Int J App Pharm, Vol 11, Issue 4, 2019, 251-257Original Article


OPTIMIZATION OF AQUEOUS-BASED FILM COATING PROCESS PARAMETERS CONTAINING GLUCOSAMINE SULFATE POTASSIUM CHLORIDE

NISHANT OZA*, AKRUTI KHODAKIYA, SWATI SAGAR

C. U. Shah College of Pharmacy and Research, Wadhwan City 363030, Gujarat, India
Email: ozanishant@gmail.com

Received: 07 Jan 2019, Revised and Accepted: 10 May 2019

ABSTRACT

Objective: The aim of the present work was to prepare film-coated tablet of glucosamine sulfate potassium chloride and study the effect of coating process parameters which implicate more significant effects on an aqueous-based film coating process of tablets.

Methods: The different batches of uncoated tablets were prepared by wet granulation method. Aqueous film coating was carried out by using opadry®II white 85F18422. A 32 full factorial design was employed to study the effect of spray rate (X1) and inlet air temperature (X2) on coating uniformity, coating process efficiency and % loss on drying. The surface characteristics of the aqueous-based film-coated tablet were studied using a SEM. Check point batch was prepared to validate the evolved model.

Results: Preliminary trials indicated that individual process parameters affected the quality of coated tablets. Hence, studied the combined effect of these factors on the coating process required and 32 full factorial design was applied. In this study, it was seen that the spray rate and inlet air temperature had a major effect on tablet coating process. It was observed from factorial batch that maximum drug release was found in batch F5.

Conclusion: The results of full factorial design indicate both parameters spray rate (X1) and inlet air temperature (X2) have a significant effect on coating process and batch F5 is stable for 3 mo at the accelerated condition.

Keywords: Glucosamine sulfate potassium chloride, 32 full factorial design, Aqueous-based film, Spray rate, Inlet air temperature

© 2019 The Authors. Published by Innovare Academic Sciences Pvt Ltd. This is an open-access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
DOI: http://dx.doi.org/10.22159/ijap.2019v11i4.31905

INTRODUCTION

Glucosamine sulfate potassium chloride (GS-K) is a naturally occurring chemical found in the human body. It resides in human cartilage connective tissue that serves as a joint cushion in the knees, hips and joints [1, 2]. It is used in the treatment of osteoarthritis. GS-K is highly hygroscopic and degrades rapidly when exposed to moisture or air. So it’s creating problems in shelf-life and bioavailability [3, 4].

Oral route of drug administration is the most appealing route for drug delivery. Among the oral dosage form tablet are most preferred dosage forms because of its ease to manufacturing, convenience in administration and accurate dosing. Film coating and sugar coating of the tablets is an additional step in the manufacturing process which increases the cost of products [5, 6]. Film coating is carried out by using organic solvent or aqueous coating. Aqueous coating of oral solid dosage forms has rapidly replaced solvent-based coating for safety, environmental and economic reasons. In, aqueous coating processing parameters like spray rate, inlet air temperature, pan speed, atomizing air pressure are important issues [7, 8].

GS-K of orally administered drugs exhibit moisture sensitive characteristics that create stability problem in the aqueous coating. The slower rate of evaporation gives rise to the possibility of water penetrating; this could result in either physical degradation of the drug. So, the present work was carried out by optimizing various processing parameters and improves the stability and shelf-life of the product.

MATERIALS AND METHODS

Materials and reagents

Glucosamine sulfate potassium chloride was received as a generous gift from Jenburkt Pharmaceuticals Ltd. Sihor, Gujarat, India. Opadry II 85F18422 white was obtained from Colorcon, Goa, India. Microcrystalline cellulose (PH 101) and Microcrystalline cellulose (PH 102) were purchased from SAVA Fine Chemical, Mumbai, Maharashtra, India. All other materials and chemicals used were of either pharmaceutical or analytical grade.

Drug excipients compatibility study

The physicochemical compatibilities of drug and excipients were tested by differential scanning calorimetric (DSC) analysis. DSC thermograms of the drug and drug-excipients physical mixtures (1:1 wt/wt) were derived from a DSC with a thermal analysis performed by using an automatic thermal analyzer system (DSC 60, Shimadzu, Japan). The analysis was performed at a rate of 10 °C/min from 50 °C to 250 °C under a nitrogen flow of 20 ml/min [9, 10].

