CHAPTER.5 FORMULATION AND EVALUATION OF FAST DISSOLVING TABLET of DOMPERIDONE

Transcription

1 CHAPTER.5 FORMULATION AND EVALUATION OF FAST DISSOLVING TABLET of DOMPERIDONE 5.1 Development, characterization and solubility study of solid dispersion of domperidone Phase solubility study studies In order to determine the most suitable carrier for domperidone, phase solubility with different carrier like PVPK30, PEG 4000 and PEG 6000 were carried out by a reported method by higuchi and Connors [159]. An excess amount of domperidone was added to the aqueous solutions of each carrier in distilled water containing increasing concentrations of the individual carrier (i.e., 0.05%, 0.1%, 0.15%, 0.2%, 0.25%, 0.3 % w/v). The flasks were sealed and shaken at 37 0 C for 48 h in a thermostatically controlled water bath and the samples were filtered through a 0.45 µm cellulose nitrate membrane filter. The filtrate was suitably diluted and analyzed spectrophotometrically at 284 nm. Data analysis The values of apparent stability constant, K S, between each drug carrier combination were computed from following formula:- K S = slope/ intercept (1- slope) Slope and intercept were obtained from phase solubility curve. The values of Gibbs free energy of transfer, G tr 0, of domperidone from plain distilled water to aqueous solutions of the carrier were calculated according to following relationship:- G tr 0 = RT. Log S O /S S where, S O and S S are the molar solubility of domperidone in 1% aqueous solution of the carrier and in the plain distilled water, respectively Preparation of physical mixture and solid dispersion of domperidone Melt fusion method was used to prepare solid dispersions of domperidone with PEG In melted PEG 6000 domperidone was added. It was mixed well and flash cooled on ice bath and then stored overnight in desiccator. The prepared solid dispersion was then grounded by using a mortar and pestle, sieved through a mesh 40 and stored over a fused K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 100

2 calcium chloride in a desiccator for further use. Different ratio of drug: polymer physical mixture and solid dispersion are shown in Table 5.1 and Table 5.2 respectively. Table 5.1 Different ratio of physical mixtures S. No. Formulation Number Drug : Carrier Ratio 1 DP1 1:1 2 DP2 1:3 3 DP3 1:5 4 DP4 1:7 5 DP5 1:9 *DP= drug polymer physical mixture Table 5.2 Different ratio of solid dispersion S. No. Formulation Number Drug : Carrier Ratio 1 DSD1 1:1 2 DSD2 1:3 3 DSD3 1:5 4 DSD4 1:7 5 DSD5 1:9 * DSD = drug polymer solid dispersion Characterization of solid dispersion of domperidone FT-IR spectroscopy FTIR spectra were obtained on Shimadzu FTIR Model 8400-S spectrometer. The spectra was recorded as a dispersion of the sample in Potassium Bromide in IR disk (2 mg sample in 200 mg KBr) with the scanning range of 400 to 4000 cm-1 and the resolution was 1 cm -1. K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 101

3 Thermal analysis DSC analysis was performed using Netzsch DSC 204, Tokyo, Japan. The samples were heated in a sealed aluminium pans at a rate of 100 C per min in a 30 to 3000 C temperature under nitrogen flow of 40 ml/min. Scanning electron microscopy (SEM): The morphology of domperidone- PEG 6000 system was investigated by means of ESEM TMP with EDAX (Philips, Holland). Samples were previously sputter-coated with a gold layer in order to make them conductive. Pictures were taken at an excitation voltage of 30 kv and a magnification of 1500x. Drug content Drug content was determined by weighing randomly selected tablets, pulverizing to a fine powder. The weight equivalent to 10 mg domperidone was weighed and dissolved in 5 ml of methanol in volumetric flask using magnetic stirrer, the volume was adjusted to 100 ml with phosphate buffer (ph 6.8) and the solution was filtered. An aliquot of 1.0 ml of solution were diluted to 10 ml phosphate buffer (ph 6.8) in separate volumetric flask. The content in was determined spectrophotometrically at 284 nm. In vitro drug release Dissolution studies of domperidone from all physical mixtures and solid dispersions were performed according to the method described in USP XXIV, using USP II apparatus (paddle method). The dissolution test was performed using 900 ml phosphate buffer ph 6.8, at 370 ± 0.50C and 50 rpm. Aliquots (5 ml) was removed from the dissolution medium at specific time intervals and was replenished immediately with same volume of fresh medium, the amount of released domperidone was determined by UV analysis at 284 nm. Mathematical modelling The drug release data obtained were fitted to various kinetic models viz. Zero order, First order, Higuchi, Hixon Crowell to know the mechanism of drug release from these formulations. K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 102

4 5.2 Development of fast dissolving tablet of domperidone using different solid dispersions Preparation of tablets The direct compression method was used for the tablet preparation. All the raw materials were passed through a screen (40 mesh) prior to mixing. Powdered solid dispersions, containing amount equivalent to 10 mg of domperidone, was mixed with the other ingredients and compressed on a 10 station mini press tablet machine (CPMD Chamunda pharma machinery pvt. Ltd. Ahmedabad India) equipped with 9 mm concave punch. Composition of fast dissolving tablets of domperidone is given in Table 5.3. Ingredients (mg) Table 5.3 Composition of fast dissolving tablets Batch F1 F2 F3 F4 F5 SD (1:1) F6 SD (1:5) Domperidone F7 SD (1:9) SD Crosscarmellose sodium Starch Micro crystalline cellulose Lactose Na-Saccharin Mag.Stearate Tablet weight=250 mg K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 103

5 5.3 Optimization of fast dissolving tablet containing domperidone solid dispersion using various super disintegrants Preparation of tablets Tablets were prepared by direct compression method as per the formula (preliminary trials) shown in Table 5.4 on a 10 station mini press tablet machine (CPMD Chamunda pharma machinery pvt. Ltd. Ahmedabad India) equipped with 9 mm concave punch. Table 5.4 Typical formula of fast dissolving tablets S. No. Ingredients Quantity (%) 1 SD (1:5) 24 2 Sodium starch glycolate Cross carmellose sodium Cross povidone MCC Mannitol 10 7 Lactose q. s. 8 Mag. Stearate Saccharine sodium 0.6 Tablet weight=250 mg Optimization of Formulation Optimization technique based on response surface methodology was utilized. Response surface methodology can be defined as a statistical method that uses quantitative data from appropriate experiments to determine and simultaneously solve multivariate equations. It is generally used to determine the optimum combination of factors that yield a desired response and describes the response near the optimum. This methodology was used in the present study to optimize the variables affecting the formulation. K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 104

6 Statistical Design A randomized 3 level full factorial design using two numeric and one categorical factor was adopted to systematically study the formulation of. A total of 30 experimental run with 3 centre points were performed at all possible combination. The independent variable, were selected on the basis of trials taken during preliminary batches. The disintegration time and hardness were selected as dependent variable. Analysis of Response Response were analysed by Analysis of variance (ANOVA), to identify the insignificant factors, which were then removed from the full model to generate the reduced model. Variables in 3 level full factorial design are shown Table 5.5. Matrix design for different experimental run is shown in Table 5.6. Table 5.5 Variables in 3 Level full factorial design Independent variables-factor Low (-1) Levels (%) Middle (0) X 1 = Microcrystalline cellulose (MCC) X 2 = Disintegrating concentration X 3 = Disintegrating agent* SSG CCS CP Dependent variable- Response Y 1 = Disintegration time (seconds) Y 2 = Hardness (kg/cm 2 ) *SSG= Sodium starch glycolate, CCS= Cross carmellose sodium, CP= Cross povidone High (+1) K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 105

