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Journal of Drug Delivery and Therapeutics

Open Access to Pharmaceutical and Medical Research

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Open Access Full Text Article   Research Article

Formulation, Optimization and Characterization: Thermosensitive Intranasal Nanostructured Lipid Carrier (NLC) In-situ Gel of Novel Agomelatine to Overcome the Limitations of Oral Delivery

Nabeela Zainab*, Syed Abdul Azeez Basha , Abdul Mannan 

Department of Pharmaceutics, Deccan School of Pharmacy (Osmania University), Aghapura, Hyderabad, Telangana – 500 001, India

 

 

INTRODUCTION

Depression, a prevalent and debilitating mental disorder, seriously impairs cognitive performance, interferes with physical health, affects day-to-day functioning, causes social and financial challenges, and frequently results in high rates of suicide¹. The effectiveness of current pharmacotherapy treatments, such as tricyclic antidepressants (TCAs) and selective serotonin reuptake inhibitors (SSRIs), is outweighed by serious side effects, including discontinuation symptoms, sexual dysfunction, and disturbed sleep patterns because their mechanisms of action are not fully understood and their interactions with non-targeted receptors².

Agomelatine (AG), a melatonin analogue, is an atypical antidepressant that combines melatonin receptor agonism and 5-HT_2c antagonism, offering a safer alternative to SSRIs and TCAs with fewer side effects and better tolerance³. It is marketed as a 25 mg oral tablet. However, AG has low water solubility and poor oral bioavailability (<5%), a short half-life of 1–1.5 hours, high protein binding, and extensive hepatic metabolism, which complicates longer dosing schedules and patient compliance⁴. High doses and liver metabolism can also pose a risk of liver damage⁵. As an alternative to the oral route, nasal route has been researched to target the brain tissues directly with lower concentrations of the drug.

Nose-to-brain is a non-invasive technique for targeting the brain directly, with high-level vasculature offering rapid absorption and bypassing the blood-brain barrier (BBB) especially for drugs under 200 nm in size⁶. It increases bioavailability by preventing plasma protein binding, making more of the drug available for therapeutic effects. However, conventional nasal delivery faces challenges such as difficulty targeting the upper nasal region, rapid mucociliary clearance of drugs, and low membrane permeability of nasal mucosa.

A promising solution is the use of nanosize-based in-situ gelling systems, which form a gel network in the nasal cavity, increasing residence time and allowing for more efficient drug delivery with accurate dose⁷. Thermosensitive in-situ gels, made from polymers like Poloxamer 407 (Pluronic^® F127), which undergo reversible gelation in response to temperature changes⁸ such as increment to temperature in physiological nasal range, improve the system's effectiveness. However, solution of poloxamer 407 that imparts gelling property has short residence time⁹ due to it quickly dissolving in aqueous phase, limiting its effectiveness. Residence time can be extended by adding mucoadhesive polymers like sodium alginate, which is known for its strong adhesive properties and compatibility with Poloxamer 407¹⁰, to enhance gel strength and pharmacological effectiveness without causing irritation or any significant side effects.

To further enhance intranasal administration and drug delivery, an attractive colloidal system of nanostructured lipid carriers (NLCs) with a size of less than 200 nm has been selected for efficient AG delivery. The next generation of SLNs are NLCs, which are made up of a binary mixture of liquid and solid lipids stabilized by a surfactant system. Compared to conventional colloidal delivery systems (such as nanoemulsions), they have several benefits, including cell-specific controlled drug release, high stability, high drug entrapment, and decreased drug leakage¹¹. Additionally, these nanoparticles enhance nasal penetration and inhibit drug deterioration. 

The research strategy here seeks to get beyond the drawbacks of traditional nasal delivery by fusing nanotechnology with in-situ gelling technology to deliver neurotherapeutics like agomelatine to the brain effectively. In current investigation, effort was made to develop NLCs of agomelatine (AG-NLCs) using a modified high-shear homogenization method followed by converting them into thermoreversible in-situ gel by cold method with poloxamer 407 and sodium alginate as polymers to overcome associated oral delivery problems.

MATERIALS AND METHODS

Materials

Agomelatine was received as a gift sample from Precise ChemiPharma, Navi Mumbai, India. Compritol^® 888 ATO, Precirol^® ATO 5, Gelucire^® 43/01 were kindly gifted by Gattefossé, Bangalore, India. Oleic acid, Capryol^® 90, Labrafac™ PG, Lauroglycol™ FCC were received from SRL Chemicals, Mumbai, India. Poloxamer 188 and poloxamer 407 were generously supplied by BASF Pharma, Bangalore, India. Sodium alginate was purchased from S.D. Fine Chem Ltd., Mumbai, India. Ethanol and methanol were purchased from Ashland (Pvt. Ltd), Maharashtra., India. Dialysis Membrane-110 was obtained from HiMedia Laboratories, Mumbai, India. All other reagents were of analytical grade obtained from laboratory.

