Entacapone Nanoemulsion: Formulation Design, Optimization, and Evaluation

doi:10.21203/rs.3.rs-4081418/v1

Download PDF

Research Article

Entacapone Nanoemulsion: Formulation Design, Optimization, and Evaluation

https://doi.org/10.21203/rs.3.rs-4081418/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Entacapone is utilized as an adjunct to levodopa therapy for the treatment of Parkinson's syndrome. According to the Biopharmaceutics Classification System, it is classified as a class IV drug. The solubility of a substance can be enhanced by utilizing nanoemulsion, which can also effectively traverse the blood-brain barrier owing to its nanoscale dimensions. The formulation utilized various proportions of Capmul Medium Chain Mono and Diglycerides as the oil phase, Pluronic F127, and Phospholipin 90 as hydrophilic and lipophilic surfactants. Optimization was performed using 3² factorial designs in Design Expert^®8.0.5.2 software, incorporating mixing speed, time, and sonication parameters. The nanoemulsion exhibited an average particle size of 120.8±1.9nm, with a low polydispersity index of 0.144, indicating a uniform globule size. The zeta potential suggested good stability, while the XRD pattern indicated decreased drug crystallinity. The TEM images confirm that the size of the particles falls within the range of 120–150 nm and there is no evidence of aggregation. The drug was released at a rate of 80.33±0.92% for 8 hours. The current study demonstrates enhancements in the solubility and stability of formulated nanoemulsions designed for oral delivery.

Entacapone

Nanoemulsion

Capmul MCM

Pluronic F127

Oral route

Nanoemulsions are emulsions that have been reduced to a nano-sized scale to enhance the delivery of active pharmaceutical ingredients. These are thermodynamically stable isotropic systems where two immiscible liquids are combined to create a single phase by utilizing an emulsifying agent, such as a surfactant or co-surfactant. The size of the droplets in nanoemulsion typically ranges from 20 to 200 nm [1, 2]. The primary distinction between emulsion and nanoemulsion resides in the dimensions and morphology of the dispersed particles within the continuous phase. By enhancing the body's ability to absorb drugs, it can take the place of liposomes and vesicles. Additionally, it is both non-toxic and non-irritating, and it exhibits enhanced physical stability [3]. Nanoemulsions consist of tiny droplets with a small size, resulting in a larger surface area that enhances absorption. The formulation of this substance can take various forms, including foams, creams, liquids, and sprays [4, 5]. It enhances the absorption of oil-based supplements in cell culture technology. It aids in dissolving drugs that are soluble in lipids. It is beneficial for taste masking and requires a minimal energy input [6, 7].

Parkinson's disease is a prevalent neurodegenerative disorder that leads to significant impairment and is a growing worldwide public health concern due to its impact on motor, non-motor, and cognitive functions [8]. Parkinson's disease ranks as the second most prevalent neurodegenerative disorder, following Alzheimer's disease. Parkinson's disease commonly manifests in individuals aged 55 to 65 and affects approximately 1–2% of individuals over the age of 60, with a prevalence of 3.5% in the 85 to 89 age group. The prevalence of this condition affects approximately 0.3% of the general population, with a higher occurrence among men compared to women, with a ratio of 1.5 to 1.0 [9]. Nanocarriers possessing distinctive physicochemical properties can penetrate the blood-brain barrier through various mechanisms. In recent times, various innovative approaches to nanotechnology have emerged. One such approach involves enhancing the effectiveness of therapeutics by attaching them to nanocarriers that are functionalized with appropriate ligands. This strategy enables targeted delivery to specific sites in the body, particularly the brain, thereby improving the treatment of Parkinson's disease and minimizing any adverse effects [10].

Entacapone, a drug containing nitrocatechol, has received approval for clinical application in patients diagnosed with Parkinson's disease. By stopping the enzyme Catechol-O-Methyl Transferase (COMT) from working, it stops the breakdown of dopamine and levodopa [11]. A COMT inhibitor called Entacapone is used along with levodopa and carbidopa to treat Parkinson's disease. As the pH increases, the solubility of Entacapone in water also increases. It was noticed that when ingested orally, the drug has low bioavailability (29–46%) and significant variability in absorption across individuals. Inadequate membrane permeability, insufficient aqueous solubility in gastrointestinal fluids, and the first-pass effect can all contribute to suboptimal bioavailability [12–14]. According to the biopharmaceutics classification system [15–20], Entacapone is categorized as a class IV medication. Reports indicate that nanosized formulations improve the permeability and solubility of water while also preventing first-pass effects. Hence, enhancing the solubility and dissolution rate of Entacapone could lead to heightened bioavailability and therapeutic efficacy.

