FORMULATION, DEVELOPMENT AND EVALUATION OF NIOSOMAL DRUG DELIVERY SYSTEM FOR CLINDAMYCIN PHOSPHATE. Jivrani Shilpa D*, Patel Vijay K

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1 Impact factor: /ICV: Pharma Science Monitor 5(2), Sup-1, Apr-Jun 2014 PHARMA SCIENCE MONITOR AN INTERNATIONAL JOURNAL OF PHARMACEUTICAL SCIENCES Journal home page: FORMULATION, DEVELOPMENT AND EVALUATION OF NIOSOMAL DRUG DELIVERY SYSTEM FOR CLINDAMYCIN PHOSPHATE. Jivrani Shilpa D*, Patel Vijay K Shree Krishna Institute of Pharmacy, Shankhalpur, Bechraji, Mehsana, Gujrat, India ABSTRACT To formulate and evaluate Niosomal drug delivery system for Clindamycin phosphate to increase its effectiveness by increasing penetration through skin and reducing its side effects Sorbitan esters which are Non-ionic surfactants was the key ingredient which forms vesicles upon hydration with aquous media. Cholesterol was used to make vesicle stable and rigid. Different formulations were prepared by using different sorbitan ester and changing the ratio of surfactant and Cholesterol. A 3 2 factorial design was applied to evaluate the effect of various surfactants and surfactant:cholesterol ratio on dependent variable i.e. Entrapment efficiency and Vesicle size. Regression analysis and analysis of variance were performed for dependent variables. The results of the F-statistics were used to select the most appropriate model. Batch F21 was selected as the optimized batch which contained span 60 as non ionic surfactant and 2:1 surfactant:cholesterol ratio. It was incorporated into carbopol 934 as gelling agent and compared for invitro release profile and in-vitro skin penetration with marketed gel. In-vitro release data was fitted to various model to ascertain the kinetic of drug release. The study indicate that the formulation was increase the effectiveness of drug reduce the side effects of drug. KEYWORDS: Clindamycin phosphate, Non-ionic surfactants, Cholesterol, Entrapment efficiency, Vesicle size, Carbopol 934. INTRODUCTION Dermal (topical) delivery targets the drug to the pathological sites within the skin with the least systemic absorption. Drug localization in this case is a crucial issue in the treatment of dermatological problems such as skin cancer, psoriasis, alopecia and acne, where the origin of disease is located in the skin. several limitations have been associated with the conventional topical preparations e.g. low percutaneous penetration because of the barrier function of the stratum corneum, the outermost layer of the skin and absorption to the systemic circulation. The outer layer of skin, stratum corneum, provides a rate limiting step during percutaneous absorption of drug. many strategies have been assessed to overcome the barrier function of the stratum corneum and to improve drug transport into the skin. The carrier is one of the most important entities required for successful targeted drug delivery.1

2 Impact factor: /ICV: In the last years, the vesicular systems have been promoted as a mean of sustained or controlled release of drugs, because of their certain advantages. These vesicular systems were found to be more effective as they render controlled release of drug due to depot formation in skin and some were more effective in transdermal delivery.vesicular systems such as liposomes and niosomes are also widely used in cosmetic and skin care applications because of their ability to increase the stability of entrapped drugs, improved bioavailability of poorly absorbed ingredients and enhanced skin penetration. 2,3 Clindamycin Phosphate is a antibiotic widely used for the treatment of acne. In oral dosage forms it produces pseudomonas colitis while in topical dosage forms it has side effects like irritation, skin rash, itching etc. it s topical bioavailability is also less. So, to overcome these limitations an attempt has been made to prepare niosomes of Clindamycin Phosphate and optimize it for enhanced delivery through the skin upon the variation of surfactant cholesterol and incorporate into gelling agent carbopol 934 and compare for in vitro release and in vitro permeation with marketed conventional gel of Clindamycin Phosphate.4,5 MATERIALS AND METHODS The chemicals used were: Clindamycin phosphate was the generous gift from Montage laboratory, himmatnagar. Cholesterol and Carbopol 934 were purchased from chem dye corporation, ahmedabad, Span 60, span 20, span 40 were purchased from purvi enterprise, ahmedabad. All other chemicals used were of analytical grade. FORMULATION OF CLINDAMYCIN PHOSPHATE NIOSOMES USING THIN FILM HYDRATION TECHNIQUE : The mixture of vesicles forming ingredients like surfactant and cholesterol are dissolved in a volatile organic solvent (diethyl ether, chloroform or methanol) in a round bottom flask. The organic solvent is removed at room temperature (20 C) using rotary evaporator leaving a thin layer of solid mixture deposited on the wall of the flask. The dried surfactant film can be rehydrated with aqueous phase at 0-60 C with gentle agitation. This process forms typical multilamellar niosomes film of lipid on the wall of rotary flash evaporator. The aqueous phase containing drug was added slowly in it. 6,7