Selection of Excipients

Selection of the Solid Lipid and Liquid Lipid 

Screening of solid lipids was done by measuring agomelatine's saturation solubility in various solid lipids – Compritol^® 888 ATO, Precirol^® ATO 5, Gelucire^® 43/01. One gram of each solid lipid was put into separate test tubes, and heated in a water bath with a controlled temperature to 4-5°C above the respective solid lipid's melting point (MP) ¹². 

For selected liquid lipids – Capryol^® 90, Oleic Acid, Lauroglycol^™ FCC, Labrafac^™ PG – 2 mL of each vehicle was added to 5 mL stopper vials.

50 mg of agomelatine was put in excess in each test tube and each vial with different solid lipids and liquid lipids respectively. Using a vortex shaker (CM101; Remi), the mixtures were agitated at 100 rpm, 25°C for 72 hours to reach a supersaturation state. After centrifuging the mixtures at 18,000 rpm (3300; Inkarp Instruments), the excess agomelatine was removed by passing the supernatant through a 0.20 µm syringe filter. Following the proper dilution with ethanol, the quantity of agomelatine in each filtrate was measured using a UV spectrophotometer (T60U; PG Instruments) at 229 nm (readings were taken thrice)¹³.

Selection of Binary Mixture of Solid and Liquid Lipid based on Miscibility

To test the compatibility of chosen lipids in the ratio of solid lipid to liquid lipid ratio stated in literature¹⁴, both lipids were mixed together in the given ratio 70:30 by heating to 15-20°C above melting point of selected solid lipid, agitated at 100 rpm for 1 h, brought to 25°C for 24 h. Obtained solidified binary mixture was assessed visually for phase separation or precipitation by smearing on filter paper to analyze for traces of any oil on the filter paper, absence of which indicates miscibility of the lipids¹⁵.

Screening of Surfactant 

100 mg lipid_mix, with a ratio of 70:30 solid:liquid lipid, was dissolved in 3 ml of methylene chloride and added to 10 ml of 5% aqueous surfactant solution. The solvent was evaporated and a colloidal system, consisting of NLC, was created by agitating the mixture constantly. UV spectrophotometer (T60U) was used to examine the solution in three batches for % transmittance at a wavelength of 229 nm after suitable dilution with deionized water¹⁶.

Drug-Excipient Interaction study using FT-IR

By FTIR analysis on JASCO Inc. FT/IR-4X, FT-IR spectra were obtained for pure drug (Agomelatine) and mixtures of drug with excipients (Precirol^® ATO 5, oleic Acid, poloxamer 188 and poloxamer 407). All solid samples were prepared using the potassium bromide (KBr) pellet technique¹⁷  1:10 of sample:KBr at 25°C, and ATR method¹⁸ was used for liquid samples, spectra were recorded from 4000 to 400 cm^-1.

Design Of Experiment – 3² Full Factorial Design 

A two-factor three-level factorial design¹⁹ was employed using Stat-Ease Design Expert v.12 (USA) to investigate the impact of independent variables on dependent variables. The quantity of total lipid (A) and surfactant concentration (B) were chosen to serve as the independent variables (two-factors). Particle size (nm) at a range of (150 to 170), Zeta potential (mV) at range of (-3 to -40) & Entrapment efficiency (%) at a range of (50-70) were selected as dependent variables (three responses) (Table 1). We tested the impact of the two factors we chose A & B at three different levels (+1, 0, -1). Each factor's experimental range was established according to preliminary findings and the feasibility of manufacturing the NLC at extreme levels (Table 2). The experimental approach led to the development of nine different formulas, designated as AF1–AF9 and evaluated for chosen dependent responses PS, ZP, EE.

The applied factorial table shows the values of the independent factors and the dependent responses that will be assessed (Table 3).

 

 

Table 1: Experimental variables (factors and responses)

 

Table 2: Independent Factors at Low and High Level based on Design Expert

 

 

 

 

 

 

Table 3: Agomelatine NLC Trials based on Stat-Ease Design Expert

 

 

Statistical Analysis:

Analysis of variance (ANOVA)¹⁷ was conducted with a confidence interval of 95% to identify the statistical significance of each variable and differences across variables. For each response, a suitable mathematical model (regression equation) was generated to measure the impact of independent variables, by aid of statistical metrics such as the regression coefficient (R²), p-value (p<0.05), and F-value. Contour plots and 3D response surface plots were created to establish the relationship between factors and dependent variables.

Preparation of AG-NLC

Using data from the nine separate runs by factorial design approach depicted in Table 3, Agomelatine-loaded NLCs were made using slightly modified hot high-speed homogenization (HSH) method²⁰ with solid lipid:liquid lipid (lipid_mix) in 70:30. Chosen solid lipid (here Precirol^® ATO 5) was heated up on a water bath at 80℃, a temperature about 15-20°C above its MP, liquid lipid (i.e., Oleic acid) was added to melting solid lipid. Into the molten lipid phase, 5 mg of agomelatine in a little quantity of ethanol (1 mL) was placed. The lipid phase was transferred to the different concentrations of hot aqueous surfactant phase (double distilled water + Poloxamer 188) preheated at 80 ℃, same as that of lipid phase with constant stirring. This mixture was put through high-speed homogenizer (SS316; Bhuvan Engineering) at 18000 RPM for 30 minutes at 80℃, followed by rapid spinning at 1200 rpm for 15 min using probe sonicator (VCX750; SONIC)⁴⁸ for increased size reduction. The NLCs were brought to ambient temperature, filtered (Whatman syringe filter; nylon; 0.45 µm) to remove unentrapped agomelatine, stored in sterile glass vials with screw caps at 6°C ± 2°C until they were further analyzed.