Our current study work focuses on exploring the formulation and development of Entacapone nanoemulsion, which has not been investigated previously. The main objective of the study was to investigate the potential of nanoemulsion as a delivery system for Entacapone in the treatment of Parkinson's disease. The second goal was to study and describe the nanoemulsion using different methods, including Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), measuring the size of the drug particles, zeta potential analysis, and stability studies.

Entacapone is a gift sample from Drugs India in Hyderabad, India. Zirconium oxide beads were received from Lupin Pharmaceuticals Ltd. in Pune, India as a gift sample. Sigma Chemicals in Mumbai, India provided Pluronic F127 and Pluronic F68. Disodium hydrogen phosphate, sodium hydroxide, and tween 80 (Polysorbate 80) were acquired from S.D. Fine chem. in Nellore, India. Hydroxypropyl methylcellulose (HPMC K15 M) was Colorcon Ltd. in Mumbai, India. All other substances used in this study were of the analytical grade.

Calibration plot in using Ultraviolet Spectroscopy (UV)

Methanol

A standard stock solution of 100 µg/ml was prepared by dissolving 10 mg of Entacapone in 100 ml of methanol. Then UV spectrophotometric analysis method was developed by first scanning the solution of Entacapone (10 µg/ml) in the ultraviolet range between 200 nm and 600 nm and determined its λ_max. A stock solution of Entacapone was pipetted into 10 ml volumetric flasks and the volume was made up to 10 ml with methanol. Working standard concentrations ranging from 4–20 µg/ml were prepared from the stock solution. The solutions were mixed using a vortex mixer and their absorbances were measured at λ_max using methanol as blank on Shimadzu 1700 UV-Visible Spectrophotometer. A calibration curve was plotted by using the obtained absorbances. The above procedure was repeated three times.

0.1N HCl and methanol

Entacapone 10 mg in 100 ml of methanol was dissolved to provide a standard stock solution (100 g/ml). Then, by first measuring the λ_max of the Entacapone solution (10 µg/ml) in the UV region between 200 nm and 600 nm, a UV spectrophotometric analysis method was created. The stock solution of Entacapone was pipetted into 10 ml volumetric flasks, and the volume was increased to 10 ml with methanol to produce final concentrations ranging from 4 to 25 grams per millilitre. The solutions were combined using a vortex mixer, and their absorbances were measured at maximum with methanol used as the blank. Three times the aforementioned process was carried out. Analysis of standard concentrations ranging 1 to 10 µg/ml were performed.

pH 7.2 phosphate buffer

10 mg of Entacapone was dissolved in 100 ml of pH 7.2 phosphate buffer to create a standard stock solution (100 µg/ml). Then, by first scanning the solution of Entacapone (10 µg/ml) in the ultraviolet region between 200 and 600 nm and calculating its maximum, a UV-spectrophotometric technique of analysis was created. To achieve final concentrations ranging from 2 to 16 g/ml, suitable aliquots of the Entacapone stock solution were pipetted into 10-ml volumetric flasks, and the volume was topped off with pH-7.2 phosphate buffer. On a Shimadzu 1700 UV-Visible Spectrophotometer, the solutions were combined using a vortex mixer, and their absorbances were measured at maximum with pH 7.2 phosphate buffer as a blank. A calibration curve was then constructed. Three times the aforementioned process was repeated.

Preparation of nanoemulsion

The described technique was used to create the entacapone nanoemulsion formulation [30–32]. For the trial of the oil phase, the entacapone (0.12% w/v) and necessary dosage (0.5% w/v) of lipophilic surfactant (Phospholipin90) were dissolved in the chosen oil, i.e., Capmul MCM (15% v/v), with stirring. The required amount of distilled water (85%) was combined with hydrophilic surfactant (0.5% w/v Pluronic F127) in the aqueous phase. The oil phase was introduced to the aqueous phase dropwise while premixing with Ultra-turrax at 9500 rpm after both phases had warmed to 70°C. The premixing process took 10 minutes (2 rounds of 5 minutes). After acquiring the pre-emulsion, it was ultrasonically sonicated for 9 minutes (3 cycles of 3 minutes) at 80% amplitude and 0.6 duty cycles. The obtained nanoemulsion was moved.

Solubility of entacapone in different oils

To attain equilibrium, entacapone was added to the chosen oils, the mixture was vortexed for 2 minutes, and then the mixture was agitated for 48 hours on a mechanical stirrer. After the combination was centrifuged at 25000 rpm for 10 minutes to separate the undissolved drug, the oil solution's supernatant was removed. The absorbance was then measured against a corresponding blank using a UV visible spectrophotometer (UV Shimadzu 1700) at 384 nm. The calibration curve in methanol was used to determine the entacapone concentration.

