Soumyadip Ghosh1,2*, Ankita Basak1
1Department of Pharmaceutics, Bengal School of Technology (A College of Pharmacy),
Delhi Rd, Chinsurah R S, Sugandha, West Bengal 712102, India.
2Department of Pharmaceutics, Calcutta Institute of Pharmaceutical Technology and Allied Health Sciences, Banitabla, Uluberia, Howrah, West Bengal-711316.
*Corresponding Author E-mail: soumyadip.phd@gmail.com
ABSTRACT:
Objective: To deliver Nisoldipine (Nsp) transdermally, new particulate carriers have been prepared, such as stable solid lipid nanoparticles (SLNs) and nanostructured lipid carriers as gel form, using a two-factor, three-level central composite design (CCD). Method: For this experiment, The Nsp-SLNs gel was prepared using carbopol 940.We fabricated SLNs with stearic acid and tween 80 using a modified solvent diffusion method. Results: Particle size, zeta potential, polydispersity index, and in-vitro dissolution studies of the prepared nanoparticles were evaluated for their optimal use. Rat abdominal skin was also investigated for percutaneous permeation of Nsp-SLNs. Analyzing the particle size by photon correlation spectroscopy (PCS)using Malvern Zetasizer, which shows that the Nsp-SLNs are in the range of 75.49±0.63nm to 106.41±0.63nm. The entrapment efficiency (EE%) among all 9 Nsp-SLN formulations fell around 84.14±0.5% and 86.14±0.25%. Conclusion: An in-vitro drug release test was conducted over a period of 12 hours. Formulation F4 showed the optimum result based on the response surface methodology. Nsp-SLNs and Nsp-SLNsgels were successfully formulated using stearic acid and tween 80 was subjected to transdermal use. Nsp-SLNs feature a steady zeta potential window with a monodispersing range, a uniform particle size distribution within the nanoparticle range, and good encapsulation effectiveness. Higuchi and zero-order kinetics were used to predict the in-vitro release of Nsp-SLNs and gels supplemented with stearic acid and tween 80.
KEYWORDS: Solid lipid nanoparticles, Nisoldipine, Transdermalgel, Optimization, Nano-emulsion, Entrapmentefficiency, Experimental design.
INTRODUCTION:
Nisoldipine (Nsp), a calcium channel blocker, is prescribed to treat vascular problems associated to hypertension. Major drawback of Nsp is to the significant first-pass metabolism occurring in the gut wall, it has a limited bioavailability (5%)1. So, there is a need to develop a formulation that can improve bioavailability. In spite of increasing gastrointestinal bioavailability, Nanoparticulate drug delivery systems (NDDS) also regulate or maintain the plasma drug concentrations window2.
The researchers confirmed that lipid-based drug delivery systems (LDDS) increase the bioavailability of lipophilic pharmaceuticals via lymphatic transport. Due to their biocompatible and biodegradable properties in addition to their low toxicities, solid lipid nanoparticles (SLNs) have attracted consideration as carriers for the development of pharmaceuticals since they're poorly water-soluble3. Solid lipid nanoparticles were developed in the first decade of the century to boost bioavailability and target specificity in order to address the issues with colloidal systems such as emulsions, liposomes, and polymer nanoparticles. SLNs consist of substances which are biocompatible as well as biodegradable with average particle sizes in the submicron-sized range over 10nm and 1000nm4. These additionally possess the ability to involve hydrophilic and lipophilic pharmaceuticals for enhanced consistency5. The fact that the framework is comprised up of physiological components, including excipients generally recognized as safe (GRAS) standing for oral and topical administration, decreases the risk of acute and chronic toxicity, and this is an obvious advantage when utilizing lipid particles as drug carrier systems. SLN is generated by substituting out the emulsions' liquid lipids (oil) for a solid lipid, which has many advantages above the oil-based core6. As a highly lipophilic drug (BCS class II), Nisoldipine (Nsp) is an excellent choice to develop lipid-based nanoparticle systems. Particle size, zeta potential, drug loading and entrapment efficiency, in-vitro release of drugs, and ex-vivo permeation experiments utilizing rat abdomen tissue are only a few of the physical and chemical variables the fact that excipients used in the production of SLNs of pharmaceuticals might impact7,8.