 

 

Table 4: Agomelatine NLC Formulations

S. No.	Ingredients	AF1	AF2	AF3	AF4	AF5	AF6	AF7	AF8	AF9
1	Agomelatine (mg)	5	5	5	5	5	5	5	5	5
2	Precirol® ATO 5 (mg)	70	175	280	280	70	175	70	175	280
3	Oleic Acid (mg)	30	75	120	120	30	75	30	75	120
4	Poloxamer 188 (%)	1.5	1.5	2	1.5	1	1	2	2	1
5	Ethanol (mL)	1	1	1	1	1	1	1	1	1
6	Total Lipids (mg)	100	250	400	400	100	250	100	250	400

 

 

Figure 1: Formulated Nanostructured Lipid Carriers for Agomelatine

 

 

Characterization of AG-NLCs

Particle size, Polydispersity Index (PDI) and Zeta Potential

The PS, polydispersity Index and ZP of prepared NLCs were analyzed by Nano Partica Nano particle analyser/Zetasizer – (SZ-100; Horiba Scientic) with 90° angle at 25°C. The samples have been adjusted to a 10% concentration using double distilled water to avoid multiple light scattering effects and contained in a disposable cuvette made of quartz, which included two electrodes²¹. 

Zetasizer uses dynamic light scattering (DLS) method to analyze PS and electrophoretic mobility for ZP determination.

 

Figure 2: Nano Partica Nano Particle Analyser

 

 

 

Entrapment Efficiency (%)

A slightly modified version of the previously published method was used to determine the %EE of agomelatine in the NLC²². After filtering out any traces of free agomelatine, 1 mL of the NLC solution was mixed with 2.5 mL of methanol to dissolve it entirely. Following a 15-minute centrifugation run at 4℃ at 12,000 rpm (3300; Inkarp Instruments), the transparent supernatant liquid was collected, filtered, and subjected to UV analysis at 229 nm. The following equation was used to compute the %EE:

 

 

 

 

Formulation of Thermosensitive AG-NLC In-situ Gel

AG-NLC in-situ gels were prepared by cold method²³ (Table 5). Varied concentrations of poloxamer 407 solutions (2%, 4%, 6%, 8% and 10%) were prepared by dispersing the required amount of polymer in 25 ml cold deionized water (5 ˚C) with constant stirring on magnetic stirrer at 200 rpm for 1 hr, followed by refrigeration for 4 hours to get clear solutions by complete dissolution. 0.3% (0.075 g) sodium alginate (mucoadhesive polymer for controlled release of agomelatine from the gel) was mixed with each conc. of poloxamer 407 solution. 25 microliter (0.10% w/v) of optimized AG-NLC was added to each base solution at 5 ℃ with continuous stirring to form homogeneous phase. With incubation at 35 ℃, gelation was allowed to happen. The gels were then refrigerated for further evaluation.

 

 

Table 5: AG-NLC In-situ Gel Formulation 

 

 

Figure 3: (a) Poloxamer solutions in Varied Concentrations (2-10%); (b)Thermosensitive AG-NLC In-Situ Gels (NLCG-1 to NLCG-5)

 

Evaluation of AG-NLC In-Situ Gel

Viscosity

The viscosity-related phase behavior changes were quantified using a Brookfield viscometer (Brookfield Engineering, MA, USA) equipped with a specific C50-1 spindle at 20 rpm. The temperature was recorded at 25 ℃ and 37 ℃, with three measurements taken for each²⁴. 

Determination of pH

pH of formulated AG-NLC in-situ gels was measured in triplicate with a calibrated digital pH meter (WPH-10; Wensar Instrument) at room temperature by immersing the glass electrode into it and recording the value²⁵.

Gelation temperature and gelation time. 

5 mL of AG-NLC in-situ gel was placed in a clear vial containing a magnetic bead. Using a magnetic stirrer (MG-212; SISCO) and a heating pan, the vial was placed in a water bath set at 4°C. A 2℃/min increase in temperature at 100 rpm was achieved stirring in the range of transition temperature (25-37°C). The temperature when the AG-NLC in-situ gel in solution form converted to gel with non-flowing characteristic when turned to 90° angle was noted, when the bead stopped rotating, and the duration of the phase transition was documented as the gelation time²⁶. The experiments were repeated three times. 

Drug Content

A modified UV-Vis spectroscopic technique was used to ensure drug content uniformity. In a volumetric flask, 1 mL of the gel formulation—which is equal to 1 mg of Agomelatine—was combined with 100 mL of PBS (pH 6.8). The mixture was agitated for 2 hours and then filtered. One mL of the filtrate was diluted with ten mL of pH 6.8 phosphate buffer and then analyzed at 229 nm. Drug content was determined three times for each formulation²⁷.

