor fluid was sonicated to remove dissolved gases and equilibrated at 37 0C before placing in the receptor compartment. Porcine oral mucosa was used as the model membrane. The mucosa was mounted between the donor and receptor compartments. The receptor compartment was filled with 15 ml of isotonic phosphate buffer of pH 6.8 and the hydrodynamics were maintained by stirring with a magnetic bead at 50 rpm. Optimized film of dimensions 2 x 2 cm loaded with one mg of drug, previously weighed was placed in intimate contact with the mucosal surface of the membrane that was previously moistened with a few drops of phosphate buffer. The donor compartment was filled with 1 ml of phosphate buffer of pH 6.8. Samples were withdrawn at suitable intervals of 5, 10, 15, 20, 25 and 30 min, replacing the same amount with the fresh medium.
2.6. Data analysis
Statistical validation of the polynomial equation generated by Design Expert version® was established on the basis of ANOVA provision in the software. A total of 13 runs (FF1-FF13)
Figure 4 Contour plot showing the effect of polymer concentration (X1) and plasticizer (X2) on response Y1.
with triplicate center points were generated. The resultant experimental data of response properties were compared with those of the predicted values.
3. Result and discussion
3.1. Optimizations of independent variables
HPMC in a range of 45-50% was selected for the formulation of fast dissolving films (FDF). It was found that on increasing the amount of polymer above 50% the percentage drug release and disintegration time kept on increasing; while at 40% the disintegration time kept on decreasing. Plasticizer was selected in the range of 15-20%. Since above 20% FDF became stickier and below 15% the film did not show good flexibility of FDF.
3.2. Characterization of fast dissolving films (FDF)
Granisetron HCl (GH) oro-dispersible films prepared were transparent, colorless, thin, and soft, with no spot on the film surface (Fig. 2). The prepared FDF was evaluated according to the following parameters: % drug content, thickness, weight variation, surface pH, folding endurance and percentage moisture loss as shown below in Table 3.
Table 4 Summary of results of quadratic model for regression analysis of responses Yb Y2, and Y3.
Quadratic model R2 Adjusted R2 Predicted R2 SD %CV
Yi 0.9987 0.9978 Y2 0.9931 0.9881 Y3 0.9986 0.9976 0.9963 0.9760 0.9942 0.096 0.74 0.043 0.10 2.44 0.23
Polynomial equations Y1 = 95.30 - 2.88X1 + 0.12X2 + 0.12X1X2 + 0.15Xi - 0.35X2 Y2 = 26.90 + 8.17X1 + 0.33X2 + 2.50X1X2 + 4.36X? + 2.86X2 Y3 = 0.18 + 5.500X1 + 9.333X2 + 2.000X1X2 - 3.155X2 - 4.655X2
45.CC 46.C0 47.00 48.C0 49.CC 50.CC
Figure 5 Contour plot showing the effect of polymer concentration (X1) and plasticizer (X2) on response Y2.
46.00 46.00 47.00 48.00 40.00 50.00
Figure 6 Contour plot showing the effect of polymer concentration (X1) and plasticizer (X2) on response Y3.
3.3. Evaluation of in-vitro release
The ex-vivo release profiles of films were calculated and the cumulative amount of drug release was found, the results are demonstrated in Fig. 3. Drug release profiles of formulations F1, show an initial phase of release of the drug having low polymer amounts to spread the network of hydrophilic chain around matrix system. The formulation FF10 showed fast release due to the less amount of polymer and plasticizer and minimum in FF5 which was having the highest percentage of polymer which will form a layer around the drug and allow the drug to release at a slow pace. The influences of polymer levels are found to be vital in regulating the drug release.