Development of glucosamine sulfate potassium chloride core tablet

The tablets were formulated by wet granulation technique and the whole process like dispensing; sifting, milling and compression were done under the controlled temperature and humidity. All the ingredients were individually screened through sieve no. 60, except glidants and lubricant. Povidone K30 and methylparaben were dissolved in isopropyl alcohol (IPA) which was used as a binder. Dibasic calcium phosphate and microcrystalline cellulose (Avicel PH 101) was used as diluents. Granulation was carried out in two-liter capacity rapid mixing granulator (RMG) and drying was carried out in fluid bed dryer (FBD) until LOD was dropped below 2 %. Compression was carried out using 16 station “D” types tooling rotary compression machine. Composition of core formulation described in table 1 [12, 13].

Preliminary screening of coating parameters

GS-K core tablet were coated by using 10% suspension of opadry® II 85F18422 white in water. Core tablets were loaded into pre-warmed coating pan. Then spray of the coating dispersion was started along with the regulation of various coating parameters like atomizing air pressure (1.8 Bar), pan speed (9-11 rpm), spray rate and inlet air temperature as described in table 3. Spraying process was continued until about 3% weight gain was achieved on the core tablets. Then the coated tablets were dried for 15 min at about 50 °C of inlet air temperature [14, 15].

Evaluation parameters of glucosamine sulfate potassium chloride core tablet

Thickness, Hardness, Weight variation, Drug content uniformity, % Friability and Disintegration test of the formulations were measured as described by Yadav K et. al, Khar RK et. al, Madgulkar AR et. al, and Lakade SH et. al, respectively [16-19].

Table 1: Formulation of glucosamine sulfate potassium chloride core tablet

Batch No. T1 T2 T3 T4 T5
Ingredients Quantity (mg/tablet)
Glucosamine sulfate potassium chloride 750 750 750 750 750
Microcrystalline cellulose (Avicel PH 101) 187.5 177.5 172.5 162.5 152.5
Dibasic calcium phosphate (Anhydrous) 100 100 100 100 100
Methyl paraben 0.5 0.5 0.5 0.5 0.5
Povidone K30 20 30 35 35 35
Isopropyl alcohol Q. S. Q. S. Q. S. Q. S. Q. S.
Sodium starch glycolate 10 10 10 20 30
Microcrystalline cellulose (Avicel PH 102) 25 25 25 25 25
Magnesium stearate 7 7 7 7 7
TOTAL 1100 1100 1100 1100 1100

Evaluation of coating parameters

Coating uniformity

The Coating uniformity was measured as the variation in weight gain of coated tablets. The reported standard deviation (SD) was calculated as:

Where, wtai and wtbi are the weights of tablet i after and before coating, respectively, n is the number of tablets measured and x is the average weight gain of the n measured tablets from coating [20, 21].

% Coating process efficiency

The % Coating process efficiency (% CPE) will be measured as the actual percent weight gain relative to the theoretical percent. Coating process efficiency was determined by the following equation:

Where, wgt is the theoretical percent weight gain and wga is the actual percent weight gain, before and after coating, respectively [22, 23].

% Loss on drying

The % loss on drying (% LOD) is the moisture content of the coated tablets expressed as percent weight. The tablets were weighed, dried at 60 °C for 24 h and there weighed. %LOD was determined by the following equation:

Optimized batch surface roughness was checked by Scanning Electronic Microscopy [24, 25].

In vitro drug release study

Drug release studies were carried out by using paddle type dissolution test apparatus (50 rpm, 37±0.5 °C) for 45 minute in purified water (900 ml). At the end of the time period, 10 ml of the samples were withdrawal and analyzed for drug content by using HPLC method at 195 nm [26, 27]

Optimization of aqueous coating process parameters by using 32 full factorial design

Two variables, spray rate and inlet air temperature were found critical. So, they were optimized using different trials, while other parameters were kept constant on the basis of previous coating study. On the basis of preliminary results, the coating spray rate (X1) and the inlet air temperature (X2) were chosen as independent variables in 32 full factorial design, while coating uniformity (CU), coating process efficiency (CPE), % loss on drying (%LOD) was selected as dependent variables. Multiple linear regression analysis, ANOVA and graphical representation of the influence of factor by 3D plots were performed using of sigma plot software 11.0. The experimental runs and measured responses of 32 full factorial design batches of Aqueous Containing of GS-K tablets were depleted in table 4 [28-30].

