IVA, Ivabradine HCL, SEM, Scanning electron microscope, NS, Nanosuspension, PI, Polydispersity index, RI, Refractive index, %T, %Transparency, SC, Subcutaneous tissue, CCD, Centre composite design, %EE, %Entrapment efficiency, ZP, Zeta potential,
The aim of the present research investigation was to develop nanosuspension based transdermal gelfor improving bioavailability and diffusivity of Ivabradine HCL. Ivabradine hydrochloride is an If channel blocker widely used as an anti-ischemic drug with lowering heart rate. It has a very low oral bioavailability about 40% due to its extensive hepatic metabolism. The multiple emulsion solvent diffusion evaporation method was adopted to develop Nanosuspension with employed Center composite design, which was characterized by Particle size, Zeta potential, %Entrapment efficiency, pH, Drug content. The optimized formulation showed 225nm Particle size, 0.12 PI, 36mv Zeta potential and 95.31% Entrapment efficiency. The drug permeation data of optimized formulation were significantly enhanced when compared with its plain gel. It could be concluded that prepared Ivabradine HCL nanosuspension showed better bioavailability as compared to pure Ivabradine HCL due to greater diffusivity achievement.
Ivabradine HCL, Transdermal gel, Nanosuspension
Ivabradine hydrochloride is used to treat mild to severe chronic heart failure and also used unstable angina pectoris. Angina pectoris is the disease that characterized by the insufficient supply of oxygen to the heart 1,2. Ivabradine hydrochloride is If channel antagonist. The plasma half-life is about 2hrs and bioavailability is 40% because of extensive first-pass hepatic metabolism. A nanosuspension is a dispersion of drug particle which have ing particle size about submicron range that are mainly stabilized by using surfactants. It is used for either oral and topical use or parenteral and pulmonary administration 3,4.
These nano-sized particles possess the larger surface area in comparison with the coarse particles of drugs, therefore require surface active agents to minimize the surface free energy and enhance physical stability. The amorphous drug nanosuspensions are rapidly undergo particle growth 5,6. Nanosuspensions have been reported to increase bioavailability by enhancing its dissolution velocity and saturation solubility, thus, leading to an increased concentration gradient. In the present study, Center composite design was used to formulate Ivabradine HCL nanosuspension in which Poloxamer 407 and magnetic stirring speed were taken as independent variables and their characterizations like Particle size, Polydispersity index, Zeta potential, and %Entrapment efficiency that were selected as dependent variables and step by step statistical analysis was performed. The optimized batch of IVA NS was converted into the transdermal gel using Carbopol 934P, HPMC EL50 and HPMC K4M gelling agent and their concentration were selected as independent variables and spreadability, gelling strength, and gel viscosity were dependent variables with employed D-optimal mixture design 7,8,9.
Materials and methods
Ivabradine HCL was obtained as a gift sample from Alembic Research Centre, Baroda, India. Isopropyl Myristate (IPM), Eudragit RL100, Poloxamer 407 were procured from Loba Chem, Mumbai, India. Span 20, Methanol, Carbopol 934P, HPMC K4M, and HPMC ELV 50 were procured from Himedia Labs, Mumbai, India Sigma-Aldrich, India. Double-distilled water was used throughout the study. All chemicals and solvents were of analytical reagent grade and used as received without further purification.
Primary screening study for selection of optimized organic solvent
Various organic solvents like Methanol, Acetone, and Dichloromethane with different polymers (Poloxamer 188, Poloxamer 407) were utilized for preparation of nanosuspension formulations. The prepared above formulations were evaluated particle size and percentage yield.
Preparation of Ivabradine HCL Nanosuspension
Dissolve suitable amount of Eudragit RL 100 in the suitable quantity of Span 20 and Methanol to prepare an organic dispersion. Emulsification of aqueous drug solution was carried out in organic dispersion under magnetic stirring at the certain time to obtain primary W/O emulsion. Further, this Primary emulsion was added in quantity sufficient double distilled water containing Poloxamer 407 at suitable stirring speed for 15 to 20 minutes to achieve final nanoparticulate dispersion 10,11.
Experimental design for Ivabradine HCL Nanosuspension
Various formulation batches were prepared for exploring the influence of the effect of polymer and stirring speed. Central composite design (CCD) was used for the systemic study of the combined effect of the effect of independent variables concentration of Poloxamer 407 (X1) and Magnetic stirring speed (X2) were studied at five different concentrations coded as –?, -1, 0, 1, and +? on critical dependent variables. The value for alpha (1.414) is calculated to fulfil both rotatability and orthogonality in the design. The design consists of total 13 runs (IVA-NS-F1 to IVA–NS-F13) that included 4 factorial points, 4 star points and 1 centre point and 5 replicate point experimental run. Total 13 experimental runs were generated as per Design Expert® 10.0.1 software (Stat-Ease. Inc. Minneapolis, USA) statistical software 7,12.
Layout of CCD experimental design
Experimental Run A: Conc. of Poloxamer 407 as per
Drug to Stabilizer ratio (%) B: Magnetic stirring speed (rpm)
IVA-NS-F01 +? 0
IVA-NS-F02 0 +?
IVA-NS-F03 0 0
IVA-NS-F04 0 0
IVA-NS-F05 1 1
IVA-NS-F06 -? 0
IVA-NS-F07 -1 -1
IVA-NS-F08 0 0
IVA-NS-F09 1 -1
IVA-NS-F10 0 0
IVA-NS-F11 0 0
IVA-NS-F12 0 -?