3 Impact factor: /ICV: Table 1: Representing the Composition of Formulation: Table 1. Composition of drug and excipients in factorial batches of niosomes Batch F17 F18 F19 F20 F21 F22 F23 F24 F25 Drug mg mg mg mg mg mg mg mg mg Span ml ml ml Span mg mg mg Span ml ml ml Cholesterol 20 mg 20 mg 20 mg mg mg mg mg mg mg Chloroform 7 ml 7 ml 7 ml 7 ml 7ml 7 ml 7 ml 7ml 7 ml Phosphate 10 ml 10 ml 10 ml 10 ml 10 ml 10 ml 10ml 10 ml 10 ml buffer 7.4 CHARACTERIZATION OF NIOSOMES: 6,7 Entrapment Efficiency: Free drug was separated from entrapped drug in niosomes by ultracentrifugation at 4 C for 30 minutes. Supernatant containing free drug was collected and analyzed by UV spectrophotometer. Percent drug entrapment was calculated by using following formulala. PDE = Total Amount of Drug Free Amount of Drug / Total Amount Of Drug 100 Particle Characteristics : The surface appearance and shape of niosomes was analysed by TEM study. The vesicles were dispersed in water and one drop of the diluted dispersion was placed on a 200-mesh carbon coated copper grid. The photographs were taken at 30,000X magnification and 100 KV voltages. Vesicle Size : Vesicle size can be range from 20nm to 50µm. Large niosomes with size over 1 micrometer can be measured by light microscopy and coulter counter. Niosomes in the nano size range can be measured bu Malvern particle sizer. Drug Content

4 Impact factor: /ICV: Drug content of the niosomal preparations were determined by lysis method. Adequate amount of 50% n-propanol was added to the niosomal dispersion and shaken well until all the vesicles were completely lysed. It was diluted suitably with distilled water and the absorbance was measured by UVspectrophotometer. In Vitro Release In vitro drug release study of niosomal preparation was performed by Franz diffussion cell with semipermeable membrane. The semi permeable membrane soaked in a buffer for 6-8 hours. It was clamped carefully to one end of the hollow glass tube of 17 mm (area cm²) (dialysis cell). This acted as donor compartment. 25 ml of PBS 7.4 was taken in a beaker which was used as a receptor compartment. small quantity was spread uniformly on the membrane. The donor compartment was kept in contact with the receptor compartment and the temperature was maintained at 37 ± 0.1 ºC. At predetermined time intervals, sample was withdrawn and replaced by 1 ml of PBS. The drug concentrations in the aliquot were 5.determined by UV against appropriate blank. EXPERIMENTAL DESIGN 9 A 3 2 randomized full factorial design was performed, and the effect of surfactant (A) and Surfactant: cholesterol ratio(b) were taken as independent variables, while entrapment efficiency (Y1) and vesicle size(y2) were taken as dependent variables. The factors were studied at 3 levels (-1, 0, 1 ) (Table 2). The statistical optimization procedure was performed with the help of optimization software such as Design Expert 9. The software performs response surface methodology (RSM) which includes the multiple regression analysis (MRA), ANOVA and statistical optimization. Table 2. Selection of level for 3 2 factorial design Independent factors Levels X1:Effect of verious Span 20 Span 60 Span 80 surfactant X2:Surfactant:Cholesterol 2: 0.5 2:1 2: 1.5 ratio

