INTRODUCTION:

Early in the 1990s, SLNs were developed to replace the existing conventional carrier systems, which include polymeric nanoparticles, emulsion, and liposomes.¹ SLNs are a new category of nanoparticulate drug carrier that is gaining popularity. It has small lipid vesicles in the nanometer range and has the benefits of other colloidal carries while avoiding their drawback.² SLNs are a novel drug carrier that enables targeted and controlled drug delivery by different routes of administration. These are physiologically stable particles with a size range between 1-1000 nm.³ It offers various benefits, including enhanced drug stability and compatibility for the hydrophobic and lipophilic active ingredients.⁴ Because there are no solvents used during the manufacturing process and the excipient is reasonably inexpensive, SLNs are less hazardous than polymeric nanoparticles. The major advantage of SLNs is the production potential on an industrial scale.

Every year, around 2-3 million people suffer from pulmonary arterial hypertension (PAH), a condition that can lead to death.⁵ Vascular growths in the small pulmonary arteries is a characteristic of this condition. Right ventricular failure and mortality result from an increase in pulmonary vascular resistance.⁶ A lack of breath, chest discomfort, syncope, exhaustion, and peripheral edema are symptoms of PAH that primarily affect women rather than men.⁷ Endothelin (ET-1), a strong endogenous blood vessel constrictor in lung tissue and plasma, is abundant in patients with PAH.⁸ Vascular endothelial cells are the primary manufacturers of endothelin. The primary way that endothelin works is by activating the ET-A and ET-B endothelin receptors.⁹ Endothelin decreases the diameter of the pulmonary artery lumen because it mainly acts on the ET-A receptor. This causes a rise in pulmonary vascular resistance, a decrease in vascular bed responsiveness, and finally an increase in pulmonary arterial hypertension.¹⁰

Epoprostenol was the first active moiety to exhibit this mode of action. Epoprostenol use was restricted due to its serious side effects. Treprostinil, iloprost, and beraprost were then found to be effective in treating PAH disease. Clinical usage of tadalafil and sildenafil was restricted. Although it necessitates critical care, inhaled nitric oxide (NO) is another possible treatment for PAH¹¹. Since 2000, bosentan has been authorized for the treatment of functional classification III/IV PAH in both North America and Europe. In 2000, intravenous prostanoids or calcium channel blockers were the only approved treatments for PAH.¹² Bosentan (Tracleer^®) was the first orally administered drug that has dual endothelin receptor antagonistic activity. The mechanism of action of bosentan was by blocking the endothelia molecule.¹³

Both 125 mg and 62.5 mg tablets of bosentan have a 50% oral bioavailability. The cytochrome P450 isoenzymes CYP2C9 and CYP3A4 metabolize it in the liver after it is mainly absorbed through the GIT. The majority of an oral dosage is eliminated through the biliary system, with less than 3% of it being retrieved in urine. Bosentan has a half-life of 5 -8 h and is poorly soluble drug with a solubility 1.0 mg/100 mL in water and; 0.1 mg/100 mL and 0.2 mg/100 mL in aqueous solution of pH 1.1 - 4.0 and pH 5.0, respectively. Its solubility increases with an increase in pH, for example at pH 7.5 it becomes 43 mg/100 mL. The primary cause of bosentan poor absorption and limited bioavailability is its poor solubility.¹²

The objective of the current study is to develop and evaluate bosentan-loaded solid lipid nanoparticles utilizing the micro-emulsion process with varying concentrations of lipid and surfactants. Additionally, 32 randomized full factorial design was used to examine the primary impact of independent factors, such as mean particle size (MPS), polydispersity index (PDI), entrapment efficiency (%EE), and zeta potential (ZP), on the physicochemical characteristics of prepared bosentan loaded SLNs. Additionally, solid-state characterization and in-vitro release were investigated, along with stability experiments at room temperature and chilled temperature for the lyophilized powder of the optimized formulation.