IVA-NS-F13 -1 1
Contour and response surface plot generated to study response variation against two independent variables. The optimized formulation was evaluated for the various response parameters and the experimental values obtained were compared with those predicted by the mathematical models. The significance of the models was further confirmed by statistical analysis. The diagnostic plot calculated to evaluate the residual information carefully to validate the assumptions underlying the analysis of variance. Additionally, the composition of optimized (checkpoint) batch was derived by constructing overlay plots. The percentage relative error of each response was calculated using following equation to judge the validity of the model 12, 13.
% Relative Error= (Predicted value–Experimental value) ×100
Preparation of Transdermal gelling system of Ivabradine HCL Nanosuspension
Disperse required quantities of Carbopol 934P, HPMC K4M and HPMC ELV 50 slowly into the suitable amount of previously prepared optimized IVA NS. This dispersion was vortexed for 10min on vortexer until uniform solution obtained. The final dispersion was kept overnight in a refrigerator at 5°C for 24hr for complete gelation of polymers with the addition of quantity sufficient Triethanolamine for adjusting the pH (up to 6.6) and subsequent sealing in the glass vials and storage at room temperature for further study. Conventional gels containing drug were also prepared using standard method 14-17.
Experimental design for Ivabradine HCL Nanosuspension based transdermal gel
Optimized formulation of Ivabradine HCL nanosuspension was converted into Nanosuspension based transdermal gel with employed D-optimal mixture design. X1: Concentration of Carbopol 934P, X2: Concentration of HPMC K4M, and X3: Concentration of HPMC ELV 50 were selected as independent variables and Spreadability, Gel viscosity and Gelling strength were taken as dependent variables. Total 8 experimental runs were generated as per DOE 10.0.00 18. The Layout of all experimental run was given in below (Table 2).
Layout of D-optimal mixture design
Experimental run Space type X1: Concentration of Carbopol 934P X2: Concentration of HPMC K4M X3:Concentration of HPMC ELV 50
IVA-NS-F1 CentEdge 0.5 0 0.5
IVA-NS-F2 AxialCB 0.166667 0.166667 0.666667
IVA-NS-F3 CentEdge 0.5 0.5 0
IVA-NS-F4 Vertex 1 0 0
IVA-NS-F5 CentEdge 0 0.5 0.5
IVA-NS-F6 Vertex 0 1 0
IVA-NS-F7 AxialCB 0.166667 0.666667 0.166667
IVA-NS-F8 Vertex 0 0 1
2.2.7.Optimization of D-optimal mixture design
The optimization of formulation variables using mathematical equations and response surface plots to prepare the desired Ivabradine HCL nanosuspension based transdermal gel. The special cubic model incorporating interactive and polynomial terms was exercised to evaluate the responses 18.
Yi = b1X1+b2X2+b3X3+b12X12+b13X13+b23X23+ b123X1X2X3
Where Yi was the dependent variable, bi was the expected coefficient for factor Xi. Further same steps were carried out as per previous part in this paper.
2.2.8.Physiochemical Characterization of formulations
220.127.116.11 Particle size distribution and zeta potential analysis
Mean particle size, size distribution and zeta potential of IVA nanosuspensions were determined using Particle size analyzer (Zetatrac). 1ml of samples was diluted to 10ml with distilled water, agitated for 5min and these diluted samples were subjected to Particle size analyzer 19.
18.104.22.168. Percentage yield and drug content
The drug content was determined by dissolving the accurately weighed quantity of prepared nanosuspension in pH 6.8 phosphate buffer. The solution was ?ltered using (0.45m) membrane filter, suitably diluted and the samples were measured using double beam UV-spectrophotometer at 286nm against pH 6.8 buffer as blank for determining the drug content 19.
22.214.171.124. Determination of saturation solubility
The excess amount of various formulation batches of IVA NS was added to 10ml of pH 6.8 phosphate buffer. Samples were sonicated for 5sec and stirred in a water bath (37±0.3°C) for 48h. Samples were then centrifuged at 10,000rpm for 15min then ?ltered with the membrane filter (0.45µm), diluted with appropriate quantity and analyzed using double beam UV-spectrophotometer against pH 6.8 buffer as blank as described earlier 19.
126.96.36.199. %Entrapment efficiency
The encapsulated IVA was measured by subtracting the free amount of the drug from IVA Nanosuspension by ultracentrifugation at 25,000rpm for 30min. The solution was filtered using membrane filter (0.45µm) and diluted with pH 6.8 Phosphate buffer and IVA content was determined using double beam UV-spectrophotometer against pH 6.8 phosphate buffer as blank. Entrapment efficiency (%EE) was calculated from the following equation 20,21.
% Entrapment efficiency= Weight of Initial drug- Weight of Free drug × 100
Weight of Initial drug
188.8.131.52. Scanning Electron microscope study
The morphology of nanoemulsion can be determined by scanning electron microscopy (SEM). A good analysis of shape and surface morphology of disperse phase in the formulation is obtained through SEM Image analysis software 22.
184.108.40.206. Rheological Studies and pH Measurement
The viscosity was determined by using Rheometer with the S61 spindle at 20rpm speed and 25°C temperature. The pH of each batch was measured using digital pH meter which was calibrated using buffers of pH 4 and pH 7 before the measurements 23,24.
The clarity of formulated solution was determined by visual inspection under a good light, observed against a black and white background, with the contents set in motion with swirling action 25.
It consists of a wooden block, which was provided by a pulley at one end. A ground glass slide was fixed on this block. An excess of gel (about 1 gm) under study was placed on this ground slide. The gel was then placed between these slides. Another glass slide has the same the dimension of the fixed ground slide and provided with the hook (string attached to hook). One kg weight was placed on the top of the two slides for five minutes to expel air and to provide a uniform film of the gel between the slides. The top plate was allowed to pull of 80gm. The time (in seconds) required by the top slide to cover a distance of 7.5 cm be noted. A shorter interval suggests better spreadability 26.