In Vitro Drug Release Study

In-vitro diffusion experiments from in-situ gels were carried out using a Franz diffusion cell (JFDC-07; ORCHID Scientific) through dialysis membrane soaked in receptor dialysis medium of PBS 6.8 for 4 h before use. 1 mL of AG-NLC in-situ gel was added to the donor compartment, while 15 mL of PBS (pH 6.8) was added to the receiver compartment. The mixture was kept at 100 rpm with a magnetic stirrer at 37 ± 1 °C for 6 hours. The receptor compartment was sampled at regular intervals (every 1 mL) and restocked with new dialysis media at the same volume at time intervals 30, 60, 90, 120, 150, 180, 210, 240, 270, 300, 330, 360 minutes²⁸. The samples were taken three times and then passed through a 0.20 μm filter; after appropriate dilutions, they were analyzed spectrophotometrically (T60U) at 229 nm against PBS (pH 6.8) as blank²⁹.

Drug Release Kinetic Study

In vitro drug release data of optimized AG-NLC in-situ gel was fitted to four well-known release models like zero order, first order, Higuchi-equation, and Peppas-Korsemeyer²⁸ to know the mechanism of drug release of agomelatine from the formulation by regression analysis correlation coefficient (R²) and release exponent (n) determination.

Scanning Electron Microscopy (SEM)

To envisage the surface morphology of the optimized AG-NLC in-situ gel formulation in terms of shape and texture of surface, scanning electron microscopic analysis (SEM) was done (S-3700N, Hitachi) at 15-18 Kv after gold sputtering at various magnifications³⁰. It gives a qualitative description of the surface. 

Stability Studies

Short-term stability investigations were conducted on the optimized AG-NLC in-situ gel as per ICH regulations. The samples were kept in glass vials with screw caps at temperatures 4°C±1°C & 25°C±1°C for a duration of 1 month in stability chamber (NLHC16SI; Newtronic).  Results were evaluated for physical stability at day 30, for drug diffusion rate, gelation temperature, pH, and drug content using same methods stated earlier²⁷.

RESULTS AND DISCUSSION

Selection of excipients

 Selection of Solid Lipid and Liquid Lipid

For high drug loading in NLC, drug should show high solubility in lipid matrix. Order of solubility of agomelatine in solid lipids was Precirol^® ATO 5>Compritol^® 888ATO>Gelucire^® 43/01 (Figure 4a) and that in liquid lipids was oleic acid>Labrafac^™ PG>Lauroglycol^™ FCC>Capryol^® 90 (Figure 4b). As maximum solubility was demonstrated in Precirol^® ATO 5 (62 ± 0.147 mg/mL) and oleic acid (81.5 ± 0.91 mg/mL), they were chosen as solid lipid and liquid lipid respectively for AG-NLC preparation. AG's greater solubility in liquid lipid as opposed to solid lipid suggests it may be responsible for greater drug loading and retention¹¹.

It has been demonstrated that Precirol^® increases the EE of NLCs³¹, could be because of its loose structure to trap lipophilic and hydrophilic molecules.

 Miscibility assessment

Lack of oil droplets from Precirol^® ATO 5 and oleic acid mixture, and no sign of phase separation on filter paper confirmed the miscibility of the Lipid_mix in 70:30 ratio. Based on published research, selected lipids demonstrated the necessary stability and were shown to be safe for the mucous layer and a variety of cell types³².

 Selection of Surfactant

Figure 4c lists the surfactants that were considered for use in determining the Agomelatine transmittance %; poloxamer 188 (97.98 ± 0.45%) was chosen to generate NLC. More percentage of light transmittance indicates smaller vesicle size, hence greater emulsification. This occurs with surfactants having high HLB value, poloxamer 188 has HLB value of 29. Consistent with this, earlier studies demonstrated compatibility of poloxamer 188 with selected lipids³³. As a surfactant, Poloxamer 188 has the capacity to emulsify selected lipid_mix, has a mild effect on the nasal mucosa without irritating it, and tends to lessen lipid polymorphic state transitions.

 

 

 

 

 

(a)                                                                         (b)

(c) 

Figure 4: Solubility of AG in different selected (a) solid lipids, (b) liquid lipids, (c) surfactants. All measurements were repeated thrice.

 

 

Fourier Transform Infrared Spectroscopy

The stretching of the N-H bond, of the C=O bond, and of the aliphatic C-H bond for the CH₃ group all caused broad peaks seen in the FTIR spectrum of pure agomelatine (Figure 5), at 3243.68 cm^-1, 1625.7 cm^-1, and 2941.88 cm^-1 respectively; these are characteristic to agomelatine, they demonstrate similarity to and are in good occurrence with findings reported earlier³⁴ (Table 6).