MATERIALS AND METHODS:

Materials:

Bosentan was gift sample provided by Mega Fine Pharma Pvt. Ltd, Mumbai. The solid lipid used for preparation was glyceryl monostearate (GMS) (m. p. 54 °C – 60 °C). All other chemicals were purchased from Loba Chemie Pvt. LTD. Mumbai, including the co-surfactant propylene glycol and the surfactant tween 80. Additionally, every reagent used was of analytical quality.

Methods:

Saturated solubility study: By collecting 5 mL of each solvent in vials, the saturation solubility of bosentan was investigated in distilled water, methanol, phosphate buffer (pH 6.8), and acetonitrile. Bosentan was added in excess to each vial, and the vial was sealed with a stopper. After vortexing this solution for 10 minutes and sonicating it for 15 to 20 minutes, the vials were placed in an orbital shaker incubator set at 50 rpm for 48 hours, with the temperature kept at 37±0.5 ºC. These vials were then centrifuged at 8000 rpm, and using the same solvent, the drug's absorbance was measured using a UV Visible spectrophotometer.¹⁴

Selection of lipid: Based on the drug's highest solubility in the lipid, the lipid was chosen for the SLN synthesis. The solubility of bosentan was assessed in a range of lipids, including palmitic acid, stearic acid, Lauric acid, and GMS. Accurately weighed 10 mg bosentan was added to 10 mg of melted lipid, while being constantly stirred. Additional lipid was added in increments while being constantly stirred and heated until a clear solution was obtained. The total amount of lipid used to obtain a clear solution was noted.¹⁵

Selection of surfactant and co-surfactant: HLB values are critical factors to consider in the selection of surfactants and co-surfactants. The HLB value must be maintained within the range of 8 to 13 to facilitate the formation of an oil-in-water micro-emulsion.¹⁶ Surfactants and co-surfactants exhibiting values between 8 and 15 were selected for the pseudo-ternary phase diagram.

Construction of Phase Diagram: Solubility studies of bosentan were carried out in lipids namely; GMS, stearic acid, lauric acid, and palmitic acid, surfactants namely; Tween 80, Span 80, Tween 20, span 20 and co-surfactants namely; propylene glycol, polyethylene glycol 400, polyethylene glycol 200. The water titration method was employed with different ratios of tween 80-propylene glycol (1:1, 2:1, 3:1, 4:1) to generate pseudo ternary phase diagrams utilizing Chemix School software.¹⁷

Preparation of bosentan-loaded solid lipid nanoparticles: Solid lipid nanoparticles are made using the microemulsion process, which was created by Gasco and associates and is based on the dilution of the microemulsion. Lipid (GMS) was melted at a temperature higher than 5 °C, and the drug was dissolved in the melted lipid. Propylene glycol (co-surfactant) and tween 80 (surfactant) was heated separately to the same temperature. The lipid phase was gently agitated at 2000 rpm while an aqueous phase containing S_mix [Tween 80 (2): Propylene Glycol (1)] was added drop by drop to create an opaque microemulsion. The warm o/w microemulsion was mechanically agitated at a 1:10 ratio (microemulsion: cold water v/v) while being dispersed in cold water (2–3 °C) to create a colloidal milk suspension of SLN.

For lyophilization of bosentan-loaded SLN, a cryoprotectant D-Trehalose (5% w/w) was added in the SLN dispersion. The composition was frozen at -50 °C in a deep freezer of temperature capacity of -80 °C before being placed in a Labconco lyophilizer for 48 h. The primary freeze drying of the frozen compositions was carried for 48 h and the secondary drying at 20 °C for 6 h. The dried compositions in vials were vacuum sealed and stored in refrigerator between 2 - 8 °C.¹⁸

Design of Experiment and Statistical Analysis:

The design of experiment (DOE) approach was used to optimize the ideal composition utilizing the microemulsion technique and investigate mathematical correlation between factors and parameters. In all, nine possible bosentan-SLN formulation batches were made. Primary optimization was carried out to investigate the effects of process factors, such as lipid concentration, surfactant concentration, and magnetic stirring time. The primary effects and interactions of independent factors on the physicochemical properties of the resultant bosentan-SLNs were investigated using 3² randomized full factorial design. Optimization of bosentan-SLN dispersion using three levels and two variables with 3² full factorial designs was the appropriate condition for SLN preparation. The key process parameters (independent variables) chosen for this design were the lipid concentration (Z₁), which has three levels (200, 250, and 300 mg), and the surfactant concentration (Z₂), which has three levels (0.35%, 37.5%, and 40% w/w). To examine their impact on particle size and entrapment efficiency, two answers were selected. Two responses were chosen in order to investigate their effects on particle size and entrapment efficiency. (Table-1)

To better understand the results based on the size of the coefficients and additional positive (synergistic impact) or negative sign, a comprehensive polynomial regression equation was developed as follows.

Y = b₀ + b₁Z₁ + b₂ Z₂ + b₃ Z₁Z₂ + b₄ Z₁² + b₅ Z₂²… (1)

Where, b₁ to b₅ represent coefficients derived from the directly observed values of Y, and b₀ is an intercept representing the arithmetic average of the quantitative result of nine trials. In addition, A and B are the coded values of independent variables. The interaction term AB shows that the response parameters have changed when two factors change simultaneously. When one component changes at a time from a low value to a high value, the major effects, Z₁ and Z₂, indicate the mean result. The non-linearity of the model was further assessed using the polynomial terms, Z₁₂ and Z₂₂.

ANOVA (Design Expert 13 [Stat-Ease, Minneapolis, MN, USA]) was used to assess the model's statistical significance. Surface-response plots and contour plots were analyzed by keeping each element at its low, medium, and high values while changing the other elements along the study's range.¹⁸

Characterization of Bosentan loaded SLN:

The results of critical quality attributes (CQAs) for each of the nine batches of bosentan-loaded SLNs were recorded after they were analysed for particle size, entrapment efficiency, and zeta potential. Polynomial coded equations were used to qualify the impact of CQAs on zeta potential and %EE.

Particle Size: Particle size and polydispersity values of all freshly prepared batches were measured using the Zetasizer (Horiba Scientifics SZ-100 using quartz cuvette cell 4 apertures) after a 1:10 dilution with double-distilled water.¹⁹

Zeta potential: Zeta potential measurement is required for determining the stability of the SLN dispersion. The Zetasizer was used to determine the zeta potential of the prepared SLN dispersion.²⁰

Entrapment Efficiency: The bosentan-loaded SLN-dispersion (100 mL) become acidic (pH 1.2) with addition of 0.1 mol/L of HCl, which led to the SLN aggregating. Centrifugation was used to separate the solution for 30 min at 5000 rpm. A UV spectrophotometer was used to detect the absorbance at 273 nm after 1 mL of the supernatant was diluted with 10 mL of water. The following formulas were used to calculate the entrapment efficiency.²⁰

Initial amount of drug –amount of free drugs

EE% = ---------------------------------------------------x 100

Initial amount of drug … (2)

Evaluation of Optimized of Bosentan Loaded SLN

Solubility study:

The shake flask method was used to determine the solubility of Bosentan monohydrate-loaded solid lipid nanoparticles in the distilled water at room temperature. The Bosentan monohydrate loaded solid lipid nanoparticle solubility was analysed in distilled water. Every 3 vials containing 5mL of distilled water had an excessive quantity of the optimized batch powder. Second, these dispersions were kept in an orbital shaking incubator at a rate of 20 rpm for 48 h at a temperature of 37 ±0.5 °C. After reaching equilibrium, the samples were centrifuged in a chilled micro centrifuge for 15 minutes at 5000 rpm. A UV visible spectrophotometer was then used to measure absorbance at λ_max 273 nm after 1 mL of the centrifuged samples' supernatant was removed and diluted to the appropriate dilution using the specific solvent.¹⁴