Where M=weight tide to upper slide, L=length moved on the glass slide, T=time taken.
220.127.116.11. Gelling strength
A sample of 50g of the gel was put in a 100ml graduated cylinder. A weight of 35g was placed onto the gelled solution. The gel strength, which is an indication for the viscosity transdermal gel of the at physiological temperature, was determined by the time in seconds required by the weight to penetrate 5cm into the gel 24,27.
18.104.22.168. Fourier transform infrared spectroscopy
Fourier transform infrared (FT-IR) spectra of Optimized batches of IVA NS GEL exicipients mixture and pure drugs were recorded on FT-IR. The infrared spectra of alone IVA and IVA NS GEL have detected the existence of an interaction between drug and polymer. For a recording of spectra, a minute quantity of drug powder and drug exicipient mixture was placed on the sample holder and compressed lightly using a pressure clamp. Scanning was performed in the range of 4000–400cm-1 28.
22.214.171.124. Drug content of gel
An accurate amount of prepared gel dissolved in 100ml of pH 6.8 phosphate buffer and allowed to shake for 2hrs on the mechanical shaker. This solution was filtered using membrane filter (0.45µm). After suitable dilution drug absorbance was recorded by double beam UV-spectrophotometer at 286nm using pH 6.8 phosphate buffer as blank 29.
126.96.36.199. Ex vivo and in vitro permeation study of optimized formulations
For ex vivo study excised goat SC tissue obtained from the local slaughterhouse and mounted on Franz diffusion cell containing a diffusion area of 1.77cm2. The receptor compartment was filled with 16ml of pH 6.8 phosphate buffer and the content was magnetically stirred at 300rpm to prevent stagnant layer formation at 32°C. The donor compartment was filled with 1gm or 1ml Ivabradine HCL formulations to achieve desired drug concentration at the site. Aliquots of 0.5ml were withdrawn at predetermined intervals (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 and 24hr) from receptor medium and replaced immediately with an equal volume of receptor solution to maintain the volume constant. The amount of drug permeated was measured after suitable dilution using double beam UV-visible spectrophotometer against pH 6.8 buffer as blank. In order to the estimated extent of enhancement by formulations, a conventional gel of drug with same concentration was also subjected to in vitro permeation under the same circumstances 18.
188.8.131.52. Permeation Data Analysis
The results data of in-vitro permeation study were employed to calculate permeability parameters like Flux (Jss), Permeability coefficient (Kp) and enhancement ratio (ER). The flux (Jss, µg/cm2/hr) of the drug was calculated from the slope of the plot of the cumulative amount of drug permeated per square centimetre of skin at steady-state against the time using linear regression analysis. Permeability coefficient (Kp) of a prepared patch has been determined by following equation
Where Jss represents the flux of studied patch, Cd represents the concentration of drug in donor compartment (µg/cm2) 30.
The Enhancement Ratio was determined by the following equation;
Enhancement Ratio (ER) = Steady state of Flux by IVA NS transdermal gel
Steady state Flux by plain gel
184.108.40.206. Release Kinetic Modelling
The results data of in vitro permeation study of nanoemulsion loaded in situ gel was fitted with different mathematical models to understand the kinetics and mechanism of drug release. Based on the R2 value (n value of korsemeyer), the best-fitted model has selected The kinetics of drug release from drug delivery system to decide by incorporating different mathematical models like Zero order, First order, Hixson Crowell, Higuchi, Korsmeyer.
Where F represents the fraction of drug released in time t and K0 is the zero-order release constant.
Where F represents the fraction of drug released in time t and K is the first order release constant.
Where F represents the fraction of drug released in time t and Kh is the Higuchi dissolution constant.
W01/3 –Wt1/3 =? t
Where W is the initial amount of drug in the pharmaceutical dosage form, W is the remaining amount of drug in the pharmaceutical dosage form at time t, and ? (kappa) is a constant incorporating the surface volume relation.
Where F represents the fraction of drug released in time t, K is the Korsmeyer–Peppas release rate constant, and n is the diffusion exponent 23,24.
Results and discussion
3.1. Primary screening study for selection of optimized organic solvent
As per results of screening study, Methanol and Poloxamer 407 showed higher percentage yield so it was selected as an optimized organic phase for preparation of nanosuspension by multiple emulsification solvent diffusion method. Center composite design utilized to explore the influence of independent variables on dependent variables. X1: concentration of Poloxamer 407 and X2: Magnetic stirring speed were selected as independent variables and particle size, polydispersity index, zeta potential and %entrapment efficiency were taken as dependent variables. The results of total 13 experimental batches have summarized in (Table 3).