7 Table 5.6 Layout for full factorial design using two numeric and one catagoric factor Run X1: MCC (%) X 2 : Disintegrating Concentration (%) X 3 :Disintegrating agent D1 0 0 CP D2 0-1 SSG D3 1-1 CP D4-1 0 CP D5 0 1 CP D6-1 1 CP D7 0 0 SSG D CCS D9 1 0 CP D CCS D SSG D CCS D SSG D CCS D CCS D SSG D CP D CCS D CCS D CP D CCS D CCS K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 106

8 D CP D SSG D SSG D SSG D CP D CCS D SSG D SSG Validation of statistical model Levels of factors were selected at different points and responses predicted by the statistical models were calculated. Tablets were prepared using these levels and responses were measured practically. The predicted responses were compared against observed responses and closeness between them was checked. Response surface plots Response surface plots were generated for each response to study the effect of both factors on each response. Different constraints were applied (Table 5.7) and on the basis of confirmation report (Two-sided, Confidence = 95%, n = 1) as shown in Table 5.8, tablets were prepared. Name Table 5.7 Constraints Goal Lower limit (mg) Upper limit (mg) X 1 MCC target-> In range X 2 Disintegrating agent Concentration In range 2 6 X 3 Disintegrating agent Equal to CCS SSG CP DT Hardness K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 107

9 Table 5.8 Confirmation Report (Two-sided, Confidence = 95%, n = 1) Factor Name Level Low Level High Level Std. Dev. Coding X 1 MCC Actual X 2 X 3 Disintegrating Concentartion Disintegrating agent Actual CCS SSG CP N/A Actual Preparation of optimized batch (DFDT1) Optimized batch was prepared by direct compression method as per the formula shown in Table 5.9 on a 10 station mini press tablet machine (CPMD Chamunda pharma machinery pvt. Ltd. Ahmedabad India) equipped with 9 mm concave punch. Table 5.9 Composition of optimized batch Ingredients Quantity (%) Quantity (mg) SD Ac-Di-Sol 6 15 MCC Mannitol Lactose q. s. q.s. Mag.stearate Saccharine Na K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 108

10 5.4 Design and optimization of fast dissolving tablet containing domperidone solid dispersion using effervescent technique Preparation of tablets Tablets were prepared as per the formula given in Table All the raw materials were passed through a 40 mesh screen prior to mixing. Powdered 1:5 solid dispersion, containing amount equivalent to 10 mg of domperidone, was mixed with the other excipients. Sodium bicarbonate and anhydrous citric acid were preheated at a temperature of 80 0 C to remove absorbed/ residual moister and were thoroughly mixed in a mortar to get a uniform powder and then mixed with other ingredients. The blend thus obtained was directly compressed on a 10 station mini press tablet machine (CPMD 3-10, Chamunda Pharma Machinery Pvt. Ltd., Ahmedabad, India.) equipped with 9 mm concave punch. Table 5.10 Typical formula for fast dissolving tablets S. No. Ingredients Quantity (mg) 1 SD 60 2 Sodium bicarbonate Citric acid Ac-Di-Sol Mannitol q. s. 6 Saccharine sodium Mint flavor Mag. Stearate 3.75 Tablet weight=250 mg Optimization of formulation A randomized central composite design was implemented for the optimization of the fast dissolving tablets. Centre points were repeated three times to estimate the experimental error. Further a stepwise multivariate linear regression was performed to evaluate the response. Different variables used in central composite design are shown in Table Matrix design for different experimental run is shown in Table K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 109

11 Analysis of response Response were analysed by Analysis of variance (ANOVA), to identify the insignificant factors, which were then removed from the full model to generate the reduced model. Independent variables- Factor Table 5.11 Variables in central composite design Low (-1) Levels (mg) Middle (0) X 1 = Sodium bicarbonate X 2 = Citric acid X 3 = Ac-Di-Sol Dependent variable- Response Y 1 = Disintegration time (seconds) High (+1) Table 5.12 Layout for central composite design Run X 1 :Sodium bi Carbonate(mg) X 2 :Citric acid(mg) X 3 :Ac-Di-Sol.(mg) E E E E E E E E E E E K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 110

12 E E E E E E E E E Validation of statistical model Levels of factors were selected at different points and responses predicted by the statistical models were calculated. Tablets were prepared using these levels and responses were measured practically. The predicted responses were compared against observed responses and closeness between them was checked. Response surface plots Response surface plots were generated for each response to study the effect of both factors on each response. Different constraints were applied (Table 5.13) and on the basis of confirmation report (Two-sided, Confidence = 95%, n = 1) as shown in Table 5.14, tablets were prepared. Table 5.13 Constraints Name Goal Lower Limit (mg) Upper Limit (mg) X 1 :sodium bicarbonate is in range -1 1 X 2 :citric acid is in range -1 1 X 3 :Ac-Di-Sol is in range -1 1 DT is target = K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 111

13 Table 5.14 Confirmation Report (Two-sided, Confidence = 95%, n = 1) Factor Name Level Low Level High Level Std. Dev. Coding X 1 Sodium bicarbonate Actual X 2 Citric acid Actual X 3 Ac-Di-Sol Actual Preparation of optimized batch (DFDT2) Optimized batch was prepared as method discussed earlier. The formula for optimized batch (DFDT2) shown in Table Table 5.15 Composition of optimized batch Ingredients Value (mg) SD 60 Sodium bicarbonate 35.4 Citric acid Ac-Di-Sol 11.4 Mannitol Saccharine Na 0.6 Mint flavor 0.6 Magnesium stearate 3.75 Tablet weight=250 mg 5.5 Evaluation of fast dissolving tablets of domperidone Pre-compression characterization The quality of tablet was generally dictated by the quality of physicochemical properties of blends. There were many formulations and process variables involved in mixing steps all these can affect the characteristic of blend produced. The characterization parameters for evaluating the flow property of mixed blends includes bulk density, tapped density, Hausner s ratio, compressibility index and angle of repose. K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 112

14 Bulk density Apparent bulk density (ρ b ) was determined by pouring the blend in to a graduated cylinder. The bulk volume (V b ) and weight of powder (M) was determined. [ ] The bulk density was calculated using the formula- Tapped density The measuring cylinder containing a known amount of tablet blend was tapped 100 times using density apparatus. The constant minimum volume (V t ) occupied in the cylinder after tapping and the weight (M) of the blend was measured [ ]. The tapped density (ρ t ) was calculated using formula:- Compressibility index Compressibility is the simplest way for the measurement of powder flow property. It is an indication of ease with which a material can be induced to flow [ ]. It is expressed as compressibility index (I), which can be calculated as follows:- Where, ρ t = Tapped density; ρ b = bulk density The limits for compressibility index are shown in Table Table 5.16 Compressibility index as an indication of powder flow properties Compressibility Index (%) Type of flow >12 Excellent Good Fair to passable Poor K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 113