3.4. Fitting model to the data
Box-Behnken statistical experimental design as the RSM requires 13 runs. The ranges of Yj ,Y2 and Y3 are 92.0098.30%, 23.00-45.00 s and 0.16-0.19 N/cm2, respectively. For all the responses observed for 13 formulations prepared were simultaneously fitted to first order, second order and quadratic models using Design Expert. It was observed that the best-fitted model was quadratic and the comparative values of R-squared, SD, and % CV are given in Table 4 along with the regression equation generated for each response. It is evident that all the two independent variables, namely the concentration of polymer (Xi), concentration of plasticizer (X2), respectively have interactive effects on the three responses, Yb Y2 and Y3. A positive value represents an effect that favors the optimization, while a negative value indicates an inverse relationship between the factor and the response.
3.5. Contour plots and response surface analysis
Two dimensional contour plots were prepared for all the three responses and are shown in Figs. 4-6 for responses Yb Y2 and
Y3, respectively. These plots are known to study the interaction effects (studying the effects of two factors at one time) of the factors on the responses. Linear regression plots between the observed and predicted values of the response properties were drawn (Fig. 7a-c). The linear correlation plots demonstrated high values of R-squared for all the three responses drawn between the predicted and experimental values. The R-squared values of Yb Y2 and Y3 were found to be in the range of 0.9963-0.9978, 0.9960-0.9981 and 0.9942-0.9976, respectively.
3.5.1. Response 1 (Yj): effect on drug release
The model proposes the following polynomial equation for
Drug Release
Y1 = 95.30 - 2.88X + 0.12X2 + 0.12ХЛ + 0.15X1 - 0.35X2
where, Y1 is drug release, X1 is the polymer concentration, and X2 is the concentration of plasticizer. The Model F-value of 1100.58 implies the model is significantp < <0.0001. Therefore this model can be used to navigate the design space. The contour plots (Fig. 4) showed the effect of different independent variables on percentage drug release (Yi). Percentage drug release decreases as the amount of polymer increases form 45% to 50% since the drug remains inside the polymer matrix and vice versa.32 The increase in rate of drug release at 45% could be explained by the ability of the hydrophilic polymers to absorb water, thereby promoting the dissolution, and hence the release, of the highly water-soluble drug. Moreover, the hydrophilic polymers would reach out and hence, create more pores and channels for the drug to diffuse out of the patches.33
The drug release pattern in the fast dissolving films (FDF) is also affected by the concentration of plasticizer (X2) and followed a direct relationship when the amount of plasticizer increases. A positive value for the coefficient (above mentioned equation) is an indicative of the favorable effect whereas a negative value for the coefficient indicates an unfavorable effect. There is only a very little such as 0.01% chance that a ''Model
Figure 7 Linear correlation plots (a, b, and c) between actual and predicted values.
Table 5 Evaluation of physical and chemical stability of optimized batch (FF10) at 40 ± 2 C/75 ± 5% RH as per ICH Q1A (R2)
guidelines stability studies.
Time (days) Physical change Chemical change
Appearance Weight variation Drug content Surface pH
0 Not changed 68.67 99.72 6.87
15 Not changed 68.33 99.45 6.80
30 Not changed 68.21 98.91 6.73
60 Not changed 68.00 98.63 6.70
90 Not changed 67.33 98.58 6.63
F-Value'' this large could occur due to noise. Values of ''Prob > F" < 0.0500 indicate model terms are significant and values >0.1000 indicate the model terms are not significant. If there are many insignificant model terms, model reduction may improve your model. The ''Lack of Fit F-value'' of 0.44 implies the Lack of Fit is not significant relative to the pure error.
3.5.2. Response 2 (Y2): effect on disintegration time
The following polynomial equation prevailed from the model for disintegration time.
Y2 = 26.90 + 8.17X + 0.33X2 + 2.50X1X2 + 4.36XJ + 2.86X2
Figure 8 Determination of shelf life.
where, Y2 is disintegration time. All the formulation showed response of Y2 < 60 s. The Model F-value of 200.36 implies the model is significant p < 0.0001. The ''Lack of Fit F-value'' of 0.48 implies the Lack of Fit is not significant relative to the pure error. There is a 71.45% chance that a ''Lack of Fit F-value'' this large could occur due to noise. Values of ''Prob > F'' < 0.0500 indicate model terms are significant. In this case X1, X2, X1 X2, X"2 X2 are significant model terms. As the concentration of both the independent variables (X1 and X2) increases resulted dependent variable showed a positive response which is illustrated in Fig. 5 (as the amount of polymer and plasticizer increases the disintegration time also increases).