Results of observed responses of center composite design
Batch code Particle size (nm) PI ZP (mv) EE (%)
IVA-NS-F01 178.9±2.115 0.1±11.32 34.16±0.514 94±1.15
IVA-NS-F02 260.8±1.56 0.3±10.98 32.54±1.692 70.211±3.8
IVA-NS-F03 287.4±4.17 0.18±5.23 31.62±3.17 82.14±8.67
IVA-NS-F04 287±3.24 0.17±7.19 35.03±0.16 81.55±0.71
IVA-NS-F05 210±0.15 0.14±0.94 21.05±5.97 83.67±4.31
IVA-NS-F06 263.8±0.98 0.25±0.21 60.01±6.31 99.41±9.87
IVA-NS-F07 267.8±2.3 0.26±3.13 36.12±2.001 85.46±1.05
IVA-NS-F08 287.95±4.67 0.18±15.1 33.12±0.674 80.76±7.5
IVA-NS-F09 270.3±7.31 0.18±12.78 35.25±3.18 83.25±5.39
IVA-NS-F10 286.98±0.84 0.17±6.51 37.45±9.57 80±8.41
IVA-NS-F11 287.69±1.24 0.176±7.69 36.12±2.014 81.95±2.69
IVA-NS-F12 320±6.77 0.19±1.121 39.13±6.47 68.74±3.22
IVA-NS-F13 324.2±9.11 0.25±4.70 55.53±9.127 95.44±6.14
The results are mean ± SD (n=3), aPI: Polydispersibility Index, bZP: Zeta Potential, c%EE: Entrapment efficiency
The study of the statically design generally starts with the determination of the transformation of the given variables to improve the fit between the response and independent variables. The transformation was determined by using the Box-Cox plot that gives the optimum lambda value (?) depending on which suitable transformation was made. The advantages of model transformation are to stabilize the variance of residual and normalize the distribution of the residual. But as per graph, there was no need for power transformation 31.
Fig 1. Optimized Ivabradine HCL nanosuspension
Particle size (Fig. 2) PI (Fig. 3) ZP (Fig. 4) %EE (Fig. 5)
Fig. (2) Particle size (3) Polydispersity index (4) Zeta potential (5) %Entrapment efficiency box cox plot for power transform.
Selection of the optimization model that best describes and fits the obtained data is the first step towards an optimal statistical analysis. Therefore, different models, viz., linear, quadratic, and special cubic, were first analyzed for the response variables (Y1 to Y3) by the predicted residual sum of square (PRESS) statistic for and R2 determination of suitability of model fitting. Selection of model was based on the highest order model that explains significantly more of the variation in the response (p-value small) as well as minimum PRESS value. Here, all the responses followed linear mathematical model while remaining others followed the quadratic model. The quadratic model contained polynomial equations representing the quantitative effect of the formulation variables on the measured responses 32.
Statistical analysis (ANOVA) of CCD experimental design batches
Responses R2 Adjusted R2 SS MS F ratio P value
Particle size 0.8955 0.8209 15834.65 3166.93 12.00 0.0025
PI 0.8420 0.7292 0.030 5.997E-003 7.46 0.0100
ZP 0.9270 0.8749 1121.28 224.26 17.79 0.0007
%EE 0.9499 0.9141 885.35 177.07 26.54 0.0002
Optimization of each formulation component was performed by fitting desired response objectives in the designed model. The effect of formulation components on the response Y1 to Y3 is graphically presented as 2D and 3D contour plots. A residual analysis is necessary to confirm that the assumptions of the ANOVA are met. Determination coefficient r2 value was 0.999 so strong correlations values of “Prob> P” less than 0.0500 indicate model terms were significant. The generated regression coefficients were represented at (Table 5). The regression coefficient is indicated the expected change in response Y per unit change in X when all remaining factors are held constant. A positive value indicates direct proportionality, while a negative value indicates an inverse relationship between the independent and dependent variables 33.
Coefficient table of all observed responses
Responses A B AB A2 B2
Particle size -16.4708 -23.4527 -4.175 -36.227 -1.702
p-Value 0.0241 0.0047 0.6231 0.0006 0.7903
PI -0.0504713 0.0131579 -0.008675 0.0006075 0.0335325
p-Value 0.0015 0.2307 0.5599 0.9565 0.0169
ZE -8.98843 -0.513708 -8.4025 5.09037 -0.534625
P-Value 0.0002 0.6946 0.0021 0.0069 0.7031
%EE -2.70386 1.56004 -2.39 8.67869 -4.93606
p-Value 0.0211 0.1313 0.1067 < 0.0001 0.0015
In this (Table 5), each column contains the coefficient estimate for the coded model term and the p-value for that respective coefficient.
3D Response surface plot (Fig. 6) Particle size
2D Counter plot (Fig. 7)
3D Response surface plot (Fig. 8) Polydispersity index
2D Counter plot (Fig. 9)
3D Response surface plot (Fig. 10) Zeta potential
2D Counter plot (Fig. 11)
3D Response surface plot (Fig. 12) %Entrapment efficiency
2D Counter plot (Fig. 13)
Fig. 6-13 Influence of formulation factors on all responses (3D &2D).
Three-dimensional response surface plots and two-dimensional plots are presented in (Figure 6-13). In which all figures exhibited a nearly linear relationship of all factors in the form of almost straight lines 12.
Desirable constraints for numerical optimization of all responses
Goal Lower Limit Upper Limit
Poloxamer 407 amount In Range -1 1
Magnetic stirring speed In Range 1 1
Particle size Minimize 178.9 320
Polydispersibility index Maximize 0.1 0.3
Zeta Potential Minimize 21.05 60.01
% Entrapment efficiency Maximize 68.74 99.41
The optimization of the gel was performed using numerical optimization technique, where the optimization is based upon the desirability. From above (Table 6) enlists different constraints decided for numerical optimization. Based on the desired criteria, optimized solutions were predicted by the software and the solution that had higher desirability value (0.97) was selected as optimized formulation 34.