Transmission electron microscopy analysis

The TEM (JEM-2000 EX II, JEOL. Philips, LTD., Tokyo, Japan) was used for morphological analysis of the suspended F6-bosentan loaded SLN. After a 1:20 dilution with ultra-pure water, it was operated at 80 kV and sonicated for 10 minutes in an ultrasonic bath. A single drop of the diluted sample was applied on a copper grid coated with carbon, and left to dry for five minutes at room temperature. Lastly, pictures taken with soft imaging viewer software were examined.²¹

Scanning electron microscopy analysis

Using SEM (JEOL JSM-6390LV, Japan) surface morphology, shape, and homogeneity of an optimized batch of bosentan-loaded SLN were examined. Prior to evaluation using a direct-current sputter coater, the formulation was mounted with gold under low vacuum to ensure the particles' superficial electro-conductivity.²¹

Fourier-transform infrared spectroscopy analysis

FTIR spectroscopy (Jasco V530 spectrometer) was used to evaluate bosentan, a physical mixture of bosentan and GMS, and an optimized batch of bosentan SLN. Potassium bromide was mixed with a small quantity of sample (2 mg) and the resultant material was combined to prepare a pellet that was scanned between 3000 and 400 cm^-1 using FTIR.²⁰

Differential scanning calorimetric analysis

DSC analysis was performed to verify the drug's composition and purity and to optimize the batch.²² In standard aluminium pans (Shimadzu DSC 50, Tokyo, Japan), about 10 mg samples of each drug and optimized formulation were heated at a steady rate of 10 °C/min over a temperature range of 20 °C to 300 °C. The inert atmosphere was maintained by purging nitrogen at a rate of 25 mL/min.

X-ray diffraction analysis

XRD analysis was used to look into any changes in the sample's crystalline nature before and after formulation using X-ray diffractometer (Bruker, Germany). XRD of pure drug and optimized formulation were obtained and analysed. The 2 °θ was measured using a diffractometer in the 4 - 400 range with a repeatability of 0.001. Using a rate meter with a time constant of 2102 pulses per second and a scanning speed of 2 min, the XRPD pattern was automatically collected and analysed.^23-25

In-vitro drug release study

Bosentan-loaded SLN formulations were investigated for in vitro drug release over a 12 h period in PBS pH 6.8 using cellulose membrane dialysis sacks (Sigma, USA) with a specific capacity of 60 ml/feet, an approximate flat width of 2.5 mm, as well as a diameter of 16 mm. A molecular weight of 12,000 g/mole was the cut-off. Both ends of the tube containing SLN dispersion were securely sealed and transferred to the dialysis bag. The dialysis bag was hold in a beaker containing 100 mL PBS (pH 6.8) with magnetic stirring at 100 rpm. Sink condition was ensured by completely replacing the dissolving media with equal volumes of fresh media following each sampling. At specified time intervals ranging from 1 to 12 h, samples were collected and spectrophotometrically examined using a Jasco V650 UV visible spectrophotometer at 273 nm ^25-26.

Stability study

In order to investigate the physical changes in the optimized formulation caused by the short-term stability, such as particle size, a stability study of the bosentan loaded SLN was conducted. The optimized formulation was subjected to short term accelerated stability study as per ICH guidelines for a span of 3 months. The samples were stored in a stability chamber at 25 ±2 ºC and at 60 ± 5% RH. At the end of 3 months the formulation was tested for particle size.²¹

RESULT AND DISCUSSION:

Selection of Solid Lipid, Surfactant and Co-Surfactant:

A variety of solid lipids were investigated before using them in formulating SLN. The greatest solubility of the drug in a particular lipid was taken into consideration when selecting it. It was noted how much lipid was utilized overall to solubilize the 10 mg of bosentan. This led to the selection of GMS as the lipid base for SLN production. For the selection of surfactant and co-surfactant HLB values plays an important role. Individual and combination trial of the surfactant system were made and analysed. For SLN preparation the emulsifier tween 80 and co-emulsifier propylene glycol were used possessing an HLB value of 15 and 13.4, respectively, which is required for stable o/w system.