Stability study of optimized batch

Optimized batch was packed in blister pack and was placed for stability study at 40˚C/75% RH for 3 mo. Samples were evaluated after 3-month time for in vitro drug release study. The dissolution profile of product was compared using similarity factor, f2, which was calculated by following formula.

Where, log is logarithm to the base 10, n is the number of time points, ∑ is summation over all time points, Rt is the mean dissolution value of the reference profile at time t and Tt is the mean dissolution value of the test profile at the same time point. The USFDA draft guidance document contains more information on similarity factor (f2). The value of similarity factor (f2) between 50 and 100 suggests that the two dissolution profiles are similar [31, 32].

RESULTS AND DISCUSSION

Drug excipients compatibility study

The DSC thermograph of the GS-K (fig. 1), mixture (fig. 2) Co-relatated spectrum of drug and mixture (fig. 3) were obtained. The thermograph of pure GS-K showed a melting endothermic peak at 208.94 °C. The thermograph of excipients showed a melting endothermic peak at 209.25 °C. The DSC thermograms of the mixer showed sharp distinct endothermic peaks for Glucosamine sulfate potassium chloride and the excipients. This indicates that the drug did not interact with excipients [33].

Evaluation of glucosamine sulfate potassium chloride core tablet

Trial batch of GS-K core tablet showed angle of repose range from 23.51-27.58, carr’s index range from 6.89-18.75 and hausner’s ratio range from 1.07-1.19. All the tablets passed the weight variation test and it was found within the pharmacopoeia limits. Hardness of the tablets was found to be between 2.56-6.5 kg/cm2. The thickness and friability of all the formulation was found to be in the range of 5.2 to 5.7 mm and 0.35 to 1.2, respectively. Disintegration time of all the formulation was found to be between 3.4 to 4.1 min was shown in table 2. The core tablets of Batch T1 and T2 failed in hardness and friability test. Batch T3 showed good hardness but disintegration time was high. Disintegration time was decreased in Batch T4 and T5 respectively. So, batch T5 was selected as a final core formulation [16-19].

Fig. 1: DSC spectrum of glucosamine sulfate potassium chloride

Fig. 2: DSC spectrum of the mixture

Fig. 3: DSC Co-related spectrum of drug and mixture

Table 2: Evaluation of glucosamine sulfate potassium chloride core tablet

Batch T1 T2 T3 T4 T5
Avg. Weight (mg) 1100±5 1099±2 1099±4 1101±4 1100±3
Hardness (kg/cm2) 2.56±0.2 4.90±0.3 6.2±0.4 6.4±0.4 6.5±0.6
Thickness (mm) 5.2±0.1 5.5±0.1 5.4±0.2 5.6±0.1 5.7±0.1
Friability (%) 1.2-±0.3 0.85-±0.1 0.48±0.4 0.42±0.3 0.35±0.2
Disintegration Time (min) 4.1±0.4 6.3±0.2 7.7±0.4 5.2±0.5 3.4±0.4

All values are expressed as mean±SD, n=3

Preliminary screening of coating parameters

Two variables, spray rate and inlet Air Temperature were found critical. So, they were optimized by using different trials, while other parameters were kept constant on the basis of previous coating study. Spray rate was adjusted 5, 7, 9, 11 and 13 gm/min and the batches were designated as B1 to B5 respectively. As shown in table 2 inlet air temperature was fixed at 50 °C. At a higher spray rate, sticking and picking were observed as compared to the lower spraying rates. At lower spray, rate coating efficiency was lower because the particles are dried between the paths before reaching to the tablet bed which also result in the rough surface. Batch B3 gave good surface and highest coating process efficiency thus; it was decided to use 9 gm/min spray rate in further investigations. For batch B6 to B10 inlet air temperature was adjusted 30 °C, 40 °C, 50 °C, 60 °C and 70 °C respectively. As shown in table 3, Spray rate was fixed at 9 gm/min. At 30 °C sticking and picking were observed because the water was not evaporated from tablet surface and tablets stuck to each other. Nozzle block was observed when inlet air temperature was kept 70 °C, maybe because at the higher temperature, sprayed particles got dried very quickly. Hence, further trials were carried out using combination of inlet air temperature (45 °C to 55 °C) and spray rate (7 to 9 gm/min) in order to understand their effect and to optimize coating parameters [34, 35].