15 33-38 Very poor >40 Extremely poor Hausner s ratio Hausner s ratio (HR) is an indirect index of ease of powder flow. It was calculated by the following formula Where, ρ t = Tapped density; ρ b = bulk density Lower Hausner s ratio (<1.25) indicates better flow properties than higher ones. [160] Angle of repose Angle of repose was determined using the funnel method. The blend was poured through a funnel that can be raised vertically until a specified cone height (h) was obtained. Radius was measured and angle of repose was determined using the formula [ ]. Therefore, ( ) Where, θ is angle of repose; h is the height of cone; r is radius of cone. Table 5.17 Angle of repose as an indication of powder flow properties Angle of repose(θ) Type of flow <25 Excellent Good Passable >40 Very poor K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 114

16 5.5.2 Post compression characterization After compression, the prepared tablets were evaluated for organoleptic characteristics like color, taste, odor, diameter, thickness and physical characteristics like hardness, friability, disintegration time, wetting time. General appearance The general appearance of a tablet, its visual identification and over all elegance is essential for consumer acceptance. This include tablet s size, shape, odor, color, taste, surface texture etc. [167] Tablet thickness Tablet thickness is an important characteristic in reproducing appearance and also in counting by suing filling equipment. Some filling equipment utilizes the uniform thickness of the tablets as a counting mechanism. Thickness of tablets was recorded using micrometer (Mityato, Japan). Weight variation The weight variation test would be satisfactory method of determining the drug content uniformity. As per USP [168], twenty tablets were taken and weighted individually. Average weight was calculated and compared the individual weight to average weight. The weight variation limits for tablet as per USP is given in Table Table 5.18 Weight variation limit for tablets as per USP Average weight of tablet (mg) Maximum % difference allowed 130 or less More than Hardness Hardness of the tablet is defined as the force applied across the diameter of the tablet in order to break the tablet. The resistance of the tablet to chipping, abrasion or breakage under condition of storage transformation and handling before usage depends on K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 115

17 its hardness. Hardness of the tablet of each formulation was determined using Pfizer Hardness taster [167,169]. Friability Friability of tablets was determined using Roche friabilator apparatus. This device subjects the tablet to the combined effect of abrasion and shock in a chamber, revolving at 25 rpm and dropping the tablet at the height of 6 inch in each revolution. Preweighed sample of tablets was placed in the friabilator and were subjected to 100 revolutions. Tablets were dedusted using a soft muslin cloth and reweighed. The friability (F %) was determined by the formula Where, W 0 is the initial weight of the tablets before the test and W is the weight of the tablet after test [ ]. Disintegration time The disintegration time was measured using a modified disintegration method. According to this method, a petri dish of 10-cm diameter was filled with 10 ml of Phosphate buffer ph 6.8, the tablet was carefully placed at the center of the petri dish, and the time necessary for the complete disintegration of the tablet into fine particles was noted as disintegration time [171]. Wetting time A piece of tissue paper folded twice was kept in a culture dish (internal diameter 5.5 cm) Containing ~6 ml of purified water. A tablet having a small amount of amaranth powder on the upper surface was placed on the tissue paper. The time required to develop a red colour on the upper surface of the tablet was recorded as the wetting time [172]. Dissolution studies Dissolution studies of domperidone from tablets were performed according to the method described in USP XXIV, using USP II apparatus (paddle method). The dissolution test was performed using 900 ml phosphate buffer ph 6.8 at 37 0 ± C and 50 rpm. Aliquots (5 ml) was removed from the dissolution medium at specific time intervals and was K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 116

18 replenished immediately with same volume of fresh medium, the amount of released domperidone was determined by UV analysis at 284 nm. It was found that PEG 6000 did not interfere with the assay at this wave length. 5.6 In Vivo study for optimized domperidone fast dissolving tablet Pharmacokinetic study Sample preparation Blood samples were collected from rats into a heparinized tube and centrifuged for 3 min at 12000xg to separate plasma. One ml of each sample added to 100 ml of 0.01 M NaOH. The mixture was shaken with a mechanical shaker for 10 min and centrifuged at 1620Xg for 5 min. Then 10 ml of this solution added to 100 ml chloroform and mixture was shaken for 10 min then centrifuged. A 4 ml of volume of lower organic phase was transferred to another tube and evaporated to dryness under gentle nitrogen stream. The dried residue was dissolved in 100 µl of mobile phase, and 10 µl of the aliquot were injected in to HPLC column [173]. Study design Six male Wistar rats weighing g were used in this study. Animals were housed in a room maintained on a 12 hrs light/dark cycle at 23±2 C with free access to food and water.all the animal experiments were performed according to the guideline of local animal ethical committee (Ref no- SDPC/AFC/2012/113).The Test (DFDT 2) formulation and Reference (DOMEL MT) were administered to the rats by gastric intubation method after calculating the animal dose (10 mg/kg) [174]. Blood samples were withdrawn after 0, 0.25, 0.50, 0.75, 1, 2, 3 and 4 hours and were immediately centrifuged to obtain plasma. Plasma samples were stored at C until analysis. Pharmacokinetics and statistical analysis The following pharmacokinetics parameters were calculated using noncompartmental methods: area under the plasma concentration time curve from zero to the last measurable Domperidone concentration sample time (AUC 0-t ), area under the plasma concentration time from zero extrapolated to infinite time AUC 0-, maximum plasmatic drug concentration (C max ) and time to reach C max (t max ), terminal rate constant (K el ) and terminal half-life (t 1/2 ). C max and t max were obtained directly from the concentration time curve. AUC 0 t was calculated using the linear trapezoidal method. K el was calculated by K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 117

19 applying a log-linear regression analysis to at least the last three quantifiable concentrations of ondansetron; t 1/2 was calculated as 0.693/Kel [175]. For the purpose of bioequivalence analysis AUC 0 t, AUC 0 and C max were considered as primary variables. Bioequivalence between the products was determined by calculating 90% confidence intervals (90% CI) for the ratio of C max, AUC 0 t and AUC 0 values for the test and reference products, using logarithmic transformed data. Analysis of variance (ANOVA) was used to assess product, group and period effects. The products were considered bioequivalent if the 90%CI for AUC 0 t, AUC 0 andc max fell within80 125% Pharmacodynamic study Method Study is known as Conditioned placed Aversion in which behavior of animal was studied after administration of drug [176]. In this study, Swiss albino mice (40-70 g), Maintained in a well-ventilated room at a temperature of 25 ± 1 C with 12/12 h light/dark cycle in polypropylene cages. The animals were acclimatized to laboratory conditions for 10 days prior to initiation of experiments. All the animal experiments were performed according to the guideline of local animal ethical committee (Ref no- BU/BT/185/11-12). Blockade of lithium chloride induced conditioned place aversion, as described by Frisch et al. was used as a test for the assessment of antiemetic activity. In brief, the apparatus consisted of the two compartments A and B (25 X 22 X 22 cm) differing in color (white/black) and floor texture (smooth/ roughened) and separated by a small grey alley (25 X 10 X 22 cm). From the centre of alley the mice could enter either of the two compartments through guillotine doors. The apparatus was set up in a sound protected chamber with dim overhead lighting (40 W). The behaviour of the animal was observed throughout the experiment by an observer unaware of the drug treatments. After each trial the apparatus was cleaned with 0.1% acetic acid General procedure Behavioral testing was always conducted during the same period of the day. The procedure was performed in three consecutive phases. Pre-conditioning phase This phase consisted of three consecutive days. Animals were subjected individually to the apparatus in untreated condition with the guillotine doors open for 15 min per trial. K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 118