In the present study, we employ the response surface approach to develop and optimize the Nsp-SLNs gel. NSP SLNs were created employing the solvent-based diffusion procedure, and a perfect gel formulation was developed. Nsp-SLNs having the appropriate size range of 75.49±0.63nm to 103.9±0.63nm with satisfactory drug loading efficiency were created using a central composite design (CCD). Particle size, zeta potential, polydispersity index, entrapment efficiency, and in-vitro dissolution investigation have been looked at for all 9 formulations. A gel-based nanoparticle formulation (GNps) of Nsp-SLNs was investigated using scanning electron microscopy and ex-vivo permeation.
MATERIALS AND METHODS:
Materials:
Nisoldipine (Nsp) drug was gifted from Aurobindo Pharma, Hyderabad, India. Stearic acid was purchased from the Evonik Rochm pharm polymer, Darmstadt, Germany. Sigma Chemical Corporation Pvt. Ltd. provided Tween 80 and Poloxamer 188. Other than this, all of the chemicals and reagents used in the investigations followed pharmaceutical standards and were of analytical integrity.
Fabrication of Nsp-SLNs using solvent diffusion technique:
Employing the modified solvent diffusion strategy, Nsp-SLNs were formulated using CCD model (32 formulation strategy)9. The composition of different formulations of nanoparticles is presented in Table 1. Stearic acid was transferred to the water bath (Metalab, India) and allowed to melt at above 70°C.Nsp was added to the melted stearic acid under stirring (Lab Stirrer DLHNELP Scientifica, Europe) to dissolve. To the above-melted lipid, Tween 80, Butanol, and distilled water were added dropwise and then allow to be ultrasonicated (Lab Stirrer DLHNELPScientifica, Europe) for 30 minutes to form the Nanoemulsion. Under a mechanical stirrer (Remi RQ-121/D, India) spinning at 4000rpm, 100ml of cold water (2–3⁰C) containing 0.1 percent w/v of Poloxamer 188 was added. The generated SLNs were then centrifuged (12000rpm) (Remi, India) for 30mins. Collected nanoparticles were washed using double distilled water, frozen at -20⁰C in a deep freezer, and freeze-dried in a Lyophilizer (Acumax, Germany).
Fig. 1: Fabrication of Nsp-SLNs using modified solvent diffusion technique
Table 1: Formulation of NSP-SLNs
|
Formulation Codes |
Nisoldipine (mg) |
Stearic Acid (mg) |
Tween 80 (%v/v) |
Butanol (ml) |
Distilledwater (ml) |
|
F1 |
100 |
200 (+1) |
1.0 (0) |
10 |
0.5 |
|
F2 |
100 |
100(-1) |
1.0 (0) |
10 |
0.5 |
|
F3 |
100 |
100(-1) |
1.5 (+1) |
10 |
0.5 |
|
F4 |
100 |
200 (+1) |
1.5 (+1) |
10 |
0.5 |
|
F5 |
100 |
150 (0) |
0.5(-1) |
10 |
0.5 |
|
F6 |
100 |
200 (+1) |
0.5(-1) |
10 |
0.5 |
|
F7 |
100 |
150 (0) |
1.0 (0) |
10 |
0.5 |
|
F8 |
100 |
100(-1) |
0.5(-1) |
10 |
0.5 |
|
F9 |
100 |
150 (0) |
1.5 (+1) |
10 |
0.5 |
Carbopol 940(1.5% w/w), NaCMC (1.0% w/w), and water that was purified were combined to create SLNs transdermal gels, which were then exposed to soaking for 24hours. Following this, the Nsp-SLNs formulation which had been optimized was placed in water and adequately neutralized with triethanolamine (pH 6.5)10. Glycerin was used as a humectant. Until a uniform gel formed, the agitating was being performed continuously.