FTIR spectra of NLC formulation mixture (Figure 7) and NLCG formulation mixture (Figure 8) reported same absorption peaks at 3005.52 cm^-1 for amide (N-H) stretch and 1628.59 cm^-1 for ester (C=O) stretch. This spectral data is also close to the major absorption peaks of respective groups reported in literature. The placements of the distinctive bands have not changed much which concludes that the drug was dispersed in the excipients molecularly thus retaining its unique characteristics while avoiding chemical reactions with the other excipients.

 

 

Table 6: FTIR characteristic peak comparison between pure agomelatine and AG with different excipients

Figure 5: FTIR Spectrum of Pure Agomelatine

Figure 6: FTIR Spectra of Pure AG with (a)Precirol^® ATO 5, (b)Oleic Acid, (c)Poloxamer 188, (d)Poloxamer 407

Figure 7: FTIR Spectrum of NLC formulation mixture – Pure Agomelatine with Precirol^® ATO 5, Oleic Acid and Poloxamer 188

Figure 8: FTIR Spectra of NLCG Formulation mixture – Pure Agomelatine with Precirol^® ATO 5, Oleic Acid, Poloxamer 188, Poloxamer 407

 

 

Optimization & Statistical Analysis for Formulated AG-NLCs (AF1-AF9)

Using Design-Expert^®, AG-NLCs were optimized. 9 Formulations (AF1-AF9) found in different levels of total lipids (A) and surfactant concentration (B) were prepared and evaluated for dependent responses – particle size (PS), zeta potential (ZP), entrapment efficiency (EE) depicted in Table 7 showing the design matrix of response results. This response data was fitted into different models. R² value of each model for each response – PS, ZP, EE – was obtained with 2FI model being the best fitted model showing R² value of 0.9660, 0.9677, 0.9994 respectively (Table 8). Interactive optimization model, two-factor interaction (2FI) model was chosen also based on p-value which was lowest for this model compared to other models under observation. The effects of components A and B on PS, ZP, and EE are determined using ANOVA utilized by 2FI, which yields significant (p<0.05) or insignificant (p>0.05) values.

 

 

 

Table 7: Formulation Optimization of AG-NLC with their observed responses

		Factor 1	Factor 2	Response 1	Response 2	Response 3
Std	Run	A: Total Lipids (mg)	B: Surfactant (%)	Particle Size (nm)	Zeta Potential (mV)	Entrapment Efficiency (%)
4	1	100	1.5	130.2	-23.2	39.23
5	2	250	1.5	172.3	-29.3	53.08
9	3	400	2	235.3	-20.1	27.65
6	4	400	1.5	241.1	-18.1	23.28
1	5	100	1	152.1	-21.3	32.31
2	6	250	1	184	-32.2	48.41
7	7	100	2	115.9	-25.4	45.05
8	8	250	2	159.3	-37	58.14
3	9	400	1	265	-16.1	21.11

 

 

Table 8: 2FI model summary for PS, ZP, EE

Response	Mean	Std. Dev	R2	Adjusted R2	Predicted R2
1: PS	183.91 nm	2.17	0.9660	0.9456	0.9267
2: ZP	-24.74	2.03	0.9677	0.9139	0.8573
3: EE	38.70%	0.5517	0.9994	0.9983	0.9922

 

 

 

Table 7 shows the summary of the ANOVA findings for response 1, 2, 3, i.e., PS, ZP, %EE using the 2FI model with a coefficient based on the coded variables provided by the Design-Expert^®. As per ANOVA results from the software, 2FI model of response 1, 2, and 3 was best fitted as significant as F-value is 240.52, 17.97 and 938.92; and p-value was 0.0004, 0.0191, and < 0.0001 respectively. Observed p<0.05 indicate accepted significance of coefficient terms. Model terms A, B, and A². are significant for PS; A and A² are significant model terms for ZP; A², AB, B, and A are significant model terms for %EE. These results indicated that independent selected variables – individually and in their interaction – are significantly influencing the three responses as shown in Table 9.

 

 

 

Table 9: F-ratio and associated p-values for the NLCs (AF1-AF9)

Source	Sum of Squares	df	Mean Square	F-value	p-value
For Response 1, PS
Model	21695.55	5	4339.11	240.52	0.0004	Significant
A-Total Lipids	19631.04	1	19631.04	1088.16	< 0.0001
B-Surfactant	1368.06	1	1368.06	75.83	0.0032
AB	10.56	1	10.56	0.5855	0.4999
A²	652.81	1	652.81	36.19	0.0092
B²	33.08	1	33.08	1.83	0.2687
Residual	54.12	3	18.04
Cor Total	21749.67	8
For Response 2, ZP
Model	369.33	5	73.87	17.97	0.0191	Significant
A-Total Lipids	40.56	1	40.56	9.87	0.0516
B-Surfactant	27.74	1	27.74	6.75	0.0805
AB	0.0025	1	0.0025	0.0006	0.9819
A²	294.44	1	294.44	71.65	0.0035
B²	6.60	1	6.60	1.61	0.2945
Residual	12.33	3	4.11
Cor Total	381.66	8
For Response 3, EE
Model	1428.79	5	285.76	938.92	< 0.0001	Significant
A-Total Lipids	330.78	1	330.78	1086.86	< 0.0001
B-Surfactant	140.26	1	140.26	460.86	0.0002
AB	9.61	1	9.61	31.58	0.0111
A²	948.01	1	948.01	3114.89	< 0.0001
B²	0.1233	1	0.1233	0.4053	0.5696
Residual	0.9130	3	0.3043
Cor Total	1429.70	8