5 Impact factor: /ICV: Table 3. Dependent variable for 3 2 factorial design Dependent variables 1. Entrapment Efficiency (%) 2. Vesicle size (µm) Multiple Regression Analysis The use of regression analysis in 3 2 factorial designs generates different polynomial equations for different models, with interacting terms and regression coefficients, useful in evaluating the responses. Y = b0 + b1a + b2b + b12ab + b11a2 + b22b2 Where Y is the response evaluated, b0 is the arithmetic mean response of 9 runs, bi is the estimated coefficient of independent variables. The main effects (A and B) represent the average result of changing 1 factor at a time from its low to high value. The interaction term (AB) show how the response changes when 2 factors are simultaneously changed. The polynomial terms (A2and B2) were included to investigate nonlinearity. Vesicular Size Evaluation The vesicular size of the formulation optimized by statistical optimization was evaluated by Malvern zeta sizer after sonication of the optimized formulation. Transmission Electron Microscopy The surface appearance and shape of niosomes was analysed by TEM study. The vesicles were dispersed in water and one drop of the diluted dispersion was placed on a 200-mesh carbon coated copper grid. The photographs were taken at 30,000X magnification and 100 KV voltages. The optimized Niosomal gel was incorporated into carbopol 934 for patient compliance and stability purpose and than it was compared with marketed conventional gel of clindamycin phosphate for in vitro permeation and in vitro release. Comparative Study of in-vitro permeation of Optimized Proniosomal Gel with Marketed Gel : 12,13 Ex-vivo permeation studies of the optimized formulation were compared with the marketed gel for 12 h. The permeation flux obtained from the plot of cumulative drug permeated per cm2 was plotted against time. The slope of the plot gives the permeation flux.

6 Impact factor: /ICV: Comparative Study of in vitro Release of Optimized Proniosomal Gel with Marketed and Carbopol Gel In vitro release studies of the optimized formulation were compared with the marketed and carbopol gel for 24 h. The percentage cumulative amount of drug released was noted down and used for the comparison studies. RESULTS AND DISCUSSION The non-ionic surfactant selected for the study is span 60 because of high transition temperature (53 C) and the chemical structure(long alkyl chain), which is reported for the higher entrapment efficiency. Cholesterol is another common additive that acts as cementing agent to improve the stability and play a key role in the entrapment efficiency. Hence, the entrapment efficiency and vesicle size are largely dependent upon the type of non-ionic surfactant and cholesterol, and any alteration in their concentration may lead to the leakiness of the vesicles that result in the leakage of free drug before drug diffusion and fusion of vesicles. Keeping this in mind, the present study focused on investigating the effect of variation in concentration of cholesterol and effect of different surfactant on the entrapment efficiency and vesicle size. Therefore, effect of three different surfactant (span 20, span 60, span 80) and surfactant:cholesterol ratio ( 2:0.5, 2:1, 2: 1.5) were taken and 9 formulations were prepared using 3 2 factorial design evaluated for various parameter. Entrapment Efficiency Entrapment efficiency is the measure of solute retention. High entrapment efficiency means that less time and effort are needed to remove the unentrapped drug. Vesicular entrapment efficiency is an important parameter that conveys the stability of vesicles and this depends upon the type of surfactant and amount of cholesterol used. The entrapment efficiency of various formulations is tabulated in Table 4. From the data in Table 4, it is clear that entrapment efficiency depends upon both type of surfactant and cholesterol. Effect of independent variable on the entrapment efficiency is represented in the 3D surface plot.

7 Impact factor: /ICV: Tab. 4. Observed Response in 3 2 Factorial Design for Clindamycin phosphate-loaded niosomal gel: Formulation Entrapment efficiency Vesicle size (µm) Drug Content (%) (%) F ± ± ±0.31 F ± ± ±0.46 F ± ± ±0.72 F ± ± ±0.25 F ± ± ±0.64 F ± ± ±0.33 F ± ± ±0.53 F ± ± ±1.03 F ± ± ±0.43 Entrapment Efficiency: The prepared Niosomal suspension were evaluated for % drug entrapped in the vesicles and the data is reported in the table 4. From the result, batch F21 has highest entrapment efficiency which was prepared by using span 60 and surfactant: cholesterol ratio 2:1. Span 60 has highest entrapment efficiency.. As the length of alkyl chain increases entrapment efficiency increases. Span 60 and span 80 has same length of alkyl chain but span 60 has saturated alkyl chain so its entrapment efficiency is higher than span 80.The transition temperature of span 60 is also very high than span 80 and span 20. Because of this span 60 has highest entrapment efficiency. It was found that as the ratio of surfactant: cholesterol increase from 2:0.5 to 2:1 entrapment efficiency increases, but further increase in ratio of sur:cho entrapment efficiency decreses. The reason behind that is further increase in cholesterol content makes the film more rigid and increase amount of cholesterol compete with the drug.so, drug entrapment decresed. Vesicle size: Vesicle size of batch F17 to F25 is tabulated in table 4. From the data vesicle size of Batch F17 to Batch F25 were found between As the conc. of cholesterol increase vesicle size increases. All surfactant has same head group and different alkyl chain. As the length of alkyl chain increases vesicle size increases so, noisome prepared by span 60 has more vesicle size than noisome prepared by span 20.