Optimization of process parameters

High-speed mixing and sonication time

Oil (Capmul MCM) was used to manufacture all batches, demonstrating the drug's maximal solubility. According to the existing literature on the manufacture of nanoemulsions, the emulsion formulation for preliminary optimization was 15% v/v oil (Capmul MCM), 1% w/v PluronicF127, 1% w/v soybean PC (phospholipon 90G), and 85% v/v water. The effects of high-speed mixing (by Ultra-Turrax) on the pre-emulsion's globule/droplet size were first investigated. The droplet size obtained with various speeds (9500 and 11500) and periods (1, 3, 5, 10, and 15 min) was measured in this experiment. The impact of sonication time on globule size was then measured. A 100W, 30 kHz probe sonicator (LABSONIC®M) was used to emulsify. Half of the probe tip was submerged in the pre-emulsion. 100W of sonication was used (i.e., 80 amplitudes at 0.6 cycles per second). A 100W, 30 kHz probe sonicator (LABSONIC®M) was used to emulsify. Half of the probe tip was submerged in the pre-emulsion. 100W of sonication was used (i.e., 80 amplitudes at 0.6 cycles per second). Twenty millilitres of pre-emulsion (20 ml) were treated for 18 minutes of sonication, with a 3-minute break between each cycle of sonication. The globule size and PDI were calculated following each cycle. The readings were triple recorded.

Selection of surfactants

Following the selection of the sonication and mixing speed parameters, the formulation parameters were optimized. A non-ionic surfactant was chosen based on the stability of the emulsion as seen over 15 days. Tween 80 and Pluronic F127, two nonionic surfactants frequently employed to create nanoemulsions, were tested at various doses. After choosing a lipophilic surfactant, a hydrophilic surfactant was chosen. Two widely used lipophilic surfactants, soya PC and egg PC, were tested in this study at various doses. After seeing the appearance/phase separation, a lipophilic surfactant was chosen for additional research.

Factorial Design and Optimization

According to preliminary investigations, the polydispersity index (PDI), particle size, and stability of the nanoemulsion were significantly influenced by the percentage of oil phase (X₁) and the ratio of phospholipin90: pluronic F127 (X₂). Consequently, a 3²-factorial design was employed to determine the lowest PDI, smallest particle size, and highest stability. Table 1 contains the factorial design formulation parameters and Table 2 shows formulation factors of nanoemulsion prepared as per 3² factorial designs. The statease software was used to collect two-dimensional contour plots and three-dimensional response surface plots arising from equations.

Table 1

Coded Values of the formulation parameters of entacapone Nanoemulsions
Coded Values	Actual values
Coded Values	X₁	X₂
-1 0 1	10% v/v 15% v/v 20% v/v	1:1 1:2 2:1
X₁—Oil concentration, X₂—Ratio of Phospholipon 90G: Pluronic F127

Table 2

Formulation factors of nanoemulsion prepared as per 3² factorial designs
Formulation Code	Factors
Formulation Code	Oil percentage– X₁ (% v/v)	Ratio of PL90G: PF127 X₂
Entacapone 1 (-1, -1) Entacapone 2 (-1,0) Entacapone 3 (-1,1) Entacapone 4 (0, -1) Entacapone 5 (0, 0) Entacapone 6 (0,1) Entacapone 7 (1, -1) Entacapone 8 (1, 0) Entacapone 9 (1, 1)	10 10 10 15 15 15 20 20 20	1:1 1:2 2:1 1:1 1:2 2:1 1:1 1:2 2:1

Characterization of entacapone nanoemulsion

Measurement of particle size

By using the Zetasizer (NanoZS, Malvern Instruments, UK) and photon correlation spectroscopy (PCS), particle size analysis was carried out. The polydispersity Index (PI) and mean particle size are obtained via photon correlation spectroscopy. The particle size distribution and sample width are both described by PDI. Dilution was used to determine the particle size analysis. Deionized water was used to dilute the sample, which amounted to about 100 µl, to 10 ml. The PDI and particle size data were obtained by averaging the findings from 10–20 measurement cycles at a 90° angle at 25° C in a disposable cell with a 10 mm diameter. Between 50 and 500 kcps, the measurement maintained a moderate particle count rate [33]. To get enough light scattering, all of the samples were diluted with double-distilled water before testing.

Measurement of surface charge

Zetasizer (NanoZS, Malvern Instruments, UK) was used to assess surface charge (Zeta potential). Following the dilution with deionized water mentioned above, the measurements were carried out. Using the Helmholtz-Smoluchowsky equation, the Zeta potential values were calculated from the electric mobility of the oil globules. At a field strength of 20 V/cm and three different temperatures, the measurements were made.

Morphological examination by Transmission Electron Microscope (TEM)

By using TEM, the morphology of the oil globules in nanoemulsion was visualized. A drop of the nanoemulsion was placed on a piece of parafilm after 10-fold dilution in distilled water. A carbon-coated grid was placed on top of the drop and left for 1 min. With filter paper excess fluid was removed. If necessary, negative staining was then performed by placing the grid on a drop of 2% phosphotungsten acid (PTA) for 1 min. The grid was examined under a transmission electron microscope (model JEM-100S, Joel, Tokyo, Japan) at an accelerated voltage of 20 kV.