20 After the third baseline trial the preference for one of the two compartments was calculated by taking the mean time spent in the compartments over the three baseline trials. Conditioning phase The mice were assigned randomly to the treatment groups (vehicle, lithium sulphate (160 mg/kg), Domel MT (10 mg/kg), Domstal (10 mg/kg) and DFDT2 (10 mg/kg) with lithium sulphate, in a volume of 5 ml/kg body weight). The mice were treated with the conditioning drug on one day and the vehicle on the alternate day. Each mice was exposed to an equal number of drug pairings with both the compartments. The treatment lasted for 8 days (four pairings). Post-conditioning phase On the day following the conditioning phase, drugs were not administered to animals and they were placed in the apparatus with the doors open and the time spent in the preferred compartment was recorded during the 15 min test session. Experimental set up for the study is shown in Table Table 5.19 Experimental set up for domperidone Group Group I Group II Group III Group IV Group V Treatment Treated with vehicle Treated with Lithium sulphate Treated with Comp I (DOMEL MT, MorepenLaboratoreis Ltd.) + Lithium sulphate Treated with Comp II (DOMSTAL, Torrent) + Lithium sulphate Treated with Comp III (DFDT 2) + Lithium sulphate 5.7 Stability study The stability studies of optimized formulations were performed according to ICH and WHO guidelines [177]. The drug product which is provided by a manufactures to his consumers must be both efficacious and safe. This can only be ensured by instituting a program to study the stability of a product during its various phases of development and to use proper storage conditions and comply with the expiry period under those conditions. These studies will quickly identify the need, if any, to stabilize the active substance or the formulation, and to save any waste of time and effort on an unmarkable formulation. For K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 119

21 globalization of manufacturing operations, the final product should be sufficiently robust for marketing worldwide under a variety of climate conditions, including tropical, subtropical and temperate Selection of fast dissolving tablets The results of tablet characterizations of different batches were compared and optimized batch DFDT1 and DFDT2 were selected for stability studies. The optimized fast dissolving tablets were packed in wide mouth air tight glass container. Stability studies were carried out according to ICH and WHO guidelines as shown in Table (5.20). Table 5.20 Conditions as Per ICH Protocol Time (Month) Conditions C ± 2 0 C and 60 ± 5% RH 40 0 C ± 2 0 C and 75 ± 5% RH Physical and chemical stability The tablets are withdrawn after end of period and analysed for physical characterization and drug content. The drug content data obtained was fitted in to first order equation to determine the kinetics of degradation. Accelerated stability data were plotted according to Arrhenius equation to determine the shelf life at 25 0 C. [ ] K= Ae -Ea/RT T 10% = 0.104/ K Where, K is specific reaction constant; A is Arrhenius factor; T is absolute temperature; R is Gas constant; Ea is energy of activation Comparison of dissolution profile In recent years, FDA has placed more emphasis on a dissolution profile comparison in the area of post-approval changes biowaivers. A dissolution profile comparison between pre-change and post-change product or with different strength, helps assure similarity in product performance and signal bioequivalence. K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 120

22 Among several methods investigated for dissolution profile comparison, f2 is the simplest one. f2= 50* log,*1 + (1/n) t=1 n (R t - T t )2] -0.5 * 100} Where R t and T t are the cumulative percentage drug dissolved at each of the selected n time points of the reference (before storage) and test (after storage) product respectively. When the two profile are identical, f2 = 100. An average difference of 10% at all measured time point s results in f2 value 50. FDA sets a standard of f2 value in between 50 to 100; indicate similarity between two dissolution profiles. [ ] K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 121

23 Concentration of Domperidone (mg/ml) Bhatt S.O. RESULT and DISCUSSION 5.8 Phase solubility study Phase solubility study of domperidone is shown in Figure 5.1. Solubility of domperidone in distilled water was observed to be 5.35 µg per ml indicating it is practically insoluble. Various parameters computed from phase solubility studies shows a linear increase in drug solubility with increase carrier levels, with r 2 value ranging between to Analogous results have been reported with several other drugs using the watersoluble carriers [ ] and/or co-solvent effect of the carrier [189]. Hydrophilic carriers are known to interact with drug molecules mainly by electrostatic forces and occasionally by other types of forces like hydrogen bonds [190]. Taking the slope of various linear curves as enlisted in Table 5.21, as indicative of the relative solubilizing efficiency, the PEG 6000 had the maximum solubilizing power followed by PEG 6000> PEG 4000> PVP K PVP K-30 PEG 4000 PEG Concentratiion of carrier (%w/v) Figure 5.1 Phase solubility study of domperidone K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 122

24 Table 5.21 Solubility parameter of domperidone at 37 0 C Carrier (%) Slope K s R 2 PEG PEG PVP K The value of apparent stability constant, Ks, were computed for 1:1 drug carrier interaction since all the curves obtained in the present study were of A L Type with the resultant slope less than unity [191]. Highest value of Ks, obtained for PEG 6000 binary solution revealed strong binding affinity between domperidone and solubilizer. At 0.3 % w/v concentration PEG 6000 showed 15.5 fold augmentations in the solubility of pure drug, attributed to the micellar solubilization of drug [192]. Besides PEG 6000 the other water soluble polymeric carrier also enhanced domperidone solubility although moderately. The values of Gibbs free energy of transfer G tr 0 are shown in Table 5.22, and it was found that the values of G tr 0, were negative at all levels of carriers, unequivocally demonstrating spontaneity of drug solubilization process. The values show a decline trend with increase in the carrier concentration too constructing that the process of domperidone transfer from distilled water to carrier solution is more favorable at higher carrier levels [184+. The values of G tr 0 were the lowest for the PEG 6000 indicating that the process of transfer of domperidone from distilled water to its aqueous solution was most favorable amongst all carriers studied, Hence PEG 6000 was selected for further studies. Concentration of carriers (% w/v) Table 5.22 Values of Gibbs free energy of transfer G tr 0 G tr 0 (joules/mole) for various water soluble carriers at 37 0 C PVP K 30 PEG 4000 PEG K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 123

25 5.9 Characterization of solid dispersion of domperidone The solid dispersions were evaluated for Fourier transform infrared (FTIR), differential scanning calorimetry (DSC), scanning electron microscopy (SEM) and percent drug content. Fourier transform infrared (FTIR) FTIR spectra of domperidone, PEG 6000, and all the solid dispersions are shown in Figure ( ).Interpretation of FT-IR spectra of various solid dispersions is shown in Table Figure 5.2 FTIR spectra of domperidone Figure 5.3 FTIR spectra of PEG 6000 K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 124

26 Figure 5.4 FTIR spectra of DSD 1 Figure 5.5 FTIR spectra of DSD 2 K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 125

27 Figure 5.6 FTIR spectra of DSD 3 Figure 5.7 FTIR spectra of DSD 4 K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 126

28 Figure 5.8 FTIR spectra of DSD 5 Table 5.23 Interpretation of FT-IR spectra of various solid dispersions Functional group Band width NH stretching cm -1 C=O stretching cm -1 C-H stretching cm -1 N-H deformation cm -1 The results depicted that there was no significant change in the spectrum of solid dispersion, as incorporation of domperidone into the PEG 6000 did not modify the position of its functional groups. The absence of shifts in the wavenumbers of the FTIR peaks of the solid dispersion indicates the lack of significant interaction between the drug and the carrier in the solid dispersion [ ]. K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 127