 

 

Effect of Independent factors on Response 1: Particle Size

The polynomial equation with respect to coded factors was potentially utilized to identify the relative impact of given levels of each factor (A and B) on response 1 PS, by comparing the factor coefficients based on magnitude and mathematical sign (+/-). As a general rule, high levels are coded as +1 and low levels as -1.

The coded-factors equation for PS response given by Design-Expert^® was represented as follows:

PS = +169.16 +57.20 A – 15.10 B + 1.62 AB + 18.07 A² + 4.07 B²                                                                            (Eq.1)

PS of all NLCs AF1-AF9 fell within 115.9-265.0 nm. The polynomial equation of PS suggests that factor B has a negative dominant effect and factors A, AB, A² & B² have positive dominant effects on PS. Figure 9a further shows that PS increases with increasing concentration of total lipids. This can be because more lipid creates increased core viscosity resulting in swollen core. As for the effect of factor B, increasing surfactant concentration decreases particle size due to reduced surface interfacial tension helping the NLC particles to breakdown into smaller sizes and remain disaggregated.

Effect of Independent Factors on Response 2: Zeta Potential

ZP response coded-factors equation given by Design-Expert^® is represented as follows:

ZP = -31.62 +2.60 A – 2.15 B + 0.0250 AB + 12.13 A² – 1.82 B²  (Eq.2)

ZP of all NLCs AF1-AF9 was in the range of -16.1 to -37.0. Factor B & B² seem to show negative dominant effect on ZP and factors A, AB & A² show positive effects (Eq.2). ZP decreases with increasing concentration of surfactant B. Higher surfactant levels result in superposing of electric double layer and its compression due to its non-ionic nature which provides the material it is adsorbed on with a negative charge. The zeta potential of lipid nanoparticles has been shown to be enhanced by poloxymer 188 alone. Effect of A and B is also confirmed from ANOVA results and 3D response surface plot (Figure 9b).

Effect of Independent Factors on Response 3: Entrapment Efficiency of AG in AG-NLC

EE quadratic equation was given by Design-Expert^®, represented as follows:

EE = +53.04 + 7.42 A + 4.84 B – 1.55 AB – 21.77 A² + 0.2483 B^{2 B2}                                                               (Eq.3)

EE of all NLCs AF1-AF9 was in the range of 21.11-58.14 %. Eq.3. suggests that A, B, AB, A² have antagonistic effect while B² show synergistic effect on EE. EE increases with increasing total lipids (A) as well as increasing surfactant concentration (B). Elevated surfactant levels increase solubility and stability of agomelatine in lipid matrix by decreasing partitioning between phases leading to micelle formation. Further, more amount of lipid (factor A) in the matrix results in a structure with less order and imperfections allowing more space for solubilization and entrapment of agomelatine¹¹, which can be attributed mainly to liquid lipid. The findings of the ANOVA and 3D response surface plot provide extra context for this (Figure 9c). 

 

 

Figure 9: 3D Response Surface Plot for (a) Particle Size of NLCs, (b) Zeta Potential of NLCs, (c) Entrapment Efficiency of AG in NLCs

 

Selecting the optimized formulation

In order to optimize the formulation with the required responses, a multi-criteria decision optimization (MCDM) approach was used. For the optimization process, we applied the following constraints: PS: 150-170 nm; ZP: -40 to -30 mV; and EE: 55-65% to get optimal formula solutions with high desirability functions. 

According to the response surface plots in Figure 10 and the data in Tables 10 & 11, the best formulation that fits the model is AF8 with its observed values very closely aligning with the predicted values of the software (Table 13-14).

 

  

Figure 10: Contour plot for Optimization of NLCs

 

Table 10: Predicted Factors for Optimized Formulation

Factor	Name	Level	Low Level	High Level	Std. Dev.	Coding
A	Total Lipids	253.17	100.00	400.00	0.0000	Actual
B	Surfactant	1.96	1.0000	2.00	0.0000	Actual

 

Table 11: Point Prediction & Confirmation

Solution 29 of 43 Response	Predicted Mean	Predicted Median	Observed	Std Dev	SE Mean	95% CI low for Mean	95% CI high for Mean	95% TI low for 99% Pop	95% TI high for 99% Pop
Particle Size	160	160	159.3	4.24743	2.96016	150.579	169.421	121.087	198.913
Zeta Potential	-35.0361	-35.0361	37	2.0272	1.41282	-39.5323	-30.5399	-53.6085	-16.4638
Entrapment Efficiency	57.4682	57.4682	58.14	0.551678	0.384481	56.2446	58.6918	52.4139	62.5224

 

 

 

Predicted values of total lipids (mg), surfactant (%) were 253.17 mg, 1.96% respectively showing great similarity to observed values of 250 mg and 2% of the same for AF8 NLC (Table 7). Literature validates the results of optimized formulation AF8 (Table 12). Particle size of less than 200 nm falls in the acceptable range for NLCs for intranasal delivery from nose-to-brain³⁵. Zeta potential in range of ±30 mV prevents aggregation of particles³⁶. Higher the zeta potential, higher the physical stability of NLCs for intranasal delivery³⁷. However, entrapment efficiency was lower than observed in literature³⁶ which can be attributed to drug leakage at high homogenization speeds during preparation.