Drug content and pH

The percentage of entacapone discovered in nanoemulsion to the theoretical amount of the drug administered was used to measure encapsulation efficiency. After an appropriate methanol dilution, the drug content was measured using a UV spectrophotometer at 384 nm. A pH meter (PICO +, Lab India) was used to gauge the nanoemulsions' pH.

Viscosity Measurement

The rheological measurements were performed using the Ostwald Viscometer. Approximately, 15–20 ml of nanoemulsion was poured into the filling tube and transferred to the capillary tube by gentle suction. The time needed for the nanoemulsion to flow from the upper spot to the lower area of the capillary tube was recorded. The values for reference liquid, i.e., water, were also recorded and then from the densities and time reading, the viscosity of the nanoemulsion was calculated.

FT-IR spectroscopy

To ascertain the molecular interaction between the drug and excipients, IR spectroscopy was employed. All of the aforementioned physical combinations and drug samples were combined with dried KBr in a ratio of 1:100 (according to the DSC analysis). By applying 10 tonnes of pressure for 2 minutes, the mixture was compacted to a 12 mm semi-transparent disc. An FTIR spectrometer (8400S, Shimadzu, Japan) was used to record the FTIR spectra in the 4000 − 400 cm^− 1 wavelength region.

Differential scanning calorimetry (DSC) studies

The dry vial was filled with physical combinations of pharmaceuticals and drugs with excipients. The sealed vials were kept in a stability room for four weeks at 40°C and 75% RH. Vials were taken out of the stability chamber after four weeks and put under an interaction examination. DSC was used to explore the interactions between drugs and polymers. Thermograms of pure pharmaceuticals, medications containing polymer, and mixes of drugs containing excipients were taken for this investigation. In a dynamic nitrogen atmosphere, heating was carried out at a rate of 10°C per minute over a temperature range of 30 to 340°C and as a guide, an empty sealed aluminium pan was used.

X-Ray diffraction

Another factor affecting a compound's stability and dissolution is its crystalline state. To demonstrate how milling affected the physical state of entacapone, the sample’s crystalline condition was assessed. It has been used to examine potential changes in the inner structure.

In-vitro release

Entacapone nanoemulsion and simple drug suspension in-vitro release tests were carried out in 0.1 N HCl (pH 1.2). For in-vitro release investigations, a dialysis membrane with a pore size of 2.4 nm (molecular weight cut-off between 12,000 Da) was employed. A dialysis bag was filled with 1ml of nanoemulsion, which contained the equivalent of 0.5 mg of medication, and the bag was sealed at both ends before being placed in a beaker with 40 ml of receptor media (pH 1.2 buffer), which was kept at 37°C. To keep the recipient compartment's volume constant, samples were taken at regular intervals and an equal volume of media was supplied each time after sampling. Using a UV spectrophotometer, the quantity of medication in the samples was determined at an absorption maximum of 315 nm (UV, Shimadzu 1700).

Stability

Over three months at 2–8 and 25°C, the stability of the nanoemulsion was tested for drug content and particle size. To prevent double scattering, the nanoemulsion was diluted with distilled water. After 1 hour, the particle size distribution of the mixture was assessed using the Zetasizer (NanoZS, Malvern Instruments, UK). Additionally, ocular observations for phase separation, cracking, or screaming were made. The stability of high-speed centrifugation was tested for 10 minutes at various speeds ranging from 2000 to 10,000 rpm.

Calibration plot in using Ultraviolet spectroscopy

Methanol

When scanned in the UV region between 200 and 600 nm, entacapone in methanol revealed distinctive spectra. The analytical wavelength was determined to be 384 nm because the scan revealed this to be the absorption maximum. Between 4 and 20 g/ml, Beer's law was followed. The experimental data was subjected to regression analysis. The standard curve's regression equation was y = 0.0597x − 0.0013. The developed method's correlation coefficient was discovered to be 0.9999, indicating that there was a linear relationship between drug concentration and absorbance. The developed UV spectrometric analysis method for entacapone is shown with parameters demonstrating linearity.