Fig. 14. Overlay plot of Ivabradine HCL Nanosuspension
Results of optimized formulations
Observed Response Predicted Value Experimented value %Relative error
Particle size 245.44 225±0.169 8.32
Polydispersity index 0.13 0.12±1.47 7.69
Zeta potential 34.16 36±0.731 5.11
%Entrapment efficiency 86.78 95.31±5.028 8.94
Results are (Mean±SD, n=3)
To validate the applied model, an optimized formulation (F) was developed. Predicted and actual responses along with percentage relative error are given in (Table 7). The particle size, polydispersibility index, Zeta potential and %Entrapment efficiency were obtained as 225±0.169, 0.12±1.47, 36±0.731, 95.31±5.028 respectively which are in close agreement with the predicted value. Percentage prediction error was calculated which was obtained as less than 10%, which also confirmed the validity of Ivabradine HCL Nanosuspension 13,19,35.
3.2.Characterizations of Ivabradine HCL Nanosuspension
The particle size values of all the batches of experimental design have been summarized in (Table 3). The optimized batch of IVA NS was showed the particle size 225nm which confirmed nanometre size of the developed formulation. When the concentration of stabilizer increased then particle size is decreased. At increasing magnetic stirring speed that enhances the particle size reduction but at same time polydispersity slightly increased. The PI of the optimized batch of IVA NS was obtained 0.12 which confirmed narrow size distribution of developed formulations. Zeta potentials values of all experimental design batches of IVA Nanosuspension are summarized in (Table 3). Eudragit RL 100, Poloxamer 407 and Span 20 act as the stabilizer for present formulations that helps to reduce the free energy of all formulation system. Both are effective in the stabilizing effect by steric (coating of particles) and electrostatic (repulsion between particles) mechanisms offered by polymers and ionic surfactants. The zeta potential observed between 21.05-60.01mv. This positive high surface charge produces repulsion between particles and prevents their aggregation. Apart from stability, zeta potential also gives information about mucoadhesive nature of particles. The observed positive zeta potential was based on the presence of Quaternary Ammonium group in the backbone of the Eudragit polymer. The zeta potential value of the optimized batch of IVA NS was found to be 36mv which supported the stability of dispersed systems. The adsorbed surfactant Poloxamer 407 present on the nanoparticles surface may shield the particle surface, thus covering is with the electrically neutral layers and causing a slight shift in the surface charge 36. Poloxamer 407 has linear ABA triblock polymer chain (A stands for hydrophilic polyethylene oxide (PEO) segment and B stands for hydrophobic polypropylene oxide (PPO) segment). The hydrophobic PPO chains can drive the polymer to adsorb on the surface of drug particles, while the hydrophilic PEO chains surround the drug particles providing steric hindrance against aggregation 37. It is reported that Ivabradine is slightly acidic in nature so such compound has high affinity with eudragit polymer so it might be one of cause for exhibiting showed high entrapment efficiency 8.
Poloxamer-407 can develope substantial mechanical as well as thermodynamic barrier at the interface that prevent coalescence of individual emulsion droplets at their optimum level. The %Entrapment efficiency of all the batches was observed in the range of 70.211-99.41% that tabulated in (Table 3). %EE of the optimized batch was found to be 95.31%. The maximum entrapment was found in batch 6 and minimum was found in batch 2. It was clear that increased in %EE with the increase in polymer concentration in the various formulations 38. The drug content of optimized formulation was found to be 99.57%. The drug content of optimized formulation was more than 85%. So this method is suitable for size reduction 21. The nanoparticles surface appearance and shape were analyzed by scanning electron microscope study (Figure 15). This was indicating the size and shape of the prepared nanosuspension and the nanoparticles were found to be spherical with a smooth surface and less aggregate 39.
Fig. 15 SEM Image of Optimized Ivabradine HCL nanosuspension.
3.3. Experimental results of Ivabradine HCL nanosuspension based transdermal gel
The optimized batch of IVA NS was converted into the preparation of transdermal gel using D-Optimal mixture experimental design. The results of responses like spreadability, viscosity of gel and gelling strength have been summarized below (Table 8).
Results of observed responses of D-Optimal mixture design
Formulation code Spreadability (gm.cm/sec) Viscosity of gel (sec) Gelling strength (sec)
IVA-NS-GEL-F01 15±0.986 20615±0.029 1±0.968
IVA-NS-GEL-F02 27±1.74 8628±1.051 0.388±0.127
IVA-NS-GEL-F03 12±0.407 21208±4.14 2±0.947
IVA-NS-GEL-F04 8±7.81 30610±5.78 10±1.031
IVA-NS-GEL-F05 21±0.132 11215±1.175 0.91±0.884
IVA-NS-GEL-F06 19±1.694 11837±0.247 0.917±2.176
IVA-NS-GEL-F07 24±2.027 9518±1.911 0.415±0.009
IVA-NS-GEL-F08 23±0.569 10622±0.208 0.864±0.433
Results are (Mean ±SD, n=3)
The Box-Cox plot from Design-Expert recommends natural log transformation of the viscosity of gel and spreadability and inverse transformation of Gelling strength 7.
Spreadability (Fig. 16) Gel viscosity (Fig. 17) Gelling strength (Fig. 18)
Fig. 16-18 Box cox plot for power transform all observed responses
Statistical analysis of observed responses
Responses R2 Adjusted R2 SS MS Adeq Precision F-Ratio p-Value
Spreadability 1.0000 0.9999 4.52 0.75 259.081 7929.31 0.0086
Gel strength 1.000 0.9997 5.11 0.85 195.277 4595.78 0.0113
Gel viscosity 0.9999 0.9994 4.25E+008 7.093E+007 127.186 2100.18 0.0167
Determination coefficient r2 value was 0.999 so strong correlations 7,18.
Spreadability Fig. 19 Gelling strength Fig. 20 Viscosity of gel Fig. 21
Fig. 19-21 3D response surface plot of all responses.