29 Differential scanning calorimetry (DSC) DSC Thermogram of domperidone, PEG 6000, and all the solid dispersions are shown in Figure ( ) Figure 5.9 DSC of domperidone Figure 5.10 DSC of PEG 6000 K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 128

30 Figure 5.11 DSC of DSD 1 Figure 5.12 DSC of DSD 2 K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 129

31 Figure 5.13 DSC of DSD 3 Figure 5.14 DSC of DSD 4 K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 130

32 Figure 5.15 DSC of DSD 5 Thermal profile of pure product exhibited a single endothermic effect corresponding to the melting of domperidone (T fus , H fus J/g) or PEG 6000 (T fus , H fus J/g) respectively. The DSC curve of solid dispersion shown progressive broadening and lowering of drug melting temperature, and concomitant reduction of its enthalpy with increasing in carrier content in mixture until total disappearance of drug melting endotherm. This finding could be considered indicative of drug amorphization as a consequence of interaction between components [195]. It also shows the progressive drug dissolution in the melted carrier before achieving its melting carrier, as was previously observed for other the drug-peg combination [ ]. Scanning electron microscopy (SEM) Scanning electron microscopy (SEM) of domperidone, PEG 6000, and DSD (1:5) are shown in Figure ( ). It was found that PEG 6000 existed in a crystalline mixture of smooth-surfaced particle with smaller particle, while domperidone existed in small irregular particle. On the contrary, SD (1:5) consisted of more spherical particles of rather irregular surface. In the case of SD (1:5), at the high polymer ratio, particles presented a surface morphology similar to that of pure PEG In these monograph, it is impossible to distinguish the presence of K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 131

33 domperidone crystals among the PEG particles. The novel arrangement between domperidone and PEG particles might be responsible for the enhance drug dissolution rate found for SD system, in comparison with the pure domperidone. Figure 5.16 SEM of domperidone Figure 5.17 SEM of PEG 6000 K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 132

34 Drug content Figure 5.18 SEM of DSD 1:5 Table 5.24 shows the drug content of different ratio of physical mixtures and solid dispersions of drug with PEG Table 5.24 Drug content of physical mixtures and solid dispersions Formulation Number Drug content (%) DP ±0.765 DP ±1.148 DP ±1.148 DP ±0.880 DP ±1.130 DSD ±1.092 DSD ±1.503 DSD ±1.881 DSD ±1.253 DSD ±1.043 DP1-DP5= Physical mixtures, DSD1-DSD5= Solid dispersions K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 133

35 In vitro drug release study of domperidone from physical mixtures and SD s Table ( ) and Figure ( ) showed the dissolution profile of pure domperidone, Physical mixture, and SDs. Drug release from pure domperidone is only 2 % after 30 min whereas the dissolution rate of domperidone from all physical mixture and SDs was significantly higher than that of domperidone alone. As the proportion of PEG increased, domperidone dissolution rate increased. This result coincides with the findings of Dario Leonardi et.al.,[198]. The hydrophilic properties of PEG 6000 probably led to greater wetting and increased surface for dissolution by reducing interfacial tension between the hydrophobic drug and the dissolution medium [199]. Table 5.25 Cumulative mean % drug release of domperidone from physical mixtures Time (min) Cumulative mean% drug release ± Standard Deviation Pure Drug DP1 DP2 DP3 DP4 DP ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±0.59 Data are expressed as mean S.D. (n = 3) K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 134

36 Table 5.26 Cumulative mean % drug release of domperidone from solid dispersions Time (min) Cumulative mean% drug release ± Standard Deviation Pure Drug DSD1 DSD2 DSD3 DSD4 DSD ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±2.33 Data are expressed as mean S.D. (n = 3) Figure 5.19 Cumulative mean % drug release of domperidone from physical mixtures K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 135

37 Cumulative % drug release Bhatt S.O PURE DRUG DSD1 DSD2 DSD Time (min) DSD4 DSD5 Figure 5.20 Cumulative mean % drug release of domperidone from solid dispersions Mathematical modeling The drug release data obtained were fitted to various kinetic models (Table 5.27) viz. zero order, first order, higuchi, hixoncrowell to know the mechanism of drug release from these formulations. In this experiment, the in vitro release profile of drug from all these formulations could be best expressed by korsemeyer-peppas, as the plot shows highest linearity (R 2 = to 0.991). The values of diffusional exponent n obtained from the slopes fitted korsemeyer-peppas model, All the solid dispersions tended to exhibit fickian diffusional characteristics, as the corresponding values of n were lower than the standard value for declaring fickian release behavior, i.e., 0.45 [200]. Likewise, the formulations were observed to yield statistically valid correlations with the Higuchi and first-order models too. The results unequivocally point out the prevalence of diffusional mechanistic phenomena, in consonance with the results obtained while fitting korsemeyer Peppas model The goodness of fit for various models investigated for binary system ranked in the order of Korsemeyer-peppas >First order > Higuchi >Hixon Crowell cube root law > Zero order. Likewise, the formulations were observed to yield statistically valid correlations with the Higuchi and first-order models too. The results unequivocally point out the prevalence of diffusional mechanistic phenomena, in consonance with the results obtained while fitting K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 136

38 Korsemeyer Peppas model [201]. The Hixson-Crowell cube root model, in general, described the drug release data modestly with r 2 values ranging between and Table 5.27 Statistical parameters of various formulations obtained after fitting the drug release data to various release kinetic models Mathematical models for drug release kinetics Formulation Korsemeyer-peppas First-order Higuchi Hixson-Crowell Zero-order Slope r 2 Slope r 2 Slope r 2 Slope r 2 Slope r 2 Domperidone DSD DSD DSD DSD DSD K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 137

39 5.10 Evaluation of fast dissolving tablet of domperidone, prepared using different solid dispersions Physical properties of tablet blend Formulation Code A physical property of tablet blend is shown in Table Bulk density (mg/ml) Table 5.28 Physical properties of tablet blend Tapped Density (mg/ml) Hausner s Ratio Carr s Index (%) Angle of Repose( θ) F1 0.51± ± ± ± ±0.29 F2 0.53± ± ± ± ±0.28 F3 0.53± ± ± ± ±0.54 F4 0.48± ± ± ± ±1.13 F5 0.57± ± ± ± ±0.21 F6 0.53± ± ± ± ±0.29 F7 0.54± ± ± ± ±1.01 Data are expressed as mean S.D. (n = 3) To determine the suitability of the powder blend for tablet compression, all formulation were characterized for various flow properties. The tablet blend for all the batches showed Good flow ability (angle of repose <30 0 ) Characterization of tablets Formulation F1- F7 characterized for different parameters as shown in Table (5.29) Incorporation of crosscarmellose sodium (4-6%) as superdisitegrating agent decreased the disintegration time (17-12 seconds).on the contrary, increase in the crosscarmellose-na concentration (8 %) increased the disintegration time of tablets without producing any appreciable change in drug release. When crosscarmellose-na is added to a tablet formulation at higher concentration, absorption of water may cause an increase in viscosity of liquid with in tablet and may delay further penetration of water. As water absorption is an important step in disintegration process, increase in crosscarmellose-na concentration showed a delayed tendency in tablet disintegration [202]. K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 138