0.1 N HCl and methanol (9:1)

When examined in the ultraviolet region between 200 and 600 nm, the spectrum of entacapone in 0.1 N HCl and methanol (9:1) displayed a distinctive pattern. The analytical wavelength was chosen based on the scan, which indicated that the absorption maximum occurred at 315 nm. Between 4 and 20 g/ml, Beer's law was followed. The experimental data was subjected to regression analysis. The standard curve's regression equation was y = 0.0629x − 0.0081. The devised method's correlation coefficient was determined to be 0.9995, indicating that there was a linear relationship between drug concentration and absorbance. The Table 4 lists the parameters for the entacapone UV spectrometric method of analysis that was developed.

pH 7.2 phosphate buffer

When scanned in the UV region between 200 and 600 nm, entacapone in pH 7.2 phosphate buffer displayed spectra distinctive spectrum. The analytical wavelength was determined to be 384 nm because the scan revealed this to be the absorption maximum. Between 2 and 16 g/ml, Beer's law was followed. The experimental data was subjected to regression analysis. The standard curve's regression equation was y = 0.0629x − 0.0081. The developed method's correlation coefficient was determined to be 0.9995, indicating that there was a linear relationship between drug concentration and absorbance. The table below lists the parameters for the entacapone UV spectrometric method of analysis.

Preparation of nanoemulsion

Optimization of process parameters High-speed mixing and sonication time

The results of a study on the impact of high-speed mixing (at 9500 rpm and 11500 rpm) on pre-emulsion globule size are shown in Table 3. After 5 minutes of vigorous mixing, the nano emulsion’s globule size was found to be 202.05.8 nm at 9500 rpm and 2054.2 nm at 11500 rpm. The polydispersity index (PDI), which indicates non-uniform distribution, was greater than 0.250 in both instances. A globule size of 200.52.0 and a PDI of 0.270 were attained at 9500 rpm after 10 minutes of high-speed mixing. Additionally, increasing high-speed mixing to 15 minutes did not significantly reduce globule size. Thus, it was decided that 10 minutes of high-speed mixing would be sufficient to produce a pre-emulsion containing globules in the nanometer range. To research stability, the pre-emulsion samples were kept at room temperature. However, after a week, there was a minor phase separation, indicating that high-speed mixing alone was insufficient to produce a stable nanoemulsion. Ultrasonication was therefore also tried.

Table 3

Effect of high-speed mixing on globule size of pre-emulsion
High-speed mixing	Globule size	PDI
5 min (9500 rpm) 5 min (11500 rpm) 10 min (9500 rpm) 15 min (9500 rpm)	205.0 ± 4.2 202.0 ± 5.8 200.5 ± 2.0 197.4 ± 4.2	0.394 0.399 0.270 0.264

The impact of the sonication time was investigated after the high-speed mixing speed and time were set in stone; the results are shown in Table 4. Based on our prior experiences, sonication was performed at an intermediate power application (80% amplitude). The globule size of the nanoemulsion was found to decrease with sonication time up to 9 min, after which there was barely any reduction in globule size.

Table 4

Effect of sonication time on globule size of nanoemulsion
Sonication time*	Globule size	PDI
3 min 6 min 9 min 12 min 15 min	169.4 ± 6.7 163.4 ± 3.0 127.4 ± 0.8 132.4 ± 1.2 203.0 ± 11.4	0.247 0.225 0.060 0.048 0.202
*High-speed mixing at 9500 rpm for 10min, #duty cycle 0.6sec, 80% amplitude

Particle size increased above 200 at a longer sonication period (15 min), which may have been caused by over-processing, which is brought on by an increase in emulsion droplet coalescence at a greater shear rate. The smallest globule size (127.40.8) and low PDI (0.060) were reached at 9 minutes of sonication, and this was therefore regarded as the ideal time to produce a nanoemulsion with uniform distribution.

Selection of surfactants

After the selection of mixing speed and sonication parameters, formulation parameters were optimized. The selection of surfactant was carried out based on the stability of the emulsion observed for 10 days. Two nonionic surfactants commonly used for the preparation of nanoemulsion i.e., Tween 80 and Pluronic F127 were tried at 1–3% and 3–7% concentration respectively. These concentrations were selected based on the literature. The results obtained from these studies are recorded in Table 5.

Table 5

Selection of non-ionic surfactant for nanoemulsion
Surfactant	Concentration	Day 1	Day 5	Day 10
Pluronic F127	1%	Milky & stable	Milky & stable	Milky & stable
	2%	Milky & stable	Milky & stable	Milky & stable
	3%	Milky & stable	Milky & stable	Milky & stable
Tween 80	3%	Milky & stable	Phase Separation	-
	5%	Milky & stable	Phase separation	Phase Separation Phase Separation
	7%	Milky & stable	Milky & stable	Phase Separation Phase Separation

From these results, it was clear that Tween 80 could not produce stable nanoemulsion. However, with Pluronic F127, stable nanoemulsion was obtained at all the concentrations. Hence, Pluronic F127 was selected as a hydrophilic surfactant for further studies.

Effect of formulation variables on the response parameters

With the aid of the Design Expert® 8.0.5.2 software, numerous polynomial equations, response surfaces, and contour plots were produced after data from all 9 formulations created according to the 3² Factorial designs had been analyzed. Table 6, 7, 8 & 9 discuss the data from the software and show how variables affect the corresponding response parameters (Y1 and Y2).