3.5.3. Response 3 (Y3): effect on tensile strength
The polynomial equation for tensile strength was as follows
Y3 = 0.18 + 5.500X1 + 9.333X2 + 2.000X1X2 — 3.155X1 — 4.655X2
where, Y3 is the tensile strength. All the formulation showed the response of Y3, 0.160-0.190. The Model F-value of 1005 taken out and weighed again 43 implies the model is significant (p < 0.0001). There is only a 0.01% chance that a ''Model F-Value'' this large could occur due to noise. In this case X1, X2, X1 X2, X12 X22 were significant model terms and response showed a positive response due to increases in impart flexibility to the film i.e. as the amount of polymer and plasticizer increases the tensile strength also increases(Fig. 6). Values >0.1000 indicate the model terms are not significant. The ''Lack of Fit F-value'' of 0.66 implies the Lack of Fit is not significant relative to the pure error and there is 61.88% chance that a ''Lack of Fit F-value'' could occur large due to noise. Non-significant lack of fit is good, we want the model to fit.
3.6. Optimization model validation
Statistical validity of the polynomials was established on the basis of ANOVA provision in the Design Expert software. Subsequently, the feasibility and grid searches were performed to locate the composition of optimum formulations. The contour plots were constructed using the output files generated by
the Design Expert® software. After developing the polynomial equations for the responses Y1, Y2 and Y3 with the independent variables X1 and X2, the formulation was optimized. Optimization was performed to find out the level of independent variables (X1 and X2) that would yield a maximum value of FF10. The R-squared values were found to be 0.968, 0.995 and 0.970 for zero order, Higuchi and Peppas, respectively.
3.7. Stability studies
The stability studies were carried out as per ICH Q1A (R2) guidelines for the optimized formulation. The formulations were stored in aluminum foil at 40 ± 2 C/75 ± 5% RH for a duration of three months and evaluated for any change in the appearance, weight variation, drug content and surface pH. Physical and chemical stability is mentioned in Table 5. The stability studies indicate no physical change in appearance and weight variation of fast dissolving films (FDF), indicating that the optimized formulation FF10 was physically stable at the accelerated conditions. The optimal storage condition of the formulation was assessed by analyzing the drug content after the time intervals of 15, 30, 60 and 90 days, drug content determined was found to be 99.72 and 98.63, at room temperature, respectively after storage for 90 days. The shelf life of the formulation was found to be 552 days using Sigma Plot 10.0 and the graph is shown below in Fig. 6 (see Fig. 8).
4. Conclusion
The main objective of the present study was to formulate and evaluate fast dissolving films (FDF) of GH. GH, an anti-emetic drug has been selected which has half-life of 5-6 h, the drug undergoes first pass metabolism. Hence in the present work, an attempt has been made to provide fast dissolving drug delivery using water soluble polymers with GH as the model drug. The films were prepared using solvent casting method using HPMC as polymer and propylene glycol as plasticizer. HPMC 15 cps was selected as polymer on the basis of their matrix forming properties and inertness, while sodium saccharin is used as a sweetening agent as it is good for diabetic patients, mint is used as a flavoring agent and to analyze the usefulness of DOE in
the development and optimization of a fast dissolving film of a model drug employing Box-Behnken statistical design.
Acknowledgement
The authors wish to thank the Management of PDM Religious and Educational Association (PDMREA) and also grateful to PDM College of Pharmacy, Sarai Aurangabad, Bahadurgarh (Hry.), India for financial support and providing the facilities to carry out the research work.
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