Experimental Design:
The quantity of stearic acid (X1) and tween 80 (X2) was considered to be two independent variables and was adjusted at three levels, such as low (-1), medium (0), and high (+1). The Nsp-SLNs were tuned for optimal performance using success in a factorial design (two factors and three levels)11. The trial batch was run according to different levels of independent variables that are taken into consideration during the Nsp-SLNs optimization procedure. Entrapment efficiency (%) (Y1), percentage (%) of drug release at 10hours (Y2), and percentage (%) of drug release at 8 hours (Y3) are three separate dependent or response variables. They were taken into account throughout the optimization method. Design Expert 11 trial version was put to use for creating and examining experimental data. Table 2 illustrates the independent and dependent variable designs.
Through the application of a polynomial equation with parameters such as independent factors and interaction with observed responses, which were taken into account in the study, the Nsp-SLNs were determined based on the optimization of independent variables on dependent variables12.
Y=b0 +b1A+b2B+b3AB+ b4A2 + b5 B2
The dependent variable in the current study was Y, the value of the intercept is b0, the coefficients used for regression are b1, b2, b3, and b5, and the response factors are A and B. AB is regarded as an interaction between the A and B variables. The relevance of the models (p<0.05) and individual response parameters was established using one-way ANOVA. Optimum response acceptability was maintained at Entrapment efficiency (%) (Y1), percentage (%) of drug release at 10hours (Y2), and percentage (%) of drug release at 8hours (Y3).
The concentration of free drug in the dispersion medium was measured in order to assess the entrapment efficiency (%) of different formulations of Nsp-SLNs. A 3ml sample of the Nsp-SLNs dispersion was placed into the centrifuge tube, where it was spun at 16000rpm for 30 minutes. Through Whatman filter paper with a pore size range of 0.22nm, the supernatant layer of the nanoparticle dispersion was filtered. The supernatant layer of the aqueous phase was measured using a UV-visible spectrophotometer (1700, Shimadzu, Japan) at a wavelength of 238 nm after washing and dilution14. The equation Entrapment efficiency (%) was used to calculate the entrapment efficiency of Nsp-SLNs15.
Amount of drug used in the formulation – amount of unentrapped drug
EE% = --------------------------------------------------------------------- ×100
Amount of the drug used in the formulation
Fourier transform infrared spectroscopy (Perkin Elmer, America) was used to analyze the drug's interaction with the polymers of Nsp-SLNs. Nisoldipine’s IR absorption peak was measured between 400 and 4000 cm-1. utilizing the KBr disc approach. For the purpose of evaluating purity, the primary peak was reported. The glass transition temperature and any drug-excipient interactions are both determined using DSC (METTLER STAR SW 1500) on samples heated to temperatures between 25°C and 300°C at a rate of 10°C per minute with an average sample weight of 2-4mg. Correctly weighed samples are placed in ordinary aluminum pans. Under liquid nitrous oxide, DSC can be recorded at a 5°C heating and cooling rate. METTLER Software was used to calculate enthalpies16.
Table 2: Experimental methodology of 32 factorial layouts with actual responses for various Nsp-SLNs formulations (coded values in brackets)
|
Formulary Indication |
Factors |
Responsesa |
|||
|
Stearic Acid (mg) (A) |
Tween 80 (%v/v) (B) |
Entrapment efficiency (%) |
Drug release at 10 hrs. (%) |
Drug release at 8hrs. (%) |
|
|
F1 |
200 (+1) |
1.0 (1) |
85.45 |
81.458 |
75.4 |
|
F2 |
100(-1) |
1.0 (1) |
84.14 |
83.043 |
74.14 |
|
F3 |
100(-1) |
1.5 (+1) |
84.35 |
82.25 |
74.35 |
|
F4 |
200(+1) |
1.5 (+1) |
86.14 |
84.628 |
76.14 |
|
F5 |
150 (1) |
0.5(-1) |
84.46 |
83.518 |
74.86 |
|
F6 |
200 (+1) |
0.5(-1) |
84.98 |
83.677 |
74.98 |
|
F7 |
150 (1) |
1.0 (1) |
85.49 |
83.043 |
75.49 |
|
F8 |
100(-1) |
0.5(-1) |
85.00 |
81.933 |
75 |
|
F9 |
150 (1) |
1.5 (+1) |
85.19 |
82.567 |
75.19 |
aMean ± Standard Deviation; n=3.