Table 6

Response parameters for formulations of nanoemulsion prepared as per 3² factorial designs.
Formulation code	Factors		Globule Size – Day 0 (nm) [Y1]	Globule Size – Day 15 (nm) [Y2]
Formulation code	Oil percentage. – X1 (% v/v)	Ratio of PL90G: PF127 - X2	Globule Size – Day 0 (nm) [Y1]	Globule Size – Day 15 (nm) [Y2]
Entacapone 1 (-1,-1) Entacapone 2 (-1,0) Entacapone 3 (-1,1) Entacapone 4 (0, -1) Entacapone 5 (0, 0) Entacapone 6 (0,1) Entacapone 7 (1,-1) Entacapone 8 (1, 0) Entacapone 9 (1, 1)	10 10 10 15 15 15 20 20 20	1:1 1:2 2:1 1:1 1:2 2:1 1:1 1:2 2:1	110 87 114 124 119 138 168 128 156	112 82 108 132 124 154 256 182 312

Table 7

Observed and Predicted values of response parameters
Batch	Response parameters
	Y₁			Y₂
	Observed	Predicted	%RE	Observed	Predicted	%RE
Entacapone 1 (-1,-1) Entacapone 2 (-1,0) Entacapone 3 (-1,1) Entacapone 4 (0, -1) Entacapone 5 (0, 0) Entacapone 6 (0,1) Entacapone 7 (1,-1) Entacapone 8 (1, 0) Entacapone 9 (1, 1)	110 87 114 124 119 138 168 128 156	106.5 87.8 116.5 133.8 111.2 135.8 161.5 134.8 155.5	3.28 0.9 2.1 7.3 7.0 1.6 4.0 5.0 0.3	112 76 108 132 104 154 256 264 312	111.6 78 106.3 128 109.3 152.6 260.3 256.6 315	0.36 2.56 1.60 3.12 4.85 0.92 1.65 2.88 0.95
% RE= % Relative Error Calculated % RE = Observed (Actual) – Predicted / Predicted * 100

Optimum Formulation

The ideal formulation parameters were produced using a numerical optimization technique based on the desirability approach. The procedure was tuned for the dependent (response) variables Y1-Y2, and the tuned formula was obtained by maintaining the mean particle diameter between days 0 and 15 in the range of 100 to 150 nm. The formulation (entacapone4) was considered the optimal choice since it satisfied all the established requirements [34–36].

To assess the predictability of the response surface model, a new optimized formulation (as per formula entacapone4) was created and tested for the responses (Y1, and Y2). The result in Table 10 shows a strong correlation between experimental and anticipated values, demonstrating the model's applicability and validity. Indicating that the Response Surface Methodology (RSM) optimization technique was suitable for optimizing entacapone nanoemulsion, the anticipated inaccuracy of the Y1 and Y2 variables was less than 8%.

Table 8

Optimized entacapone Nanoemulsion
Ingredients	Concentration
Entacapone Concentration Capmul MCM (Oil) Phospholipon 90 (Lipophilic surfactant) PluronicF127 (Hydrophilic surfactant) Distilled water	0.12% w/v 15% v/v 0.5% w/v 0.5% w/v 85% v/v

Table 9

The predicted and observed response variables of the optimal entacapone Nanoemulsion
Response	Y1 (nm)	Y2 (nm)
Predicted Observed	133.8 124.0 ± 1.6	140.8 132.0 ± 11

Solubility of entacapone in Oils

A calibration curve in methanol was used to estimate the solubility of entacapone in various oils [y = 0.0576x- 0.0415 (r2 = 0.9993)]. The solubility of entacapone in various oils is depicted in Fig. 1. When compared to other oils, Captex 500 demonstrated the maximum solubility of entacapone, however, the nanoemulsion made with it phase separated after only two days. Therefore, Capmul MCM was chosen for the creation of the nanoemulsion since it had superior solubility than the other remaining oils.

Characterization of entacapone nanoemulsion

Measurement of surface charge

Figure displays the outcomes of droplet size and zeta potential measurements of nanoemulsions. The entacapone-loaded nanoemulsions were found to have an average particle size diameter of 120.81.9 nm. The size of the droplets in the drug-loaded and blank nanoemulsions did not significantly differ. Both formulations had a polydispersity index (PI) of 0.144, which is below 0.2, and this unimodal distribution denotes globule size uniformity.

The synthesized formulation's zeta potential was discovered to be -20.6 0.8 mV. If stabilized by a single mechanism, nanoformulations with a zeta potential of 30 mV are regarded as stable; if stabilized by a combination of these two mechanisms, they have a zeta potential of 20 mV [37]. Because there were multiple mechanisms at work to stabilize the created nanoemulsion, a zeta potential of roughly 20 mV might offer adequate stability. The stability research confirms that prepared nanoemulsions are stabilized at a zeta potential of -20.60.8 mV.