Table 3: Preliminary screening of coating parameters

Batch Inlet air temperature ( °C) Spray rate (gm/min) Coating uniformity (mg) % Coating process fficiency Surface roughness %LOD Conclusion
B1 50 5 2.1±0.03 72.58±1.2 4 0.42±0.2 +
B2 50 7 2.3±0.02 80.45±0.4 5 0.53±0.3 +
B3 50 9 1.8±0.04 86.62±0.8 6 0.76±0.5 +
B4 50 11 2.2±0.07 79.85±1.7 5 0.87±0.3 +
B5 50 13 - - - - Sticking and picking
B6 30 9 - - - - Sticking and picking
B7 40 9 2.4±0.06 79.63±1.4 6 0.96±0.5 +
B8 50 9 1.9±0.05 87.56±1.6 7 0.70±0.3 +
B9 60 9 2.1±0.05 81.35±0.6 5 0.56±0.2 +
B10 70 9 2.5±0.04 68.75±1.4 5 0.45±0.6 Nozzle block

All values are expressed as mean±SD, n=3

Table 4: Runs and measured responses of 32factorial design of aqueous coating process parameters

Batch

code

 Spray rate (X1) Inlet air temperature (X2) Coating uniformity (Y1) Coating process efficiency (Y2) % Loss on drying (Y3)
F1 -1 -1 1.92 80.42 0.51
F2 0 -1 2.03 76.26 0.59
F3 1 -1 2.19 72.86 0.53
F4 -1 0 1.98 88.29 0.61
F5 0 0 2.12 86.45 0.7
F6 1 0 2.27 80.56 0.68
F7 -1 1 2.11 78.58 0.62
F8 0 1 2.28 73.65 0.71
F9 1 1 2.36 70.35 0.69
Factors and the levels in the design
Independent variables Low (-1) Medium (0) High (1)
Spray rate (X1) 7 9 11
Inlet air temperature (X2) 45 50 55

32 Full factorial design model evaluation

A statistical model incorporating interactive and polynomial terms was used to evaluate the responses:

Y=b0+b1X1+b2X2+b11X12+b22X22+b12X1X2

Where, Y is the dependent variable, bo is the arithmetic mean response of the 9 runs and any bi is the estimated coefficients for the related factor Xi. The main effects (X1 and X2) represent the average result of changing one factor at a time from its low to high value. The polynomial terms (X12 and X22) are included to investigate nonlinearity. The interaction term “X1X2” shows how the response changes when the two factors change simultaneously. Evaluation data for core tablets and coated tablets were presented in table 5 and 6 respectively. The fitted equations relating the responses that is, coating uniformity (CU), coating process efficiency (CPE) and % loss on drying (%LOD) to the transformed factor are shown in table 4. The polynomial equations can be used to draw conclusions after considering the magnitude of coefficient and the mathematical sign it carries (i.e. positive or negative). The results of ANOVA suggested that F values calculated for CU, CPE and % LOD are 50.980, 55.714 and 84.632 respectively (table 7). Tabulated F value was found to be 9.013 at α = 0.05. Calculated F values are greater than tabulated for all dependent variables, therefore, factors selected have shown significant effects. From the results of multiple regression analysis, it was found that all factors had a statistically significant influence on all dependent variables as p<0.05 (table 8) [36, 37].