Development of Pseudo Ternary Phase Diagram:

Tween 80 is chosen as the emulsifier and propylene glycol as the co-emulsifier based on HLB values, while the GMS is chosen based on the drug's solubility in a solid lipid. Five various potential combinations of emulsifier mixture to lipid at Km values 1, 2, 3, 4 and 5 were utilized for the phase diagram construction, Fig. 1. No distinct shifting of w/o to o/w was observed. The outer layer of o/w microemulsion was analysed in each phase diagram construction. (Figure-1)

Optimization of Bosentan loaded SLN using factorial design:

In the process of optimization of the batch, we decided to observe effect of various ratios of S_mix and lipid on the particle size and entrapment efficiency. In order to optimize the best formulation, we used the design expert application to get the statistical estimation of the dependent variables. For the optimization of the formulation, a 3² level factorial design was employed, Table 2. In the current investigation, a 3² full factorial layouts were implicated to evaluate how often the proportion of S_mix and lipid influences the formulation particle size and entrapment efficiency. The quantities of S_mix (Z₁) and lipid (Z₂) were selected as independent variables. Using a three-level factorial design, each factor is monitored at three distinct levels and the experiments were carried out by employing all 9 possible pairings. The three-level complete factorial design findings were addressed using the following equation.

Y= b₀+ b₁Z₁+ b₂Z₂+ b₁₂Z₁Z₂+ b₁₁(Z₁)²+ b₂₂(Z₂)² … (3)

Where, Y represent dependent element, b0 denotes average response of the 9 runs, and b1 and b2 are estimated coefficient for Z₁ and Z, the combined term Z₁Z₂ shows how responses alter when 2 factors changed significantly. For nonlinearity study the Z₁²and Z₂² were incorporated.

Table 2. Complete factorial design batches with result of PS and EE%

Formulation code	S_mix	Lipid	PS (nm)	EE (%)
SLN 1	35	2	138.6	89.76
SLN 2	35	2.5	113.4	95.36
SLN 3	35	3	112.5	95.21
SLN 4	37.5	2	137.8	89.39
SLN 5	37.5	2.5	113.4	95.36
SLN 6	37.5	3	109.1	96.26
SLN 7	40	2	178.4	68.87
SLN 8	40	2.5	173.6	83.09
SLN 9	40	3	172.1	83.05

Effect of formulation variables on particle size (Z₁)

A response surface plot and contour plot presented as Fig. 2 displays the relationship between the independent variable and the dependent variable Z1 (particle size). The results indicate that the generated SLNs particle size of all formulations ranged from 109 to 198 nm. The correlation coefficient (R²) for particle size was 0.9883, indicating model is a strong fit, and the model is significant. A polynomial equation based on the data is produced after accounting for the coefficient value and mathematical sign; this equation could be utilized to formulate a hypothesis.

Z₁ = +115.87 + 25.80Z₁- 10.18Z₂+ 4.95Z₁Z₂+ 28.80(Z₁)²+ 6.35(Z₂)² … (4)

A good fit model between the dependent and independent variables is denoted by a high value of R². The observed model shows a p-value ˂0.0500 which is significant, and the model F-value was found to be 50.55 which shows that the model is significant, in addition to that the predicted R² and adjusted were in good relation, with a difference between them is observed to be ˂0.2, which demonstrate that the selected model gives the best fit for the data. The statistical analysis of the data and the surface plot graphs demonstrated that particle size is significantly influenced by the ratio of S_mix to lipid employed in formulation preparation. It has also been noted that particle size increases in parallel with the fraction of lipid and S_mix.

Effect of formulation variables on Entrapment Efficiency

A response surface plot is used to show the relationship between the independent variable and dependent variable Z₂ (%EE). Based on findings, throughout all the formulations the %EE of the prepared SLN varied between 68 to 96.26%. The R² for the %EE was 0.9810 which indicates that the model is a strong fit and the model is significant. A polynomial equation may be utilized to make an estimation after remembering the coefficient's value and the mathematical sign it carries.