Spreadability Fig. 22 Gelling strength Fig. 23 Viscosity of gel Fig. 24
Fig. 22-24 2D counter plot of all responses.
Coefficient table of observed responses
Responses A B C AB AC BC ABC
Spreadability 2.82843 4.35682 4.79791 0.522401 0.24 0.0208418 42.03
p-Value 0.0051 0.005 0.0051 0.0578 0.12 0.737 0.007
Viscosity of gel 30610 11876.2 10582.8 16.3636 -82.36 -58 -290280
p-Value 0.0094 0.0094 0.0094 0.9884 0.94 0.9590 0.0203
Gelling strength 0.1 1.09 1.15 -0.37 1.47 -0.10 79.6305
P-Value 0.0103 0.0103 0.0103 0.1116 0.02 0.37 0.0055
It was seen that spreadability and viscosity of gel had a significant effect on the response (p<0.05) 40.
Formulation and composition of optimized batch
Name of component Concentration (%w/v)
Carbopol 934P 0.013
HPMC K4M 0.119
HPMS ELV 50 0.07
Results of optimized formulations
Observed Response Predicted Value Experimented value %Relative error
Spreadability 25.94 28±2.32 7.35
Gelling strength 0.449 0.410±0.661 8.68
Viscosity of Gel 8264.04 7589±1.005 8.16
Results are (Mean ±SD, n=3)
The spreadability, Gelling strength, and Viscosity of gel were obtained as 28gm.cm/sec, 0.410sec and 7589cps, respectively which are in close agreement with predicted value suggested by software confirmed the validity of D-optimal mixture design for optimization of gel formulation 19,35.
3.4 Fourier Transform Infrared Spectroscopy
Fourier Transform Infrared Spectroscopy (FTIR) spectra of IVA and IVA NS GEL are shown in Figure 25 (a) and (b). An FT-IR spectrum of pure IVA shows principal peaks at different wave numbers as shown in figure 25 (a). The FT-IR spectra of the IVA excipients mixture had all the characteristic peak and band values of pure IVA that all the functional groups of IVA are well preserved. This study clearly indicates the absence of any chemical interaction between the drug (Ivabradine HCL) and the polymers (Carbopol 934P, HPMC K4M and HPMC ELV 50) in the final formulation, thus confirming that the drug is compatible with all the polymers used in the present investigation 24.
Fig. 25 (a) FT-IR of Pure Drug
Fig. (b) FT-IR of Ivabradine HCL+exicipients mixture
Fig. 25. Infrared spectra of (a) Ivabradine HCL and (b) IVA with exicipients.
3.5Characterizations of IVA nanosuspension loaded gel
The viscosity of optimized Nanosuspension was very low so it was not suitable for the transdermal application so it was one of the reasons for incorporation of Nanosuspension into the gel matrix. The gel viscosities of all experimental batch were found to be 8628 -30610cps. The pH of optimized formulation was found near to the skin pH value 6.71. From a patient compliance point of view, spreadability exhibits a major role for transdermal formulation. The spreadability of all the formulation batches was found in the ranges of 8±7.81-27±1.74gm.cm/sec administration and larger diameter suggested highly spreadable that would assure the practicability to the skin. The %Drug content of Nanosuspension based gel was obtained by 99.59% 14,41.
3.6Ex vivo skin permeation study
Ex vivo skin permeation study was carried out to compare the drug release from optimized nanosuspension, nanosuspension loaded gel and conventional gel, all having the same quantity of Ivabradine HCL. The significant difference in Ivabradine HCL drug permeation between optimized nanosuspension formulation and its gel was probably because of the average particle sizes, which were significantly smaller in nanosuspension formulation. The enhancement of drug release could be due to the smallest particle size and lowest viscosity compared to nanosuspension based gel as well as its plain gel. The particle size reduction produced the most crucial effect on drug fluxes through the skin. It can be further explained by the larger surface area and potentially higher dissolution velocity of the nanosuspension system. The smaller particles easily diffused from the high concentration to the low concentration and precipitated on the surface of the large particles 42. The release of IVA HCL from nanoparticles was biphasic, with an initial faster release for the first 2hours, followed by a period of slow but sustained release at the end of 24hrs. The initial fast release phase may be due to the rapid dissolution of the IVA nanoparticle adsorbed onto the surface of the Eudragit nanoparticles. Then, the IVA Nanoparticulate dispersion in the polymer matrices led to a gradual dissolution and release of the drug. The principal requirement of any controlled release system is that the release profile and rate are controlled 43. The optimized batch of Nanosuspension showed improvement in permeability parameters like steady-state flux (Jss), the permeability coefficient (Kp) and enhancement ratio (Er) with respect to its Ivabradine gel. The comparison of permeability parameters of formulations is given in (Table 13).
Comparison of diffusion parameters
Parameters IVA gel IVA NS IVA NS gel
Flux (Jss) 15.42 µg/cm 2hr 103 µg/cm 2hr 98.48 µg/cm 2hr
Permeability coefficient (Kp) 7.71 cm/hr 51.5 cm/hr 49.24 cm/hr
Enhancement ratio (Er) – 2 2
Drug release kinetic model
The model that best fits the release data were evaluated by the correlation coefficient (r2). The correlation coefficient (r2) values were used as the criteria to choose the best model to describe drug release from IVA NS based gel. A burst release followed by a steady release (zero order release) has been observed. The r2-values (r2=0.9938) obtained for fitting the drug release data to the Korsemeyer over a period of 24hours among all other models. The ‘n’ value (0.846) was more than 0.5, which indicated that optimized showed drug release by nonfickian type diffusion 44,45,46.