8 Impact factor: /ICV: In Vitro Drug Diffusion study of different niosomal formulation: f1 f2 f3 f4 f5 f6 f7 f8 f9 Figure 1: In vitro release of Batch F17 to Batch 25 A statistical model incorporating interactive and poly nominal terms was used to evaluate the responses. Y = b0 + b1 X1 + b2 X2+b12 X1 X2+b11 X1 2 + b22x2 2 Where Y is the dependent variable, b0 is the arithmetic mean response of the 9 runs, and b1 is the estimated coefficient for the factor X1. The main effects (X1 and X2) represent the average result of changing 1 factor at a time from its low to high values. The interaction terms (X1X2) show how the response changes when two factors are simultaneously changed. The polynomial terms (X12 and X22) are included to investigate nonlinearity. The fitted equations relating the Entrapment efficiency and Vesicle size to the transformed factor are shown in the Table 6.9. The polynomial equations can be used to draw conclusions after considering the magnitude of coefficient and the mathematical sign it carries (i.e., negative or positive). Data were analyzed using Design of Expert version 9. R 2 value for Entrapment efficiency and vesicle size are and respectively indicating good correlation between dependent and independent variables. There was no need to develop reduced models because all response variables were significant i.e. P < The terms with P<0.05 were considered statistically significance and retained in the full factorial model.

9 Impact factor: /ICV: Table 5 Summary of results of regression analysis: Response Y1 ( Entrapment efficiency (%) ) P value R 2 value Response Y2 ( Vesicle size ( µm) ) P value R 2 value Full model for Entrapment efficiency: The polynomial equation was generated by multiple linear regressions. The equation derived is as under: Y= X X2+1.05X1X2-9.01X X2 2 The significance levels of all the coefficients were found to be P < 0.05 (Table 5 ) so there was no need to generate reduced model from the full model. The results of statistical analysis are shown in Table 5. The full model was tested in proportion to determine whether all the coefficient contribute significance information to the predi tion of Entrapment efficiency. Fig 2: response surface plot for Entrapment Efficiency

10 Impact factor: /ICV: Fig 3: Contour plot for Entrapmrnt efficiency Full model for Vesicle size: The polynomial equation was generated by multiple linear regressions. The equation derived is as under Y= X1+1.7X2+0.3X1X X X22 The significance levels of all the coefficients were found to be P < 0.05 (Table 5 ), so there was no need to generate reduced model from the full model. The results of statistical analysis are shown in Table. The full model was tested in proportion to determine whether the coefficient contribute significance information to the prediction of vesicle size.

11 Impact factor: /ICV: Fig 4: Response surface plot for Vesicle size Fig 5: Contour plot for Vesicle size

12 Impact factor: /ICV: Fig 6: Over lay Plot for selection of check point batch Check point batch: Formulation of check point batch from overlay plot Check point batch C1 was selected from the overlay plot of responses. The value of X1 and X2 and according to their amounts the predicted responses were given in the Overlay plot flag or in the solution of overlay data. From that any two batches C1 and C2 were selected for the verification of the model and %error was calculated using following formula: %Error = Actual response-predicted response 100. Predicted response Following table is showing the formula for Check point batch Table 6 Formulation of Check point batch Ingredient Quntity Clindamycin phosphate 100 mg Span mg Cholesterol mg Chloroform 7 ml Phosphate buffer 10 ml