Z₂ = +96.68 - 7.58Z₁+ 4.42Z₂+ 2.18Z₁Z₂- 7.61 (Z₁)²- 4.51(Z₂)² … (5)

The coefficients in the equation show the quantitative influence of an independent variable on the entrapment efficiency. A good fit model between the dependent and independent variables is denoted by a high value for the correlation coefficient the observed model shows a p-value ˂0.0500 which is significant, and the model F-value was found to be 31.01 which shows that the model is significant, in addition to that the predicted and adjusted R₂ were in good relation, with a difference between them is observed to be ˂0.2, which demonstrate that the selected model gives the best fit for the data.

The surface plot graphs and the statistical analysis of the data show that the ratio of S_mix and Lipid used for formulation preparation has a significant impact on entrapment efficiency. It has been observed that entrapment efficiency is directly proportional to the concentration of lipid and inversely proportional to the concentration of S_mix.

Figure 3. Surface and counter plots showing effect of solid lipid and S_mix on %EE

A response surface plot and a contour plot of the formulation's particle size are shown in Fig. 3. Amongst all the formulations tested batch F6 produced using a combination of medium-level solid lipid (37.5 mg) and medium-level S_mix, had the best particle size with the highest % EE.

Zeta potential

It has been mentioned, that in a mixed electrostatic and sterical stabilization of the system the zeta potential should be near to -30 mV which can be enough for physical stability. The observed zeta potential of optimized formulation was -34.2 mV, Fig. 4, which has enough charge and mobility to prevent particle aggregation. None of the nine formulations had positive zeta potential.

Figure 4. Zeta potential of optimized SLN formulation

Freeze Drying of Optimized SLN:

The optimized formulation SLN 6 was cryoprotected with 5% trehalose and freeze-dried. The 48-hour freeze-drying process involved 36 hours of primary drying and 12 hours of secondary drying at a drying rate of 0.4 ºC/min. The SLN collected after the drying process was in the form of powder. The lyophilized formulation was stored at 2-8ºC in the refrigerator, Fig. 5.

Figure 5. Optimized freeze-dried SLN formulation

Evaluation of Freeze-Dried Formulation:

Solubility study:

The saturated solubility of the optimized SLN formulation was done in triplicate and by using a shaking cum incubator. The average saturated solubility of the optimized freeze-dried formulation was found to be 64.37±0.33 mg/100 mL. This indicates that SLN has a capability to enhance the solubility of BSC class II drug. SLN may enhance the solubility of the poorly soluble drug by various mechanisms. It may increase solubilisation properties of active molecules in the GI tract and blood. Additionally, surfactant used in the SLNs, such as tween 80 and propylene glycol, also showed some effect on the solubility of the drug.

TEM analysis:

The TEM picture of SLN particles in the optimized batch, Fig. 6, appears to be circular, with smooth surfaces and no evidence of aggregation. The particle size was 100 nm, which is close to the particle size of drug in SLN. TEM analysis showed that the particles of SLN were in nanosized diameter with the drug enclosed in the lipid core and shell of the surfactant.

Figure 6. TEM images of Optimized SLN

SEM analysis:

The SEM is used to analyze morphological structure of particles. The image in Fig. 7 shows particles of optimized freeze-dried SLN 6 formulation were of nanometric scale with spherical form and smooth surface.

Figure 7. SEM images of optimized freeze dried SLN

FTTR analysis:

The FTIR spectra of bosentan were obtained to verify its chemical intactness FT-IR Spectra of bosentan exhibited peaks of different functional groups such as S=O, C=C, N-H, C-N and C-O at characteristic frequencies of 1341,1560, 2959, 1341, 1110 cm^-1, respectively. The presence of various functional groups in the bosentan FTIR spectrum complied with its standard frequency values confirming the purity of the drug. The existence of peaks in the FTIR of physical mixture at 2865.47 cm^-1 and 2921 cm^-1 may be related to carbon-hydrogen stretching in the -CH₂ alkane group found in the fatty acids acyl chain. The frequency peak at 1438 cm^-1 for C-C is coupled to the CH₂group and for C=C peak at 1435 cm^-1. The frequency peak at 1733.45 cm^-1shows stretching vibration of the carboxylic functional group. The FTIR spectra of freeze-dried product revealed that the drug frequency peaks are reduced compare to its original peaks indicating drug entrapment within the solid lipid.