Scanning electron microscopy can be used to analyze the morphology and size uniformity of Nsp-SLNs. An Optimized batch of Nsp-SLN was air-dried, mounted on a clear glass stub, gold coated, and seen under a scanning electron microscope at a magnification of 1,00,000X16.
The in-vitro study of Nsp-SLNs formulations was evaluated using a dialysis bag with a cut-off range of 12000kda to 15000 kDa (HI-MEDIA, MUMBAI, INDIA) having a pore size of 2.4nm and Nsp-SLNs equivalent to 10ml nanoemulsion was placed into dialysis bag that immersed into 100ml of pH 7.4 with maintaining the temperature of 37°C and mild agitation of 50 rpm under continuous magnetic stirring using teflon coated magnetic beads17-19. In predefined time intervals, aliquots of the release medium (1 ml) were taken out and tested for drug release and sink condition maintenance by adding a new 1 ml of fresh buffer. A UV spectrophotometer (1700, SHIMADZU, JAPAN) was used to measure Nsp-SLNs at 238 nm against a blank, and the cumulative percentage of drug release was computed using the calibration curve that had already been created20.
Numerous kinetic studies, including zero order, first order, Higuchi's model, and Korsmeyer-Peppas model, were carried out to ascertain the manner and mechanism of Nsp-SLNs release from various formulations21-23.
Ex-vivo permeation study:
The optimized formulation was tested for permeation ex-vivo using Franz's diffusion cell, which has a 3.14 cm2 diffusion area. This research used rat abdominal skin for the permeation24,25. The receptor compartment was pointed towards the dermis, whereas the donor compartment was pointed towards the stratum corneum of the excised rat skin26. In the donor compartment, Nsp-SLNs gels were applied to the skin's surface, and the receptor compartment received 20mL of medium27.
On the receptor side of the experiment, Teflon-coated magnetic beads were used to stir the solution at 100rpm while maintaining it at 37±0.5°C. At predefined intervals (1, 2, 3, and 10 hours) following injection of the test formulation on the donor side, 1 mL of samples were obtained from the receiver compartment28-30. Then, to maintain steady-state concentration, an equivalent volume of receptor fluid was delivered into the receiver compartment right after each sample was collected. Using a UV-Visible spectrophotometer with a maximum wavelength of 238 nm, this study assessed the amount of NSP-SLNs gel in receptor fluids31-33.
RESULTS:
Formulation Optimization:
The 2FI model is used to identify how to analyze individual primary components and interaction factors utilizing the design expert programme (Design Expert 11, State Ease Inc., USA). 32 full-factorial designs were used to optimize the various examined responses, each of which is represented by a quadratic equation as follows. Stearic acid (X1) and tween 80 (X2) were utilized as independent variables in this full factorial design based on responses from multiple trial batches and changed at three different levels: low (-1), medium (0), and high (+1). Entrapment efficiency (%) (Y1), percentage (%) drug release at 10 hours (Y2), and percentage (%) drug release at 8 hours (Y3) are the three separate response variables. The 2FI model was used to identify how to analyze individual primary components and interaction factors using the design expert software (Design Expert 11, Stat Ease Inc., USA). Using a 2FI equation, the various explored responses are indicated as follows.
Table 3: ANOVA summary for the response surface 2F1 model of Entrapment efficiency (%) (Y1), Percentage of drug release at 10 hrs. (Y2), and percentage (%) drug release at 8 hours (Y3).