Results of release kinetic model for an optimized batch of IVA NS based gel
Parameters Zero First Higuchi Hixon crowel Korsemeyor Peppas
R2 0.9065 0.9552 0.9877 0.9508 0.9938
Rate constant 5.759 0.129 21.284 0.036 27.932
Optimized formulation showed greater spreadability indicated more area of skin was occupy by the nanosize particle and viscous gel produce better retention of drug nanosized particle that adhered to skin with the high surface area. The pH of all the formulations lies in the normal pH range of the skin and would not produce any skin irritation. The flux was increased as compare conventional gel form. Drug permeation rate was increased with prolonged period time to produce sustained release action. So the Ivabradine HCL Nanosuspension can be used as an antihypertensive agent for transdermal drug delivery.
Declaration of interest
The authors report no conflicts of interest.
We would like to thank Alembic research centre for providing gift sample of Ivabradine HCL. We also sincerely thankful to Junagadh Agriculture University (Gujarat) for performing Scanning electron microscope study in present research investigation.
Patel DB, Patel KJ, Bharadia PD. Formulation and evaluation of orodispersible tablet of ivabradine hydrochloride. Pharm Bio Eval. 2017;4:162-170.
Bajwa PS, Bhargava A, Sharma B, Sharma J, Sharma. Development and In Vitro-In Vivo Characterization of Chronomodulated Pulsatile Delivery Formulation of Terbutaline Sulphate by Box-Behnken Statistical Design. AAPS PharmSciTech. 2017.
Barkat MA, Harshita, Ahmad I, Ali R, Singh SP, Pottoo FH, Beg S, Ahmad FJ. Nanosuspension-Based Aloe vera Gel of Silver Sulfadiazine with Improved Wound Healing Activity. AAPS PharmSciTech, 2017;18: 3274-3285.
Prasanna V, Tubati, Murthey TE, A. Rao SS. Formulation Development and Statistical Optimization of Ivabradine Hydrochloride Floating Pulsatile Microspheres Using Response Surface Methodology. Asian J Pharmaceu. 2016; 10:S110-S120.
Lodhi M, Dubey A, Narayan R, Prabhakara P, Sneh P. Formulation and evaluation of buccal film of Ivabradine hydrochloride for the treatment of stable angina pectoris. Int J Pharm Investig. 2013;3:47-53.
Shen C, Shen B, Liu X, Yuan H. Nanosuspensions based gel as delivery system of nitrofurazone for enhanced dermal bioavailability. J Drug Deliv Sci Tech 2018;43: 1-11.
Xinghua J, Zhang Y, Xiao L, Zhao Z. Optimization of Extended Zero-order Release Glicazide Tablets Using D-optimal Mixture Design. Yakugaku zasshi. 2008;128:1475-1483.
Yadav SK, Mishra S, Mishra B. Eudragit-based nanosuspension of poorly water-soluble drug: formulation and in vitro-in vivo evaluation. AAPS PharmSciTech, 2012;13:1031-1044.
Ghasemian E, Motaghian P, Vatanara A. D-optimal Design for Preparation and Optimization of Fast Dissolving Bosentan Nanosuspension. Adv Pharm Bull, 2016;6: 211-218.
Tamilselvan N, Raghavan CV, Krishnamoorthy B, Siram K. Preparation of plga nanoparticles for encapsulating hydrophilic drug: Modifications of standard methods and it’s in vitro biological evaluation. Asian J Res in Bio Pharm Sci. 2014;2:121-132.
Rawia Khalil, Hashem F, Zaki H, Arini SE. Polymeric nanoparticles as potential carriers for topical delivery of colchicine: Development and in vitro characterization. Int J Pharm Sci Res. 2014;4:1746-1756.
Garala K, Patel J, Patel A, Dharamsi A. Enhanced encapsulation of Metoprolol Tartrate with carbon nanotubes as adsorbent. Appl Nanosci. 2011;1:219-230.
Pandya VM, Patel JK, Patel DJ. Effect of different stabilizer on the formulation of simvastatin nanosuspension prepared by nanoprecipitation technique. Res J Pharm Bio Chem Sci. 2010;1:910-917.
Khurana S, Jain NK, Bedi PM. Nanoemulsion based gel for transdermal delivery of meloxicam: physico-chemical, mechanistic investigation. Life Sci. 2013; 92: 383-92.
Sinha P, Srivastava S, Mishra N, Singh DK, Luqman S, Chanda D, Yadav NP. Development, optimization, and characterization of a novel tea tree oil nanogel using response surface methodology. Drug Dev Ind Pharm. 2016;42: 1434-1445.
Harwansh RK, Mukherjee PK, Bahadur S, Biswas R. Enhanced permeability of ferulic acid loaded nanoemulsion based gel through skin against UVA mediated oxidative stress. Life Sci. 2015;141: 202-211.
Phatak Atul A., Chaudhari PD. Development and Evaluation of Nanogel as a Carrier for Transdermal Delivery of Aceclofenac. Asian J Pharm Tech.2012;2:125-132.
Dhingani A, Patel J, Garala K, Raval M, Dharamsi A. Quality by Design Approach for Development of W/O Type Microemulsion Based Transdermal Systems for Atenolol. J Dispers Sci Technol. 2014;35:619-640.
Shah SR, Parikh RH, Chavda JR, Sheth NR. Application of Plackett–Burman screening design for preparing glibenclamide nanoparticles for dissolution enhancement. Powder Technol. 2013;235:405-11.