40 Table 5.29 Characterization of fast dissolving tablets Parameters Thickness Diameter Weight Friability Hardness Drug Content Disintegration time Wetting time Formulations (mm) (mm) (mg) (%) (kg/cm 2 ) (%) (Seconds) (Seconds) F1 3.9± ± ± ± ± ± ± ±1.61 F2 3.8± ± ± ± ± ± ± ±1.01 F3 3.9± ± ± ± ± ± ±1.35 6±1.21 F4 3.8± ± ± ± ± ± ± ±1.34 F5 3.8± ± ± ± ± ± ± ±1.70 F6 3.7± ± ± ± ± ± ± ±1.43 F7 3.7± ± ± ± ± ± ± ±1.14 Data are expressed as mean S.D. (n = 3) K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 139

41 Cumulative % Drug Release Bhatt S.O. When the ratio of PEG 6000 and drug in solid dispersion was increased, disintegration time of tablets also increased although release of drug was found to be faster. Drug release from tablets prepared with solid dispersion of drug and PEG 6000 in ratio of (1:5) and (1:9) were found to be 79% and 81% respectively in 5 minutes. It was found that the disintegration time was increased with increasing in the concentration of PEG 6000 and for the formulation F6 and F7 it was found to be 58 and 108 seconds respectively. Formulations F4-F7 gives rapid drug release than compare to marketed formulation of domperidone (Normetic, Lupin Pharmaceutical Ltd.). Cumulative % drug release from various formulations is shown in Figure ( ). When compare amongst various formulations, tablets containing drug: PEG 6000 (1:5) and 6 % crosscarmellose sodium were found to be optimum in relation to rapid disintegration and dissolution Time (min) F1 F2 F3 F4 Figure 5.21 Cumulative % drug release of formulation F1- F4 K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 140

42 Cumulative % Drug Release Bhatt S.O F F F Marketed tablet Time (min.) Figure 5.22 Cumulative % drug release of formulation F5- F7 and Market product The disintegration time of optimized batch obtained in the above method was 58 second, further to reduce the disintegration and to achieve high mechanical strength; there is a need of optimization techniques. Thus, to systematic study of the joint influence of superdisintegrants and diluents on disintegration time and hardness, a statistical design was employed. When compare amongst various formulations, tablets containing drug: PEG 6000 (1:5) and 6 % crosscarmellose sodium were found to be optimum in relation to rapid disintegration and dissolution Evaluation of fast dissolving tablets prepared using various super disintegrants Characterization of tablets The preliminary trial batches were prepared using the formula (Table 5.4) by direct compression technique in order to study the effect of superdisintegrants and diluents on the disintegration time and hardness. Results of the different batches showed a wide variation in the disintegration time (42-82 seconds) and hardness ( kg/cm 2 ). On the basis of these results, dependent and independent variable were selected and to K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 141

43 systematically study different factorial batches (D1 to D30) were prepared and evaluated (Table 5.30). Table 5.30 Characterization of fast dissolving tablets Parameters Thickness Weight Friability Drug Content Wetting time Formulations (mm) (mg) (%) (%) (Seconds) D1 3.9± ± ± ± ±1.11 D2 3.8± ± ± ± ±1.08 D3 3.9± ± ± ± ±1.20 D4 3.9± ± ± ± ±1.30 D5 3.8± ± ± ± ±1.75 D6 3.7± ± ± ± ±1.03 D7 3.8± ± ± ± ±1.04 D8 3.9± ± ± ± ±1.24 D9 3.9± ± ± ± ±1.24 D10 3.9± ± ± ± ±1.14 D11 3.7± ± ± ± ±1.24 D12 3.8± ± ± ± ±1.14 D13 3.7± ± ± ± ±1.21 D14 3.8± ± ± ± ±1.01 D15 3.9± ± ± ± ±1.14 D16 3.8± ± ± ± ±1.29 D17 3.9± ± ± ± ±1.44 D18 3.8± ± ± ± ±1.29 D19 3.9± ± ± ± ±1.14 K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 142

44 D20 3.9± ± ± ± ±1.24 D21 3.8± ± ± ± ±1.19 D22 3.9± ± ± ± ±1.17 D23 3.9± ± ± ± ±1.29 D24 3.8± ± ± ± ±1.14 D25 3.7± ± ± ± ±1.08 D26 3.9± ± ± ± ±1.74 D27 3.8± ± ± ± ±1.24 D28 3.9± ± ± ± ±1.00 D29 3.8± ± ± ± ±1.21 D30 3.9± ± ± ± ±1.14 Data are expressed as mean S.D. (n = 3) Friability of all the formulation was below 1% indicates that the tablets had good mechanical resistance. Uniformity of drug content was observed in all the formulations. The weight variation results revealed that average % deviation of 20 tablets of each formulation was less than ±7.5%, which provide good uniformity in all formulations. Statistical design A statistical model incorporating interactive and polynomial terms was used to evaluate the responses, Y= b 0 + b 1 X 1 + b 2 X 2 + b 3 X 3 + b 12 X 1 X 2 + b 13 X 1 X 3 + b 23 X 2 X 3 + b 2 1 X b 2 2 X b 2 3 X b 123 X 1 X 2 X 3 Y is the measured response associated with each factor-level combination, b 0 is the arithmetic mean response of the total 30 runs; X 1, X 2, andx 3 are the factors studied, b i is the regression coefficient for factor X i computed from the observed response Y. The main effects (X 1, X 2, andx 3 ) represent the average result of changing one factor at a time from its low to high value. The interaction terms (X 1 X 2 ) show how the response changes when two factors are simultaneously changed. The polynomial terms (X 2 2 1, X 2 and X 2 3 ) are included to investigate nonlinearity. Two conclusions could be drawn from the equation: (1) a K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 143

45 coefficient with a negative sign increases the response when the factor level is decreased from a higher level to a lower level, and (2) the factor with a higher absolute value of the coefficient and a lower significance value P has a major effect on the response variables. The dependent variables, disintegration time and hardness showed a wide variation (Table 5.31). The data clearly indicates that the response variables are strongly dependent on the selected independent variables. Table 5.31 Results for each experimental run in full factorial design Batch Disintegration time (Y1) Responses Hardness (Y2) D1 54± ±0.91 D2 64± ±0.82 D3 60± ±1.09 D4 57± ±1.15 D5 47± ±0.98 D6 51± ±0.29 D7 60± ±1.14 D8 59± ±1.27 D9 52± ±0.79 D10 57± ±1.18 D11 64± ±0.59 D12 45± ±0.38 D13 60± ±1.19 D14 51± ±0.78 D15 51± ±1.44 D16 57± ±0.54 K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 144

46 D17 61± ±1.17 D18 51± ±0.89 D19 43± ±0.88 D20 51± ±0.39 D21 53± ±0.73 D22 52± ±1.34 D23 54± ±1.44 D24 60± ±1.71 D25 55± ±1.81 D26 60± ±1.40 D27 57± ±0.82 D28 47± ±0.98 D29 71± ±1.11 D30 64± ±1.01 Data are expressed as mean S.D. (n = 3) The fitted equations (full and reduced) relating the responses to the transformed factor are shown in Table Analysis of variance (ANOVA) was carried out to identify the insignificant factors, which were then removed from the full model to generate the reduced model. Table 5.32 and 5.33 represents the result of ANOVA for disintegration time and hardness, respectively. Table 5.32 ANOVA for response surface reduced cubic model for disintegration time Response model Sum of square Df Mean square F value P value R 2 Adeq. precision DT < K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 145