ANOVA for 2FI model |
||||||
|
Response1:Entrapment efficiency |
||||||
|
Source |
Sum of Squares |
df |
Mean Square |
F-value |
p-value |
|
|
Model |
3.82 |
3 |
1.27 |
15.74 |
0.0056 |
significant |
|
A-Drug: Polymer |
0.9425 |
1 |
0.9425 |
11.66 |
0.0190 |
|
|
B-Surfactant CONC (TWEEN80) |
0.1048 |
1 |
0.1048 |
1.30 |
0.3065 |
|
|
AB |
2.77 |
1 |
2.77 |
34.27 |
0.0021 |
|
|
Residual |
0.4043 |
5 |
0.0809 |
|
|
|
|
CorTotal |
4.22 |
8 |
|
|
|
|
|
Response2:% Drug release 10 hours |
||||||
|
Model |
2.66 |
3 |
0.8855 |
7.75 |
0.0251 |
significant |
|
A-DRUG: Polymer |
1.58 |
1 |
1.58 |
13.83 |
0.0137 |
|
|
B-Surfactant Conc (Tween 80) |
0.2563 |
1 |
0.2563 |
2.24 |
0.1946 |
|
|
AB |
0.8190 |
1 |
0.8190 |
7.16 |
0.0440 |
|
|
Residual |
0.5716 |
5 |
0.1143 |
|
|
|
|
Cor Total |
3.23 |
8 |
|
|
|
|
|
Response 3:%Drug release at 8 hours |
||||||
|
Model |
2.47 |
3 |
0.8223 |
9.85 |
0.0154 |
significant |
|
A-Drug:Polymer |
1.53 |
1 |
1.53 |
18.32 |
0.0079 |
|
|
B-Surfactant CONC(Tween80) |
0.1176 |
1 |
0.1176 |
1.41 |
0.2886 |
|
|
AB |
0.8190 |
1 |
0.8190 |
9.81 |
0.0259 |
AB |
|
Residual |
0.4175 |
5 |
0.0835 |
|
|
|
|
CorTotal |
2.88 |
8 |
|
|
|
|
According to the equation above, a high correlation coefficient value indicates that the experiment's components and the analyzed responses are closely related. According to the ANOVA result, both of the factors—stearic acid (X1) and tween 80 (X2)—had a significant effect on drug entrapment efficiency (%) (Y1), percentage (%) drug release at 10hours (Y2), and percentage (%) drug release at 8hours (Y3), with a p-value of 0.05 or below. The 2F1 model's simplicity was seen as a key concept. Figure 2 presents linear correlation plots of the actual and predicted results with the corresponding residual plots of the entrapment efficiency (%) (Y1), percentage (%) drug release at 10 hours (Y2), and percentage (%) drug release at 8 hours (Y3). Corresponding residual plots display a scatter between the residual vs. predicted value of the entrapment efficiency (%) (Y1), percentage (%) drug release at 10hours (Y2), and percentage (%) drug release at 8 hours (Y3).
In Table 4, the particle size of several Nsp-SLN formulations was displayed. The range of Nsp-SLNs' particle size was discovered to be between 75.49± 0.63 and 106.41± 0.63 nanometers (nm). In addition to having a restricted size distribution, Nsp-SLNs differed significantly from drug-free nanoparticles containing Nsp in terms of their distribution34.
Figure 2: A) An analysis of % Entrapment efficiency between actual and predicted values is illustrated in this linear correlation plot. B) Comparison of the actual and predicted release of % of drug at 10 hours shown in a linear correlation plot. C) A linear correlation plot is shown between the actual and predicted percentage of drug released at 8 hours. D) Contour plot demonstrating stearic acid [x1] and tween 80 [x2] affect the percentage of entrapment efficiency. E) Response Surface plot demonstrating the impact of the stearic acid [x1] /tween 80 [x2] ratio on the formulation's entrapment efficiency. F) Contour plot demonstrating stearic acid [x1] and tween 80 [x2] affect the percentage of drug released at 10 hours. G) Response Surface plot demonstrating the impact of the stearic acid [x1] /tween 80 [x2] ratio on the % drug release at 10 hours. H) Contour plot demonstrating stearic acid [x1] and tween 80 [x2] affect the percentage of drug released at 8 hours. I) Response Surface plot illustrating the impact of the stearic.