Thakkar HP, Bindesh V, Thakkar SP. Development and characterization of nanosuspensions of olmesartan medoxomil for bioavailability enhancement. J Pharm Bioall Sci. 2011;3:426-434.
Shid RR, Dhole SN, Kulkarni N, Shid SL. Formulation and evaluation of nanosuspension delivery system of Simvastatin. Int J Pharm Sci Nanotech. 2014;7:2459-2476.
Verma S, Singh AK, Mukerjee A. Formulation and evaluation of ketoconazole nanoemulgel World J Pharm Pharm Sci. 2016;5:899-911.
Ampati S, Hanumakonda A, Maheshwaram V.Formulation and evaluation of nasal insitu gel of fluoxetine hydrochloride. Indo Amer J Pharma Sci. 2016; 3: 573-581.
Patel N, Baldaniya M, Raval M, Sheth N. Formulation and development of in situ nasal gelling systems for quetiapine fumarate-loaded mucoadhesive microemulsion. J Pharma Innov. 2015;10:353-373.
Makwana SB, Patel VA. Development and characterization of in-situ gel for ophthalmic formulation containing ciprofloxacin hydrochloride. Results in Pharma Sciences.2015;6:1-6.
Garala K, Patel J, Shah M, Ramkishan A, Patel J. Formulation and evaluation of periodontal in situ gel. Int J Pharm Investig. 2013;3:29-41.
Jaiswal M, Dudhe R, Sharma PK. Nanoemulsion: an advanced mode of drug delivery system. 3 Biotech. 2015;5:123-127.
Patel J, Dhingani A, Garala K, Raval M, Sheth N. Quality by design approach for oral bioavailability enhancement of Irbesartan by self-nanoemulsifying tablets. Drug Delivery, 2014; 21: 412-35.
Doaa AH, Dalia AE, Sally AA, Mohamed AE. Formulation and evaluation of Fluconazole Topical gel. Int J Pharm Pharmaceu Sci. 2012;4:176-183.
Tank CJ, Kapse GK, Sarvaiya JI. Iontophoresis of fluvastatin sodium: Study of various factor and in vitro permeation. Int J Pharm Sci Res. 2013;4:3444-3452.
Agrawal A, Maheshwari RK. Formulation development and evaluation of in situ nasal gel of poorly water soluble drug using mixed solvency concept. Asian J Pharm. 2011; 5: 131-140.
Sanka K, Suda D, Bakshi V. Optimization of solid-self nanoemulsifying drug delivery system for solubility and release profile of clonazepam using simplex lattice design. J of Drug Del Sci and Tech. 2016
Yang C, Shen Y, Wang J, Ouahab A, Zhang T, Tu J. Cationic polymer-based micro-emulgel with self-preserving ability for transdermal delivery of diclofenac sodium. Drug Deliv. 2015;22:814-822.
Rajamma AJ Yogesha HN, Sateesha SB. Natural gums as sustained release carriers: development of gastroretentive drug delivery system of ziprasidone HCl. DARU J Pharm Sci. 2012;20:1-9.
Raza A, Bukhari NI, Karim S, Ha?z MA, Hayat U. Floating tablets of minocycline hydrochloride: Formulation, in-vitro evaluation and optimization. Future J Pharm Sci 2017;3:131-139.
Mandal B, Alexander KS, Riga AT. Sulfacetamide loaded Eudragit(R) RL100 nanosuspension with potential for ocular delivery. J Pharm Pharm Sci. 2010;13:510-523.
Sathali A., Gopinath M. Formulation and evaluation of Paliperidone Nanocrystals. BioMedRx. 2013;1:422-438.
Dandagi P, Kerur S, Mastiholimath V, Gadad A, Kulkarni A. Polymeric ocular nanosuspension for controlled release of acyclovir: in vitro release and ocular distribution. Iranian J Pharm Res. 2009;8: 79-86.
Singh VK, Singh P, Chandra D, Rai U , Singh SK. Formulation and evaluation of effect of different stabilizer at nanosuspension of satranidazole. World J Pharm Pharma Sci, 2014;3:1367-1377.
Ghasemian E, Motaghian P, Vatanara A. D-optimal Design for Preparation and Optimization of Fast Dissolving Bosentan Nanosuspension. Adv Pharm Bull. 2016;6:211-218.
Arora R, Aggrawal G, Harikumar SL, Kaur K. Nanoemulsion Based Hydrogel for Enhanced Transdermal Delivery of Ketoprofen. Adv in Pharma. 2014; 2014: 1-12.
Ghosh I, Kohn BM. Influence of critical parameters of nanosuspension formulation on the permeability of a poorly soluble drug through the skin–a case study. AAPS PharmSciTech. 2013;14: 1108-1117.
Hasan AA. Formulation and evaluation of dorzolamide hydrochloride-loaded nanoparticles as controlled release drug delivery system. Asian J Pharm. 2012; 6: 67-73.
Hussain A, Samad A, Singh SK, Ahsan MN, Haque MW, Faruk A, Ahmed FJ. Nanoemulsion gel-based topical delivery of an antifungal drug: in vitro activity and in vivo evaluation. Drug Deliv. 2016;23:642-647.
Ramteke KH, Dighe PA, Kharat AR, Patil SV. Mathematical Models of Drug Dissolution: A Review. Sch Acad J Pharm. 2014;3: 388-396.
Lakshmana P, Sharvanan SP, Aravindan S, Bhuvaneswari A, Manikandan V. Nanoemulgel for Transdermal Delivery of Cyclobenzaprine Hydrochloride: Design, Characterization and In-Vitro Studies. Novel Approach Drug Des Dev. 2017;1: 1-6.