47 Response model Table 5.33 ANOVA for response surface reduced 2FI model for hardness Sum of square Df Mean square F value P value R 2 Adeq. Precision Hardness < The Model F-value of and implies the models are significant. There is only a 0.01% chance that a "Model F-Value" this large could occur due to noise. Values of Prob> F less than indicate odel term are significant. Values greater than indicate the model term are not significant. "Adeq Precision" measures the signal to noise ratio. A ratio greater than 4 is desirable, ratio of and indicates an adequate signal. This model can be used to navigate the design space. K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 146

48 Table 5.34 Summary of result of regression analysis Disintegration Time Model* b 0 b 1 b 2 b 3 (1) b 3 (2) b 12 b 13 (1) b 13 (2) b 23 (1) b 23 (2) b 1 2 b 123 (1) b 123 (2) FM RM Hardness Model* b 0 b 1 b 2 b 3 (1) b 3 (2) b 12 b 13 (1) b 13 (2) b 23 (1) b 23 (2) b 1 2 b 123 (1) b 123 (1) RM *FM indicate full model; RM indicate reduced model K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 147

49 The coefficients of X 1 and X 2, that is, b 1 and b 2 respetively, bear a negative sign, thus on increasing the concentration of either disintegrating agent and MCC, a decrease in disintegration time is observed.factor X 3 also bear negative sign, when disintegrating agent was seleceted from sodium starch glycolate to crosspovidone with mid point cross carmellose sodium (Ac-Di-Sol) disintegration time decreases. Ac-Di-Sol is a superdisintegrants of excellent disintegration ability. It swells to a larger extent when in contact with water. The fibrous nature of Ac-Di-Sol allows intra-particulate as well as extraparticulate wicking of water even at low concentration. The superdisintegrant action of sodium starch glycolate (SSG) is governed by its extensive swelling, which increases with increased proportions of SSG. Contact of water with SSG leads to the formation of viscous plugs [203]. Due to the increase in viscosity, further uptake of water may be retarded; and the tablets break into large floccules instead of disintegrating into smaller particles. Similarly for hardness b 1 and b 3 posseses positive sign, thus on increasing the concentration of MCC, hardness increases. Validation of statistical model To validate the statistical model checkpoint batches, CP1 and CP2 were prepared according to the formula. From the over lay plot, response surface and the calculations from the statistical equation obtained by regression, the results revealed the close match of the experimental results. Thus, we can conclude that the statistical model is mathematically valid. Table 5.35 represents the comparison of predicted values and experimental values for check point batches. Table 5.35 Comparison of predicted values and experimental values for check point batches. Formulation code CP1 X 1 =+1 X 2 =+0.5 X 3 =CCS CP2 X 1 =+0.5 X 2 =+1 X 3 =CCS Predicted Values (DT) Experimental Values (DT) Residual Predicted Values (Hardness) Experimental Values (Hardness) Residual ± K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 148

50 B : D i s i n t e r g r a n t c o n c. Bhatt S.O. The best batch was selected after considering the requirements of an FDT. To full fill these requirements, disintegration time was targeted to 44 s and hardness to 4.2 kg/cm 2. The batches dissolution rates were also considered and batches with higher dissolution rates were given priority. Different constraints were applied; responses were predicted at 95% CI and they are found in range, which showed the robustness of the statistical model (Table 5.37). Further, solution with desirability near 1 was selected as shown in Table (5.36).Overlay plot (Figure 5.23) and Response surface plot for disintegration time and hardness are shown in Figure ( ). Table 5.36 Predicted response at 95% confidence (n=1) Response Prediction Std Dev SE (n=1) 95% PI low 95% PI high DT Hardness No. MCC (%) Disintegrating agent concentration (%) Table 5.37 Predicted desirability Disintegrating agent (%) DT (Second) Hardness (kg/cm 2 ) Desirability CCS Design-Expert Software Factor Coding: Actual Overlay Plot 1.00 Overlay Plot DT Hardness Design Points X1 = A: MCC X2 = B: Disintergrant conc. Actual Factor C: DT agent = CCS Hardness: A: MCC Figure 5.23 Overlay plot for DT K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 149

51 D T Bhatt S.O. Design-Expert Software Factor Coding: Actual DT Design points above predicted value Design points below predicted value X1 = A: MCC X2 = B: Disintergrant conc. Actual Factor C: DT agent = CCS B: Disintergrant conc A: MCC Figure 5.24 Response surface plot for disintegration time Figure 5.25 Response surface plot for hardness K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 150

52 Characterization of optimized tablet (DFDT 1) To determine the suitability of the powder blend for tablet compression, optimized FDT (DFDT 1) was characterized for various flow properties as shown in Table (5.38) Sr no. Formulation Code Table 5.38 Physical properties of optimized tablet blend Bulk density (mg/ml) Tapped Density (mg/ml) Hausner s Ratio Carr s Index (%) Angle of Repose ( θ) 1 DFDT ± ± ± ± ±0.34 Data are expressed as mean S.D. (n = 3) It was found that tablet blend showed good flow ability (angle of repose < 30 0 ). Further optimized FDT (DFDT 1) was characterized for different parameters as shown in Table Table 5.39 Characterization of optimized tablet (DFDT 1) Parameters Thickness Diameter Weight Fribility Drug Content Wetting time Formulations (mm) (mm) (mg) (%) (%) (Seconds) DFDT 1 3.9± ± ± ± ± ±1.15 Data are expressed as mean S.D. (n = 3) Friability of all the formulation was below 1% indicates that the tablets had good mechanical resistance. Good uniformity of drug content was observed in all the formulations. The weight variation results revealed that average % deviation of 20 tablets of each formulation was less than ±7.5%, which provide good uniformity in all formulations. Comparison of predicted responses and observed values for the disintegration time and hardness showed close agreement (Table 5.40), and the models were found to be valid. Thus, 3 Level full factorial design and statistical models can be successfully used to optimize the formulations. Table 5.40 Comparison of predicted responses and observed values Predicted Values (Disintegration time) Experimental Values (Disintegration time) Predicted Values (Hardness) Experimental Values (Hardness) K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 151

53 %CDR %CDR Bhatt S.O. Figure ( ) showed the in vitro drug release profile of all factorial batches and optimized batch and it was found to be more than 90% in 10 minutes than compare to 60% in 10 minutes for market product (DOMEL MT) Time (min.) DFDT1 D1 D2 D3 D4 D5 D6 D7 D8 D9 D10 Figure 5.26 % CDR (DFDT1, D1- D10) Time (min.) D11 D12 D13 D14 D15 D16 D17 D18 D19 D20 Figure 5.27 % CDR (D11-D20) K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 152

54 %CDR Bhatt S.O Time (min.) D21 D22 D23 D24 D25 D26 D27 D28 D29 D30 Figure 5.28 % CDR (D21-D30) 5.12 Evaluation of fast dissolving tablets prepared using effervescent technique Characterization of tablets The preliminary trial batches were prepared using the formula given in Table 5.10, using direct compression technique in order to study the effect of effervescent material, superdisintegrants and diluents on the disintegration time and hardness. Results of the different batches showed a wide variation in the disintegration time (31-65 seconds). Hardness of the different batches was found ( kg/cm 2 ), and it was not affected by change in concentration of effervescent material and superdisintegrants. Thus, hardness was not selected as dependent variable in the study. On the basis of these results, dependent and independent variable were selected and to systematically study different factorial batches (E1 to E20) were prepared and evaluated. Formulations E1 to E20 were characterized for different parameters as shown in Table (5.41) K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 153