Table 4: Particle sizesand PDIvalue of F1-F9 formulation
|
Formulation Code |
Particle Size (nm) |
PDI |
Entrapment Efficiency(EE%) |
ZetaPotential |
|
F1 |
103.9± 0.63 |
0.2±0.02 |
85.45 ± 0.5 |
-8.35±0.5 |
|
F2 |
90.6± 0.63 |
0.5±0.02 |
84.14± 0.5 |
-9.58±0.5 |
|
F3 |
106.4± 0.63 |
0.3±0.02 |
84.35± 0.5 |
-8.86±0.5 |
|
F4 |
75.49± 0.63 |
0.3±0.02 |
86.14± 0.5 |
-10.8 ± 0.5 |
|
F5 |
81.25± 0.63 |
0.4±0.02 |
84.46± 0.5 |
-6.96±0.5 |
|
F6 |
78.24± 0.63 |
0.3±0.02 |
84.98± 0.5 |
-6.38±0.5 |
|
F7 |
86.24± 0.63 |
0.2±0.02 |
85.49± 0.5 |
-8.45±0.5 |
|
F8 |
106.41±0.63 |
0.4±0.02 |
85± 0.5 |
-9.45±0.5 |
|
F9 |
92.14± 0.63 |
0.3±0.02 |
85.19± 0.5 |
-9.79±0.5 |
Figure 3: A) Bar diagrammatic representation of particle size (nm) of Nsp-SLNs. B) Bar diagrammatic representation of entrapment efficiency (EE%)of Nsp-SLNs (n=6). C) Bar diagrammatic representation of zeta potential (mv) of Nsp-SLNs(n=6)
Figure 4: The Nsp-SLN formulations F1 - F9 have particle sizes that vary from 75.49 ± 0.63 nanometers to 106.41 ± 0.63 nanometers, with F4 having the smallest particle size at 75.49 ± 0.63 nanometers.
Figure 5: Nsp-SLN formulation F1-F9 zeta potential from -18.0±0.14 mv to -21.1±0.11 mv
The entrapment efficiency or drug loading efficiency (%) (Y1) of various formulations of Nsp-SLNs was presented in Table 4. The entrapment efficiency of Nsp-SLNs was found within the range of 84.14±0.5% to 86.14±0.25%. As stearic acid (X1) and tween 80 (X2) impacted the amount of the drug entrapped in the formulation, entrapment efficiency (Y1) was significantly enhanced (p<0.05).
Zeta Potential:
Table 4 details the zeta potential of several Nsp-SLN formulations. The produced nanoparticles possessed sufficient charge at their surface, preventing exhibition owing to electric repulsion, as indicated by the zeta potential of Nsp-SLNs being found in the range of -10.8±0.5mv to -8.35± 0.5mv.
FTIR Spectroscopy and DSC:
Figure 6depicts the FT-IR spectra of Nsp-SLNs, Pure Drug, and Drug with Polymers. In FT-IR, Nsp's many vibrational peaks were seen. At 3432 cm-1, 1782 cm-1, 1635 cm-1, and 720 cm, respectively, the NH stretching of alkanes, the C-O stretching vibration, the N-H plane bonding vibrations, and the C=O stretching were all observed35.Peaks were seen at 3375.49 cm-1, 1772.61 cm-1, 1684.85 cm-1, and 707.89 cm-1 with the drug (Nsp) and polymers mixture (Stearic acid and tween 80).
Figure 6: A) FT-IRspectrum of pure drug(Nsp) and B) FT-IRspectrumofNspandpolymers
Figure 7. A) The rmogram analysis of pure drug (Nsp) and B) The rmogram analysis of pure drug (Nsp) and polymers
Figure 8 from the analysis of the SEM image illustrates the morphological properties of the nanoparticles. The topographical study confirmed that particles of nanoformulation were smooth surfaces with spherical in nature.
Figure 8: Nsp-SLNslyophilized powderunder SEM at 1,00,000 Xmagnification
In-vitro Release Study:
Figure 9 mentions the in-vitro profile of several Nsp-SLN formulations. Due to their tiny particle size and high surface area, Nsp-SLNs exhibit a significantly improved in-vitro release profile (p<0.05). Formulation F4 was deemed an optimized formulation based on the comments mentioned above. The targeted answers were limited to entrapment efficiency (%) of 86.14%, drug release at 10 hours of 84.62%, and drug release at 8 hours of 76.14%.