Morphological examination by TEM

Sharp endothermic peaks at 155 and 159°C were visible in the bulk entacapone sample using a DSC scan (Fig. 5), which were caused by the drug melting. Entacapone nanoemulsion prevented these peaks from appearing, which also pointed to a notable decrease in the drug's crystallinity. Additionally, the absence of entacapone's signature peaks in the nanoemulsion of the drug suggests the creation of an amorphous end-product. The shape of the oil droplets in the nanoemulsion formulations must be studied using TEM analysis, as must any drug precipitation that occurs when the aqueous phase is added. The prepared nano emulsion’s shape and droplet size were assessed by TEM. The globules were virtually spherical and had sizes between 120 and 150 nm, as seen in the TEM image (Fig. 5). The globules were separated and did not exhibit an aggregation tendency. The globule size seen in the TEM image matched the outcome of the DLS analysis.

To assess the physicochemical characteristics of the system, significant characteristics of the nanoemulsion, such as drug content, pH, and viscosity, were investigated under published methodologies. It was discovered that the drug content was 99.40.8%. The nanoemulsions' pH was discovered to be 5.5 +/- 0.2, indicating that oral delivery was appropriate. The nano emulsion’s low viscosity (1.63 0.02 cp), which indicates appropriateness for oral administration, was discovered.

Drug content and pH

To assess the physicochemical characteristics of the system, significant characteristics of the nanoemulsion, such as drug content, pH, and viscosity, were investigated under published methodologies. It was discovered that the drug content was 99.40.8%. The nanoemulsions’ pH was discovered to be 5.5 +/- 0.2, indicating that oral delivery was appropriate.

Viscosity measurement

To assess the physicochemical characteristics of the system, a significant characteristic of the nanoemulsion, such as viscosity, was investigated under published methodologies. The ’nano emulsion’s low viscosity (1.63 0.02 cp) indicated that it was suitable for oral administration.

FT-IR study

Figure 6 and Table 10 show the FT-IR spectra and functional groups of entacapone, Pluronic, and Phospholipin90 at the specified wavelength (cm^− 1). The peaks in the spectrum are 2937.04 cm^− 1 for C-H stretching (aliphatic), 2984.39 cm^− 1 for C-H stretching (aromatic), 3600.81 cm^− 1 for N-H stretching, 1618.01 cm^− 1 for N-H bending, and 1638.04 cm^− 1 for C = N stretching.

Table 10

FT-IR Data determining changes in functional groups of entacapone
S. No	Concentration (µg/mL)	Mean absorbance ± SD
1 2 3 4 5	2937.04 2984.39 3600.81 1618.01 1638.04	C-H stretching (Aliphatic) C-H stretching (Aromatic) N-H stretching N-H Bending C = N stretching

DSC Studies

DSC was also carried out for the entacapone plain medication to further establish the physical state. In this instance, the bulk entacapone sample's DSC scan revealed distinct endothermic peaks at 155 and 159°C (Fig. 7) associated with the drug's melting.

X-Ray Diffraction

Another element influencing a compound's stability and dissolution is its crystalline state. To demonstrate how milling affected the physical state of entacapone, the sample's crystalline state was examined. Entacapone crystals' potential internal structural alterations have been examined using X-ray diffraction. Figure 8 shows the XRD patterns for bulk entacapone particles.

The results indicated that entacapone nanoemulsions significantly decreased crystallinity compared to regular medication. All major peaks associated with PD disappeared in the nanoemulsions. It is depicted in Fig. 9.

In-vitro Release

Figure 10. shows the invitro release characteristics of simple drug suspension and nanoemulsion at pH 1.2. According to the in-vitro release experiments, the drug released more when compared to a pH 1.2 plain drug suspension. While nanoemulsion formulation demonstrated 31.770.92% drug release in 60 minutes, plain drug suspension only demonstrated 25.050.44% drug release. At 8 hours, the plain drug suspension revealed a 62.12% drug release, whereas the nanoemulsion formulation revealed an 80.330.92% drug release, indicating improved drug release that may be attributed to increased entacapone solubility and dissolution rate, which may in turn be caused by the nano emulsion’s small droplet size and surface characteristics. Drug release with time for nanoemulsions was reported to have an overall increasing release.

The release profiles were then used to characterize the release by fitting them into various exponential equations, including zero order, first order, Higuchi, Hixson-Crowell, and Korsmeyer-Peppas ( Table 11). The correlation coefficient was used to determine the model that the created formulation used. The release exponent value obtained from the Korsmeyer-Peppas model was used to identify the release mechanism used by these formulations. At pH 1.2, the ENE indicated abnormal transport pathways with a value of "n" between 0.5 and 1.0.