13 Impact factor: /ICV: Table 7 % Error between actual and predicted response of Checkpoint batch Predicted response Actual response %Error Entrapment Vesicle Entrapment Vesicle Entrapment Vesicle size efficiency size efficiency size efficiency (µm) (%) (µm) (%) (µm) (%) From the check point batch, % Error between actual response and predicted response is less than 5% for both the responses, which confirms the validity of regression analysis. From above all evaluation parameters, batch F21 has been found to be optimum in terms of Entrapment efficiency, Vesicle size, In Vitro release, Drug content. So, batch F21 selected as optimized batch. The vesicular size of optimized formulation was measured by Malvern zeta sizer and particle characteristic was evaluated by tem study after sonication of optimized formulation. Vesicle size of optimized formulation after sonication: Fig 7: Vesicle size of optimized batch after sonication Vesicle characteristic:

14 Impact factor: /ICV: Niosomes were prepared by using varying concentration of surfactant and cholesterol when examined by Transmission electron microscope (TEM) appeared as a unilamellar vesicles with a predominant spherical shape. Fig 8: TEM study of Optimized batch For patient compliance and stability purpose the optimized niosomal suspension incorporated in to 1 % carbopol gel and Characterized for various parameters. a) Preparation of carbopol gel: 11,16 Carbopol 934 (1%) was dispersed in distilled water by stirring at 800 rpm for 20 minutes. Then, Propylene glycol (1% w/w) was added and the mixture was neutralized by dropwise addition of triethanolamine. Mixing was continued until a transparent gel appeared. b) Incorporation of Clindamycin Phosphate niosomes of optimized batch into carbopol gel Clindamycin phosphate equivalent to 1% w/w was incorporated into the gel base composed of Carbopol 934 (1%) Characterization of Niosomal gel: Organoleptic Parameters colour: White Homogenicity: good Odour: odourless Drug Content: 94% PH:6.8 Viscosity: cps In vitro drug release of Niosomal gel and Marketed gel:

15 Impact factor: /ICV: Table 8 In vitro drug release of niosomal gel and Marketed gel Time in Hours % Cumulative release F26 F ± ± ± ± ± ± ± ± ± ± ± ± ± ± Comparision of niosomal gel with marketed gel % CDR Series1 Series Time (hr) Fig 9: Comparision of release profile of niosomal gel with marketed gel In vitro release of niosomal gel and marketed gel is shown in table 8. From the data it was found that Niosomal gel releases % while marketed gel releases % within 12 hours. So, niosomes increase the diffusion of drug through skin.

16 Impact factor: /ICV: cumulative drug permeated ( mg/cm²) transdermal flux of niosomal gel time in hrs. y = 0.253x R² = Series1 Linear (Series1) Fig 10: Transdermal flux of Niosomal gel mg/cm² Transdermal flux of marketed gel time( hr) y = 0.190x R² = Series1 Linear (Series1) Fig 11: Transdermal flux of Marketed gel Trasdermal flux of niosomal gel and marketed gel are shown in figure 10 and 11. From the data, flux of niosomal gel is mg/cm2/hr and flux of marketed gel is mg/cm/hr. Thus, Niosomes increase the flux of drug through skin. The reason behind that is niosomes changes the structure of stratum corneum and produces thermodynamic gradient across the skin. Which enhance the permeation of drug through skin Analysis of drug release kinetic of optimized batch. 14,15 The Regression, Slop, Intercept of formulation optimized for Zero order, First order, higuchi, and Korsmeyer-peppas and value of release exponent (n) from Korsmeyerpeppas model are shown in Table

17 Impact factor: /ICV: Release kinetic data of niosomal gel Table 9 Release kinetic data of niosomal gel Parameter Zero order First order Higuchi Korsmeyer peppes Regression value Slope Intercept The data of release kinetic of drug shown in table 9. release kinetic data indicates that the release of drug from gels follows zero order drug release because the correlation coefficient values are higher in case of zero order equation, which describe that the release rate is independent of the concentration of the drug. The diffusion exponent n is the indicative of mechanism of drug release from the formulation.the n value of 0.45 is indicative of Fickian diffusion controlled drug release, n value between signifies anomalous (non-fickian) transport, n value of 0.85 indicates case II transport, and n value greater than 0.85 indicates super case II transport. Here the value of n=0.861 for optimized batch follows super case II that is combination of two mechanism 6.11 Stability study The stability of vesicles assesed by keeping the Niosomal Gel at different temperature. Optimized Niosomal gel was selected for stability studies of vesicles. The niosomal gel was kept in sealed vials (10ml) at 4 ± 2ºC and at room temperature for 30 days and in vitro release was determined after 1 month. Table 10 Stability study of Niosomal gel Time (hrs) % CDR % CDR (At 4 o ± 2 o temp.) % CDR (At room temp.) ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±0.29