 

 

Figure 11: Particle Size & Polydispersity Index for Optimized AF8

Figure 12: Zeta Potential for Optimized AF8

 

PDI values were obtained for all nine formulations in the range of 0.181-0.354, among which AF1-AF3, AF5-AF8 exhibited polydispersity (Table 12). For lipid-based NLCs, PDI less than 0.3 is acceptable and affirms monodisperse, narrow size distribution³⁸. Optimized AF8 showed polydispersity index of 0.212 indicating homogenous nanosize population.

 

 

Table 12: Characterization of NLCs for Formulations AF1-AF9

 

Preparation and Evaluation of Thermosensitive AG-NLC In-situ Gel

Optimized AG-NLC formulation AF8 was integrated into thermosensitive poloxamer 407 of different conc. (2-10%) and sodium alginate at a level that was fixed, 0.3% to give in-situ gels³⁹ (Table 5).

Viscosity, pH, and Drug content

In reported literature, pH of nasal mucosa ranges from 5.5-6.5⁴⁰ with baseline pH of 6.3⁴¹ which can vary depending on physiological condition. Formulated AG-NLC in-situ gels (NLCG1-NLCG5) were found to have pH in the range of 6.10±0.54 – 6.34±0.73 (Table 13) showing that no mucosal irritation is expected. 

For NLCG to be easily injected into the nose by a syringe and undergo an immediate sol-to-gel transition, its formulation must have an appropriate viscosity. Instead of breaking down or eroding quickly, the prepared gel should remain intact enough to provide localized, persistent drug release. It was noted that the polymer solutions had a viscosity which was thixotropic with respect to temperature change. (Table 13)^25,42. In an aqueous solution of poloxamer 407, the poly (propylene oxide) core dehydrates as the temperature increases gradually. Conversely, solid and transparent gels are created when the hydrophilic poly (ethylene oxide) shell gets hydrated and inflated⁴³. 

Drug content was found from 92.17±0.12 – 97.48±0.38% (Table 13) which is within an acceptable range of 90-97% which means agomelatine was evenly dispersed. 

Gelation temperature & Gelation time

Gelling temperature for intranasal in-situ gels has a range of 30-36℃⁴⁴ corresponding to internal nasal physiological temperature from 29-34 ℃⁴⁵. The gelation temperature of all in-situ gels was measured (Table 13). NLCG3-NLCG5 gelation temperatures corresponded to accepted range. With increasing poloxamer 407 conc., gelation temperature decreases. Forming of gel at temperature less than 30℃ causes difficulty in administering the formulation, and gelling at more than 36℃ results in leakage and loss of in-situ gel solution from nasal cavity. If gelation does not occur at nasal mucosal site instantly within required time at required temperature, immediate nasal clearance of formulation occurs, hence gelation time is considered, it is the time required for in vitro gelation of polymeric liquid solution into gel phase. For AG-NLC in-situ gels, gelation time was measured from 9.4±0.96 to 23.2±0.46 seconds⁴⁴ (Table 13). NLCG1 and NLCG2 with high gelation temperatures and gelation times signify the formulations cannot be opted for intranasal delivery.

 

 

Table 13: Viscosity, pH, Gelation Temperature, Gelation Time, and Drug Content of Formulations NLCG1-NLCG5.

Results are expressed as mean ± SD, n=3

 

 

From the above results NLCG-4 formulation (Table 13) was chosen as optimized development. All values were within optimal range of literature.

In-Vitro Drug Release Study

For NLCG1–NLCG5, release behavior was assessed using dialysis-based in-vitro drug release method. The in-situ gels presented enhanced sustained agomelatine release over a period of 6 hours in pH 6.8 phosphate buffer, which acted as simulated nasal fluid (pH 6.5). It has been observed from the results depicted in Table 14 and Figure 13 that NLCG-1, NLCG-2, NLCG-3 initially showed burst release in first 30 mins of 43.77%, 27.07% and 21.21% respectively as compared to regular stable controlled release of agomelatine from NLCG-4 and NLCG-5. Formulation NLCG-1 achieved complete drug release within 2.5 hours. This is due to lower concentrations of poloxamer-407 polymer in the formulation (2%) indicating low viscosity, which is not sufficient to achieve sustained drug release. 