The Nsp-SLNs formulation's in-vitro release data were fitted into a number of kinetic equations, and the correlation coefficient (R2) value was computed using a number of kinetics models. The correlation coefficient (R2) value was used to derive the release mechanism, which is shown in Table 5. The highest R2 value and n exponent imply that the release pattern of Nsp-SLNs followed zero-order kinetics as well as the Korsmeyer-Peppas model.
Table 5: A regression coefficient (R2) for the Nsp-SLNs and Optimum formulation of Nsp-SLNs gel
|
Formulation No |
Zero-orderkinetics (R2) |
First-orderkinetics (R2) |
Higuchiplot (R2) |
Korsmeyer peppasmodel (R2) |
Korsmeyer Peppasmodel (nvalue) |
|
F1 |
0.9673 |
0.8424 |
0.9502 |
0.9524 |
1.1515 |
|
F2 |
0.9716 |
0.8324 |
0.9586 |
0.9531 |
1.1404 |
|
F3 |
0.9634 |
0.8468 |
0.9514 |
0.9242 |
1.1473 |
|
F4 |
0.9735 |
0.8518 |
0.9646 |
0.9621 |
1.1122 |
|
F5 |
0.9346 |
0.8354 |
0.9571 |
0.9674 |
1.1479 |
|
F6 |
0.9654 |
0.8125 |
0.9535 |
0.9452 |
1.1467 |
|
F7 |
0.9666 |
0.8298 |
0.9568 |
0.9398 |
1.1223 |
|
F8 |
0.9688 |
0.8334 |
0.9559 |
0.9271 |
1.1318 |
|
F9 |
0.9648 |
0.8229 |
0.9551 |
0.9115 |
1.1418 |
|
Nsp-SLNsgel (F4) |
0.9769 |
0.8411 |
0.9621 |
0.9766 |
0.6984 |
Figure 9 A) Percentage of drug release of Nsp-SLNs(F1-F9). B) The kinetics of Nsp-SLNs in the zero-order regime (F1-F9). C) First-orderkinetics of Nsp-SLNs (F1-F9). D) Korsmeyer’s Peppasmodel Nsp-SLNs(F1-F9). E HiguchiPlot of Nsp-SLNs(F1-F9)
3.9 Ex-vivo permeation study:
Figure 10 depicts the ex-vivo skin penetration of the Nsp-SLNs formulation (F4), Nsp-SLNs gels, and medication solutions. When plotted against time, the amount of drug that permeated through the rat abdominal skin per square centimeter of the effective diffusional area appears to follow Higuchi's equation (R2 =0.950 to 0.961) and zero-order kinetics, as shown by correlation coefficients (0.9796 to 0.9897).
Figure 10: Percentage of drug release of Nsp-SLNsandNsp-SLNsgel of optimizedformulationF4.
DISCUSSION:
The 32 full-factorial designs were used to optimize the Nsp-SLNs. The ratio of stearic acid and tween 80 was utilized in this full factorial design as a independent variable based on responses from multiple trial batches and altered at three different levels: low (-1), medium (0), and high (+1). Entrapment efficiency (%) (Y1), percentage (%) of drug release at 10 hours (Y2), and percentage (%) of drug loading at 8 hours are the three separate response variables. (Y3). Three-dimensional response surface plots and two-dimensional contour plots were used to explain how both independent variables (stearic acid and tween 80) affect dependent variables such as entrapment efficiency (%) (Y1), percentage (%) drug release at 10 hours (Y2), and percentage (%) drug release at 8 hours (Y3). The results show that non-linearity decreased the entrapment efficiency with increasing independent variables of tween. According to the response surface plot, stearic acid (X1) had a greater impact on entrapment efficiency (%) (Y1) than tween 80 (X2) did. The reaction surface plot further supports the observation that the stearic acid strip-linear curve for tween 80 (X2) was nearly flattened.