Full and reduced model for coating uniformity

The coating uniformity for coated tablets was found to be varied from 1.92 to 2.36 and it showed a good correlation coefficient of 0.988. From the graph (fig. 4) and the regression coefficient values of factors, it was concluded that the spray rate gives more effect on coating uniformity as compared to inlet air temperature. For coating uniformity, the significance levels of the coefficients b11, b22, and b12 were found to be P = 0.727, 0.804 and 0.268 respectively, so they were omitted from the full model to generate a reduced model. The P value for variable X1 and X2 were found 0.001 and 0.002 respectively (P<0.05), which indicate that X1 and X2 both variable shown a significant effect on coating uniformity [36, 37]. Hence they were retained in the reduced model. The reduced model for coating uniformity:

CU = 2.127+0.135 X1+0.102 X2

Table 5: Evaluation of core tablets for factorial batches

Powder

blend

 Hardness (kg/cm2)

Thickness

(mm)

 Friability (%) Avg. wt. (mg) Disintegration time (min)
F1 6.1±0.13 5.7±0.13 0.450±0.2 1100±0.9 3.2±0.5
F2 6.5±0.21 5.6±0.21 0.448±0.4 1101±0.7 3.3±0.8
F3 6.0±0.09 6.0±0.09 0.506±0.7 1098±1.1 3.3±0.4
F4 5.8±.32 5.8±.32 0.656±0.2 1100±1.2 3.4±0.6
F5 6.4±0.24 5.9±0.24 0.394±0.6 1100±0.9 3.4±0.4
F6 5.9±0.17 5.7±0.17 0.436±0.3 1102±1.1 3.5±0.6
F7 5.9±0.27 5.9±0.27 0.353±0.4 1102±0.9 3.5±0.8
F8 6.4±0.34 5.8±0.34 0.459±0.1 1100±0.8 3.2±0.6
F9 5.8±0.14 6.1±0.14 0.567±0.5 1101±1.2 3.4±0.4

All values are expressed as mean±SD, n=3

Table 6: Evaluation of coated tablets for factorial batches

Factorial

batches

Hardness

(kg/cm2)

Thickness

(mm)

Avg. wt.

(mg)

Disintegration

time (min)

 % Drug release at 45 min
F1 6.7±0.13 6.3±0.10 1123±0.9 3.5±0.6 81.47±1.6
F2 7.1±0.21 6.1±0.13 1121±1.1 3.7±0.8 79.12±1.5
F3 6.9±0.09 6.4±0.12 1124±1.2 3.8±0.5 75.83±0.7
F4 6.8±0.32 6.1±0.06 1120±0.8 3.2±0.8 82.68±1.5
F5 7.0±0.24 6.5±0.02 1123±0.6 3.5±0.5 86.24±0.7
F6 6.9±0.17 6.1±0.14 1118±0.9 3.6±1.0 81.24±1.3
F7 7.3±0.27 5.8±0.06 1124±1.2 3.4±0.6 79.57±1.2
F8 7.1±0.34 6.2±0.04 1123±0.8 3.6±0.7 76.82±1.1
F9 6.9±0.14 6.4±0.07 1122±0.9 3.8±0.4 73.2±1.8

All values are expressed as mean±SD, n=3

Full and reduced model for coating process efficiency

Coating process efficiency of coated tablets was found to be varied from 70.35 to 88.29 and it’s showed good correlation co-efficient of 0.989. For coating process efficiency, as seen from fig. 5, the 3D plot reveled that a corresponding increase spray rate, there were decreases in coating process efficiency and corresponding increase in inlet air temperature there also decreased the coating process efficiency. From regression, it is observed that only X1 and X22 were significant model terms which affect the coating process efficiency. Interaction and nonlinearity was not observed. The P value for variable X1 and X22 were 0.003 and 0.001 (P<0.05), which indicate that both variable has a significant effect on the coating process efficiency [36, 37]. Hence they were retained in the reduced model. The reduced model for Coating process efficiency:

CPE= 85.284-3.920 X1-9.747 X22

Table 7: Analysis of variance (ANOVA) of dependent variable

Source of variation DF SS MS F value P Value
CU Dependent variable
Regression 5 0.173 0.034
Residual 3 0.002 0.0006 50.980 0.004
Total 8 0.175 0.021
CPE Dependent variable
Regression 5 290.532 58.106
Residual 3 3.129 1.043 55.714 0.004
Total 8 293.661 36.708
% LOD Dependent variable
Regression 5 0.043 0.008
Residual 3 0.0003 0.0001 84.632 0.002
Total 8 0.043 0.005