XRD analysis

The observed XRPD spectra of bosentan with intense peaks at 8.30°, 9.24°, 15.20°, 16.65°, 17.72° and 18.59° indicates its crystalline nature. The XRPD analysis of optimized SLN formulation found that the pure drug peaks were of less intensity and magnitude. The strong peaks observed at 21.8º and 27.8 º indicating drug is present in the SLN. The reduced intensity of the peaks indicates amorphous nature of drug.^24-25 The reason for decrease in intensity may be attributed to drug dispersion at molecular level in the lipid structure of the SLN.

DSC analysis

DSC analysis was implicated to check the potential interaction between the solid lipid and drug as well as to check physical integrity of the drug. The DSC thermogram of bosentan loaded SLN exhibited a peak at 104.2 ºC, which is very close to its melting point. There was a slight change in the endothermic peak shifting to 106.8 ºC due to drug interaction with solid lipid drug losing its crystallinity at the microemulsion stage.^24-25

In vitro drug release

The percentage of drug released from the optimized SLN formulation indicated an initial burst release of the drug (14 to 20 %) in the first 2 h. It may be attributed to some drug being adsorbed at the outer surface of the nanoparticles or a chance that drug is precipitated in the lipid region. The drug release from optimized SLN6 formulation was 94.69% while drugs release from plain drug was 42.6%.24- 27 This increased drug release is due to the pace at which it was diffused from the lipidic matrix's structure. We can infer from the first burst release of bosentan that the process of SLN development is responsible for the creation of an enhanced shell of an active molecule. Thus, we might infer that SLNs have the potential to improve bosentan dissolution.

Stability study

The accelerated stability study of the optimized freeze-dried SLN was done according to the guidelines of ICH for a period of 3 months in a stability chamber at 25 ºC ±2 ºC and at 60 ± 5 % relative humidity (RH).²⁷ The findings of this study revealed that SLN formulation showed no any significant change in particle size, amount of drug entrapped and drug released over the duration of study indicating null effect of temperature, humidity and light.

CONCLUSION:

The proposed research work aimed at improving solubility and dissolution of bosentan by formulating it as solid lipid nanoparticles. The micro-emulsion process was employed at varying concentrations of lipids and surfactants. A 3² randomized full factorial design was successfully used to study effects on micromeritic properties and zeta potential on the bosentan loaded SLNs. Solid-state characterization, in-vitro release and accelerated stability study on optimized formulation indicated possibility of improving solubility of BCS Class II drugs using statistical design.

CONFLICT OF INTEREST:

The authors declare no conflict of interest.

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Received on 09.02.2025 Revised on 22.05.2025

Accepted on 05.08.2025 Published on 01.12.2025

Available online from December 06, 2025

Research J. Pharmacy and Technology. 2025;18(12):6101-6109.

DOI: 10.52711/0974-360X.2025.00882

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Creative Commons License.

Factor	Name	type	Low actual level	Medium actual level	High actual level	Low coded level	Medium coded level	High coded level
Z₁	Lipid Concentration	Numeric	200 mg	250 mg	300 mg	-1	0	+1
Z₂	Surfactant concentration	Numeric	35%	37.5%	40%	-1	0	+1

Variables	Observed Response	b₀	Z₁	Z₂	Z₁Z₂	(Z₁)²	(Z₂)²	R²	F
Particle size	Coefficient	+115.87	25.80	-10.18	4.95	28.80	6.35	0.9883	50.55
Particle size	p-value	0.0043	0.0011	0.0159	0.1450	0.0040	0.1736	-	-
EE%	Coefficient	+96.68	-7.58	4.42	2.18	-7.61	-4.51	0.9810	31.01
EE%	p-value	0.0087	0.0028	0.0129	0.1205	0.0131	0.0514	-	-