The contour plot (Figure 2) of entrapment efficiency (%) (Y1), factors X1 (stearic acid), and X2 (tween 80), revealed that linearity increased with an increase in the ratio of stearic acid (X1) and tween 80 (X2) at the low level of (-1) of tween 80 (X2), and the drug release was significantly increased (p<0.05) when X1 increased from -1 level to +1 level. The response surface plot for entrapment efficiency (%) (Y1) showed that stearic acid (X1) and tween 80 (X2), which were both taken into account as X1 and X2, had a minor linear curvature that affects entrapment efficiency (%) (Y1).The contour plot (Figure 2) of the percentage (%) of drug release at 10 hours (Y2) versus independent factors shows that the linearity of drug release rises with both independent variables. These independent factors include the ratio of stearic acid (X1) and tween 80 (X2). Another way to put it is that an increase in stearic acid (X1) in comparison to tween 80 (X2) was identified with a non-linear small increase of medication release at 10 hours. at the apex (+1) and the trough (-1). The percentage of drug release at 8 hours was significantly (p<0.05) increased as tween 80 (X2) increased from low level (-1) to high (+1). The results of the response surface plot of drug release showed that greater curvature toward the ratio of stearic acid (X1) and flattening of the curve toward tween 80 (X2) as both independent variables impact the release rate.
Low solubility and poor lipophilicity are the causes of Nsp-SLNs' ineffective encapsulation, and it has been found that nanoparticles improve drug loading efficiency, decrease drug leakage, and shorten the time that pharmaceuticals spend at target locations36.Due to electrostatic repulsion between the particles, nanoparticles often have a zeta potential range of less than 30 mv, which results in less coalescence and more stable nanoparticles37. The importance of the zeta potential value suggests that the synthesized Nsp-SLNs have less coalescence and are more stable nanoparticles38.The two-graph of stretching vibrational peaks that were in perfect agreement with one another demonstrated that the drug sample utilized was pure and stable, and no interactions between the drug (Nisoldipine) and the polymers (stearic acid and tween 80) were observed.
Nanoparticles are uniformly smooth and spherical in shape, and the particle size determined by the particle size analysis was also acceptable39. In addition, the release rate was significantly influenced by the polymers stearic acid and tween 80 as well as surfactant. According to the data analysis, the 200 mg of stearic acid and 1.5% w/v of tween 80 in the F4 formulation were released at a rate of 86.66% after 12 hours. By delivering Nsp-SLNs to the target site for a longer period of time, this evidence suggests that treatment efficacy may be improved.
The combination was optimized for the independent and dependent variable’s respective polynomial equations in order to obtain a formulation with the required results40. The formulation comprising 200 mg of stearic acid and a 1.5% w/v concentration of tween 80 was determined to contain the maximum desirable requirements after a thorough examination of the feasibility search and subsequent grid search. Entrapment efficiency, percent drug release after 10 hours, and percent drug release after 8 hours have extremely similar predicted and observed values.The Nsp-SLNs gel showed the highest percentage release of drug permeation in 12 hours (68.10%).
Lipid nanoparticles have become an attractive nano-platform for a variety of drug deliveryapplications.Nsp-SLNs and Nsp-SLNs gels were successfully formulated using stearic acid and tween 80 was subjected to transdermal use.Nsp-SLNs feature a steady zeta potential window with a monodispersing range, a uniform particle size distribution within the nanoparticle range, and good encapsulation effectiveness. Higuchi and zero-order kinetics were used to predict the in-vitro release of Nsp-SLNs and gels supplemented with stearic acid and tween 80. Nsp-SLNs showed a sustained drug release over a period of 12hrs.The Nsp-SLNs gel in its optimized formulations is a viable alternative drug delivery system.
CONFLICT OF INTEREST:
The authors have no conflict of interest regarding this investigation.
ABBREVIATIONS:
Nsp: Nisoldipine; SLNs: Solid lipid nanoparticles; FTIR: Fourier transform infrared spectroscopy; DSC: Differential scanning colorimeter; EE: Entrapment Efficiency; %DR: Percentage of drug release; SEM: Scanning electron microscopy; NDDS: Nanoparticulate drug delivery systems; CCD: Central Composite Design; GNps: Gel-based nanoparticle formulation; PDI: polydispersity index.
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Received on 15.08.2023 Modified on 04.10.2023
Accepted on 11.12.2023 © RJPT All right reserved
Research J. Pharm. and Tech 2024; 17(5):2327-2338.
DOI: 10.52711/0974-360X.2024.00365