NLCG containing Poloxamer 8% (NLCG-4) showed sustained release till the 6^th hour with a release of 100.01% and it is considered as optimized formulation based on preliminary characterization of AG-NLC in-situ gels depicted in sections 4.1 and 4.2, along with in-vitro drug release profile. Increase in polymer concentration resulted in a prolonged release rate (Figure 13). Saturation of concentration was observed in case of formulation prepared with poloxamer 10% solution (i.e NLCG-5) as the complete drug release was not achieved at the end of 6^th hour.

 

 

Table 14: In-Vitro Release study for Formulations NLCG-1-NLCG-5

Results are expressed as mean ± SD, n=3

 

Figure 13: Drug release profile comparison of formulation NLCG-1-NLCG-5

 

 

Release Kinetics

The estimations of k (release constant), R² (correlation coefficient) & n (release exponent) values are shown in Table 15. On interpreting data, it is concluded that with highest correlation coefficient R² 0.9859 with n 0.7722, kinetic analysis of the drug release profile of optimized NLCG-4 showed drug release data best fits the Korsmeyer model (Figure 14); which states that 0.45<n<1 suggests non-Fickian transport mechanism⁴⁶. NLCG-4 follows non-Fickian diffusion/anomalous diffusion; indicating diffusion is not the only drug release mechanism involved, but could also be contributed by erosion at a controlled rate⁴⁷ due to slight alterations in the formulation matrix at elevated temperatures (37℃). Liquid lipid present in the matrix gives an arrangement that is less organized which averts drug purging.

 

 

Table 15: Kinetic Data for Optimized Formulation NLCG-4

 

Figure 14: Korsmeyer Model Graph for Optimized NLCG-4

Scanning Electron Microscopy

The optimized NLCG-4 showed particles as distinct, with uniform, almost spherical, and smooth surfaces without aggregation at different magnifications (Figure 15). Turbidity in the background indicates lipid matrix.

Figure 15: SEM images of NLCG-4 at different magnifications – 1.00 KX, 25.00 KX, 50.00 KX

 

Stability Studies

Short term accelerated stability data (Table 16) for NLCG-4 showed almost no loss of drug at 4°C, a loss of 0.009% drug content at 25°C after 30 days which was considered negligible. There was minimal change in gelation temperature and pH. This concludes the changes in characterization data after stability studies were not significant as compared to the data procured on day 0 before starting stability studies, indicating the formulation retained its properties hence, confirming its stability.

 

 

Table 16: Stability studies of Thermosensitive AG-NLC In-situ Gel Optimized Formulation NLCG-4

 

 

CONCLUSION AND SCOPE

Due to agomelatine's low oral bioavailability (<5%), the intranasal route was investigated. FTIR analysis confirmed compatibility with excipients such as lipids, surfactants, and gelling polymers. Agomelatine was successfully incorporated into NLCs and suspended in an in-situ gel using poloxamer 407 for controlled release. A 3²-factorial design optimized the NLC formulation, resulting in nanosized particles with good zeta potential and acceptable entrapment efficiency for AF8. Optimized AG-NLC gel (NLCG-4) had suitable pH, viscosity for nasal administration, and enhanced mucosal residence time. In vitro, the optimized NLCG-4 maintained 100% agomelatine release prolonged over 6 hours. Stability studies at 4°C and 25°C showed no degradation, confirming the formulation's stability which can be achieved with proper choice of excipients and optimization parameters. Future research should explore higher poloxamer concentrations with various mucoadhesive combinations for AG-NLC in-situ gels. In conclusion, this intranasal AG-NLC in-situ gel holds promise for enhanced bioavailability and antidepressant activity, warranting further pharmacokinetic and cytotoxicity studies to expand its therapeutic potential.

Abbreviations

1. 2FI – Two-Factor Interaction
2. AF1-AF9 – Agomelatine-loaded Nanostructured Lipid Carrier Formulations 
3. AG – Agomelatine
4. ANOVA – Analysis of variance 
5. ATR – Attenuated Total Reflectance
6. BBB – Blood-Brain Barrier
7. BCS – Biopharmaceutical Classification System
8. EE – Entrapment Efficiency 
9. GI – Gastro Intestinal
10. HLB – Hydrophilic Lipophilic Balance
11. ICH – International Council for Harmonization
12. NLCG1-NLCG5 – AG-loaded Nanostructured Lipid Carrier Gel Formulations
13. NLCs – Nanostructured Lipid Carriers
14. PBS – Phosphate Buffer Saline
15. PDI – Polydispersity Index
16. PS – Particle Size 
17. SEM – Scanning Electron Microscopy 
18. SLN – Solid Lipid Nanoparticles
19. UV – Ultraviolet
20. ZP – Zeta Potential 

Conflict of Interest: The authors declare no conflict of interest.

Ethical Approval: No ethical approval was necessary for this study.

Funding/Grant Support: None

Informed Consent Statement: Not applicable. 

Data Availability Statement: The data supporting in this paper are available on the request from corresponding author. 

Acknowledgements: We owe our profound gratitude to Dr. M Srujan Kumar, Director, SS Pharma Labs Pvt. Ltd., Hyderabad, India for providing support in completing experimental design and formulation for current research work.

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