Table 8: Summary of multiple regression analysis for coating process parameters

Responses Model Coefficient of regression parameters
b0 b1 b2 b11 b22 b12 R2
coating uniformity Full 2.127 0.135 0.102 -0.005 0.005 -0.025 0.988
Reduced 2.127 0.135 0.102 - - - -
coating process efficiency Full 85.284 -3.920 –1.160 –0.167 0.277 -9.747 0.989
Reduced 85.284 -3.920 - - - -9.747 -
%Loss on drying Full 0.703 0.0267 0.065 0.012 0.060 0.055 0.993
Reduced 0.703 0.0267 0.065 - 0.060 0.055 -

Full and reduced model for % loss on drying

The % LOD of coated tablets was found to be varied from 0.51 to 0.71 and showed good correlation co-efficient of 0.993. For % LOD, as seen from fig. 6, the 3D plot reveled that a corresponding increase in spray rate, there was increase in % Loss on drying and the corresponding increase in inlet air temperature there was also increase in the % loss on drying. From regression, it is observed that X1, X2, X12 and X22 were significant model terms which affect the % loss on drying. Interaction and nonlinearity were not observed. The P value for variable X1, X2, X12and X22 were 0.008, 0.001, 0.004 and 0.005 respectively [36, 37]. Hence they were retained in the reduced model. The reduced model for %Loss on drying

% LOD = 0.703+0.0267 X1+0.0650 X2–0.0600 X12–0.0550 X22.

Validation of the design

To validate the evolved mathematical models (reduced models) one checkpoint was selected as shown in table 9. Good correlation was found between observed and predicted values as shown in table 10. Hence, it was concluded that the evolved models may be used for theoretical prediction of responses within the factor space [36, 37].

Selection of optimized batch in factorial design study

Drug release of all batches was carried out for 45 min. It was observed that (as shown in table no 5) maximum drug release was found in batch F5 and other all batches gave less drug release as compared to batch F5. Hence, batch F5 was selected as an optimized batch. The optimized formulation was subjected to SEM and accelerated stability study.

Stability study of optimized batch

Short term accelerated stability study showed that there was no significant change in the formulation after 3 mo and the evaluation result was found within the limit. The results are shown in table 11. Batch F5 was kept for the stability study. The in vitro release profile at initial and after 3 mo was compared using similarity factor, f2, value which was found to be 88.50. There is no significant difference in similarity factor, f2, value which indicated that the prepared formulation was stable [38].

Table 9: Formulation of checkpoint batches

Batch code Variable level
Coded value Actual value
X1 X2 X1(mg) X2 (ml)
CP1 -0.5 -0.5 8 47.5

Table 10: Evaluation of checkpoint batches and comparison with predicted value

Parameter Actual value Predicted value
coating uniformity 2.1 2.008
coating process efficiency 79.23 78.450
% loss on drying 0.721 0.714

Fig. 4: Effect of spray rate (X1) inlet air temperature (X2) on coating uniformity

Fig. 5: Effect of spray rate (X1) inlet air temperature (X2) on coating process efficiency.

Fig. 6: Effect of spray rate (X1) inlet air temperature (X2) on % loss on drying.

Fig. 7: SEM of coated tablet surface

Table 11: Comparative study of optimized batch with market product

S. No. Parameters Initial (Batch F5) After 3 mo (Batch F5)
1 Hardness (kg/cm2) 7.0±0.21 6.8±0.14
2 Average weight (mg) 1123±1.3 1121±0.7
3 Disintegration time (min) 3.5±0.3 3.4±0.4
4 Assay 99.50±0.4 %w/w 98.90±0.5 %w/w
5 In vitro drug release (After 45 min.) 86.24±1.5 83.70±1.5

All values are expressed as mean±SD, n=3

CONCLUSION

In this study, an aqueous-based film coating process of glucosamine sulfate potassium chloride tablets was performed in a side-vented perforated pan coating apparatus (auto coater). The preliminary results revealed that spray rate, and inlet air temperature had a major effect on tablet coating performances. The spray rate of coating solution 9 gm/min and inlet air temperature 50 °C considered as an optimum aqueous film coating of special shaped tablets in auto coater coating machine. An optimized batch was found stable. It showed that aqueous based film coating process is compatible with the drug. Moreover, the process of film coating in developed formulation is eco-friendly, non-hazardous and cost-effective.

AUTHORS CONTRIBUTIONS

All the author have contributed equally

CONFLICT OF INTERESTS

Declared none

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