55 Table 5.41 Characterization of fast dissolving tablets Parameters Thickness Weight Friability Hardness Drug Content Formulations (mm) (mg) (%) (kg/cm 2 ) (%) E1 3.8± ± ± ± ±1.01 E2 3.9± ± ± ± ±1.24 E3 3.9± ± ± ± ±1.10 E4 3.9± ± ± ± ±1.03 E5 3.9± ± ± ± ±1.02 E6 3.9± ± ± ± ±1.01 E7 3.8± ± ± ± ±1.31 E8 3.8± ± ± ± ±1.40 E9 3.9± ± ± ± ±1.38 E10 3.9± ± ± ± ±1.34 E11 3.9± ± ± ± ±1.12 E12 3.8± ± ± ± ±1.09 E13 3.8± ± ± ± ±1.14 E14 3.9± ± ± ± ±1.77 E15 3.9±0.21 E16 3.9±0.44 E17 3.9±0.48 E18 3.8±0.15 E19 3.9± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±1.09 E20 3.8± ± ± ± ±1.30 Data are expressed as mean S.D. (n = 3) K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 154

56 Friability of all the formulation was below 1% indicates that the tablets had good mechanical resistance. Uniformity of drug content was observed in all the formulations. The weight variation results revealed that average % deviation of 20 tablets of each formulation was less than ±7.5%, which provide good uniformity in all formulations. Statistical design A statistical model incorporating interactive and polynomial terms was used to evaluate the responses, Y= b 0 + b 1 X 1 + b 2 X 2 + b 3 X 3 + b 12 X 1 X 2 + b 2 1 X b 2 2 X b 2 3 X b 2 1 b 2 X 2 1 X 2 + b 2 1 b 3 X 2 1 X 3 + b 1 b X 1 X 2 Y is the measured response associated with each factor-level combination, b 0 is the arithmetic mean response of the total 20 runs; X 1, X 2, and X 3 are the factors studied, b i is the regression coefficient for factor X i computed from the observed response Y. The main effects (X 1, X 2, andx 3 ) represent the average result of changing one factor at a time from its low to high value. The interaction terms (X 1 X 2 ) show how the response changes when two factors are simultaneously changed. The polynomial terms (X 2 2 1, X 2 and X 2 3 ) are included to investigate nonlinearity. Two conclusions could be drawn from the equation: (1) a coefficient with a negative sign increases the response when the factor level is decreased from a higher level to a lower level, and (2) the factor with a higher absolute value of the coefficient and a lower significance value P has a major effect on the response variables. The dependent variable, disintegration time showed a wide variation (5.42). The data clearly indicates that the response variable is strongly dependent on the selected independent variable. The high values of the correlation coefficient for disintegration time indicate a close fit. Table 5.42 Results of each experimental run in central composite design Batch Response (disintegration time), Y1 E1 53±0.56 E2 48±0.73 E3 37±0.95 E4 58±0.48 K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 155

57 E5 41±0.39 E6 31±0.75 E7 41±0.89 E8 41±0.73 E9 44±0.47 E10 40±0.66 E11 38±0.97 E12 44±0.63 E13 41±0.96 E14 48±0.85 E15 43±0.49 E16 55±0.39 E17 46±0.40 E18 41±0.73 E19 54±0.57 E20 47±0.43 The fitted equations (full and reduced) relating the responses to the transformed factor are shown in Table Analysis of variance (ANOVA) was carried out to identify the insignificant factors, which were then removed from the full model to generate the reduced model. Table 5.43 represented the result of ANOVA. Response model Table 5.43 ANOVA for response surface reduced cubic model Sum of square Df Mean square F value P value R 2 Adeq. Precision DT < K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 156

58 The Model F-value of implies that model is significant. There is only a 0.01% chance that a "Model F-Value" this large could occur due to noise. Values of Prob> F less than indicate model term are significant. Values greater than indicate the model term are not significant. "Adeq Precision" measures the signal to noise ratio. A ratio greater than 4 is desirable, ratio of indicates an adequate signal. This model can be used to navigate the design space. Table 5.44 Summary of result of regression analysis Model* b (DT) 0 b 1 b 2 b 3 b 12 b 13 b 1 b 2 b 3 b 2 1 b 2 b b 3 b 1 b FM RM *FM indicate full model; RM indicate reduced model The coefficients of X 1,X 2 and X 3 that is b 1, b 2 and b 3 respetively, bear a negative sign. Thus, on increasing the concentration of sodium bicarbonate, citric acid and Ac-Di-Sol, a decrease in disintegration time is observed. Validation of statistical model Table 5.45 Comparison of predicted values and experimental values for check point batches Formulation code CP1 X 1 = -0.5 X 2 =+ 1 X 3 = CP2 X 3 =+ 1 X 3 = -0.5 X 3 = Predicted Values (DT) Experimental Values (DT) Residual ± ± To validate the statistical model checkpoint batches, CP1 and CP2 were prepared according to the formula. Table 5.45 represented the comparison of predicted values and experimental values for check point batches. From the over lay plot (Figure 5.29) response surface plot (Figure 5.30) and the calculations from the statistical equation obtained by regression, the results revealed the close match of the experimental results. Thus, we can conclude that the statistical model is mathematically valid. K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 157

59 B : C i t r i c a c i d Bhatt S.O. The best batch was selected after considering the requirements of an FDT. To fullfill these requirements, disintegration time targeted to 32 s. The batches dissolution rates were also considered and batches with higher dissolution rates were given priority. Different constraints were applied; responses were predicted at 95% CI and they are found in range, which showed the robustness of statistical model (Table 5.46). Further, solution with desirability 1 was selected, as shown in Table (5.47). Table 5.46 Predicted response at 95% confidence (n=1) Response Prediction Std Dev SE (n=1) 95% PI low 95% PI high DT Number Sodium bicarbonate (mg) Table 5.47 Predicted desirability Citric acid (mg) Ac-Di-Sol (mg) DT (Sec.) Desirability Design-Expert Software Factor Coding: Actual Overlay Plot DT X1 = A: Sodium bicarbonate X2 = B: Citric acid Actual Factor C: Ac-Di-Sol = Overlay Plot DT: X X A: Sodium bicarbonate Figure 5.29 Overlay plot for DT K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 158

60 Figure 5.30 Response surface plots for DT Characterization of optimized batch (DFDT2) To determine the suitability of the powder blend for tablet compression, optimized FDT (DFDT 2) was characterized for various flow properties as shown in Table (5.48). Sr no. Formulation Code Table 5.48 Physical properties of optimized tablet blend Bulk density (mg/ml) Tapped Density (mg/ml) Hausner s Ratio Carr s Index (%) Angle of Repose ( θ) 1 DFDT ± ± ± ± ±0.79 Data are expressed as mean S.D. (n = 3) It was found that tablet blend showed good flow ability (angle of repose < 30 0 ). Further optimized FDT (DFDT 2) was characterized for different parameters as shown in table (5.49). Table 5.49 Characterization of optimized tablet (DFDT 2) Parameters Thickness Diameter Weight Friability Drug Content Wetting time Formulations (mm) (mm) (mg) (%) (%) (Seconds) DFDT 2 3.9± ± ± ± ± ±1.15 Data are expressed as mean S.D. (n = 3) K.B.I.P.E.R. Kadi Sarva Vishwavidyalaya Page 159