18 Impact factor: /ICV: From the result of stability study, it was found that after one month of storage there was no significant change in the release of drug from niosomal gel and the stability of niosomal gel is more at room temp. than freezing temperature. ACKNOWLEDGEMENT: I Would like to thanks Shree Krishna Institute of Pharmacy, Shankhalpur for providing facilities for this reserch work. It is very great pleasure and profound sense of reverence that I express my gratitude and thanks to my esteemed honorable guide Mr. Vijay K. Patel, Assistant Professor, Shree Krishna Institute of Pharmacy, Shankhalpur, for valuable advice during the course of this investigation. It give me great pleasure to thanks him for his valuable guidance, inestimable encouragement, dedicated involvement, optimist towards puzzling obstacles and unwavering support, without whom, this work would have not reached the present status. I extend my immense thanks to Montage laboratory, Himmatnagar. for giving me a gift sample of drug kind co-operation and timely help without which I can never complete this research work REFERENCE 1. Rahimpour Y, Hamishehkar H, niosome as a carrier in dermal drug delivery, Recent Advances in Novel Drug Carrier Systems, Gangvar M, Singh R, goel R.K., Recent advances in various emerging vesicular systems: An Over view Asian pacific journal of tropical Biomedicine, 2012, Loan P, Nguyen H, Bouwstra1 J, Vesicles as a tool for transdermal and dermal delivery, Drug discovery, formulation and nanotechnology,2005, Goodman and Gilman s, The pharmacological Basis of therapeutics, 10 th edition McGraw Hill Med. Pub. Div. New York, 2001, Vyas J, Vyas P, Savant K, Formulation and evaluation of Topical Niosomal Gel of Erythromycin, International journal of Pharmacy and Pharmaceutical Sciences, 2011,3, Saumya S, Niosome: A Role in targeted drug delivery International journal of pharmaceutical science and research, Jan 2013, Nasir A, SL H and Amanpreet K, Niosome: an excellent tool for drug delivery, international journal of research in pharmacy and chemistry, 2012, Metkari*V,.Kulkarni L,.Patil S,.Jadhav P,.Jadhav P, Yadav P, Promising Drug Delivery System: A Niosomes Journal of Current Pharma Research 4 (2), 2014, Thomas L, Viswanad V, Formulation and Optimization of Clotrimazole-Loaded Pronio somal Gel Using 32 Factorial Design Scientia Pharmaceutica, 2012,

19 Impact factor: /ICV: Indian pharmacopoeia govt of India, Ministry of health and welfare, the Indian pharmacopoeia commission, Gajiyabad, Saxena S, kapoor V, Dr. Bharti M, formulation and evaluation of topical niosomal gel of roxithromycin world journal of pharmaceutical research (2014), Netweera V, Priprem A, Melatonin Encapsulated Niosomes Permeation Characteristics, International Journal of Science and Advanced Technology(2013), HendradI E*, Purwanti T,Rizkia Noviani A, the influence of niosome system (span 20/60-cholesterol) on the preparation characteristics and released of diclofenac sodium from gel carbopol etd 2020 pharmascientia,(2012), Kumar Y,.Kumar K, Shekar R, Formulation and Evaluation of Econazole Niosomes Scholars Academic Journal of Pharmacy (SAJP), (2013), Mujoriya Z*, Dr. Bodla R, Design and Development of Niosomal Delivery System for Ketoprofen Advances in Life Science and Technology, (2012), Desai S, Doke A, Disouza J. Athawale R, Development and Evaluation of Anti-fungal Topical Niosomal Gel Formulation, International journal of Pharmacy and Pharmaceutical Sciences, 2011,3, For Correspondence Jivrani Shilpa D shilpajivrani@gmail.com