Table 11

Coefficient of correlation for various models
Formulation	First order	Zero-order	Higuchi Model	Hixson model	Korsmeyer-Peppas model*
Plain Drug pH 1.2 Nano Emulsion pH 1.2	0.9791 0.9882	0.9613 0.9806	0.9917 0.9889	0.9588 0.9867	0.9941 (0.5454) 0.9875 (0.5054)

Stability

For three months at 2–8°C and RT (25–30°C), the stability of the nanoemulsion in terms of particle size distribution and drug content was observed. Under both circumstances, the nanoemulsion formulation demonstrated physical stability for three months. Table 12 lists the medication concentration and nanoemulsion particle size at various time points. After three months under both circumstances, it was discovered that there was no discernible difference in the nano emulsion’s droplet size, indicating that it was suitable for storage under either environment.

Table 12

Stability of nanoemulsion at RT and cold conditions (2–8°C)
Time	Drug content (%)	Drug content (%)	Globule size (nm)	Globule size (nm)
Time	(2–8°C)	(RT)	(RT)	(2–8°C)
Initial 1 month 2 months 3 months	99.7 ± 1.3 99.5 ± 1.1 99.5 ± 1.0 98.9 ± 1.6	99.9 ± 1.2 99.5 ± 1.1 99.5 ± 1.5 98.8 ± 1.6	120 ± 4 123 ± 2 126 ± 6 128 ± 4	120 ± 4 131 ± 8 136 ± 5 138 ± 4

The viscosity of the nanoemulsion is another factor that affects its stability. Within three months, there was no change in the viscosity or content of the medicine. On undisturbed standing, the emulsion was discovered to be stable without any breaking, creaming, or phase separation and could withstand high-speed centrifugation from 2000 rpm to 10000 rpm. The nanoemulsion formulation was therefore reliable and appropriate for RT storage.

The Entacapone nanoemulsion was developed through ultrasonication and optimization of parameters such as high-speed mixing time, surfactant choice, and sonication time. The formulation consisted of 15% Capmul MCM, 0.5% phospholipon90, 0.5% Pluronic F68, 0.12% medication, and 85% distilled water. The tests included particle size, zeta potential, pH, surface morphology, drug content, viscosity, in vitro drug release, and nanoemulsion stability. The nanoemulsions were uniform in size, with a zeta potential of -20.6 ± 0.8 mV, a drug content of 99.4 ± 0.8%, a pH of 5.5 ± 0.2, and a viscosity of 1.63 ± 0.02 cp. At pH 1.2, nanoemulsions release drugs more efficiently than suspensions. As a result, we conclude that the preparation of entacapone nanoemulsion can be an effective method for improving the solubility, stability and therapeutic efficacy of formulated nanoemulsions intended for oral delivery.

COMT: Catechol-O-methyltransferase, HPMC: Hydroxypropyl methylcellulose, UV: Ultraviolet, XRD: X-Ray Diffraction, FTIR: Fourier-transform infrared spectroscopy, DSC: Differential Scanning Calorimetry, PDI: Polydispersity Index, PCS: Photon Correlation Spectroscopy, PI: Polydispersity Index, TEM: Transmission Electron Microscope, RSM: Response Surface Methodology, DLS: Dynamic Light Scattering.

I hereby declare that this submission is entirely my work, in my own words, and that all sources used in the research are fully acknowledged and all quotations properly identified.

Funding

No funding was received to assist with the preparation of this manuscript

Competing interests

The authors have no relevant financial or non-financial interests to disclose.

Consent for publication

All the authors have read and agreed to the final copy of the findings as contained in the manuscript.

Author contribution

Conceptualization: Kusuma Praveen Kumar; Methodology: Garla Venkateswarlu; Formal analysis and investigation: Garla Venkateswarlu, Shahul Hussain Shaik; Writing - original draft preparation: Dalapathi Gugulothu, Malakapogu Ravindra Babu; Writing - review and editing: Kusuma Praveen Kumar, SK Abdul Rahaman, N Deepa; Supervision: Kusuma Praveen Kumar;

Jaiswal M, Dudhe R, Sharma PK (2015) Nanoemulsion: an advanced mode of drug delivery system. 3 Biotech 5:123–127. https://doi.org/10.1007/s13205-014-0214-0
Sah MK, Gautam B, Pokhrel KP, et al (2023) Quantification of the Quercetin Nanoemulsion Technique Using Various Parameters. Molecules 28:2540. https://doi.org/10.3390/molecules28062540
Bouchemal K, Briançon S, Perrier E, Fessi H (2004) Nano-emulsion formulation using spontaneous emulsification: solvent, oil and surfactant optimisation. Int J Pharm 280:241–251. https://doi.org/10.1016/j.ijpharm.2004.05.016
Kim M, Jiang LH, Wilson HL, et al (2001) Proteomic and functional evidence for a P2X7 receptor signalling complex. EMBO J 20:6347–6358. https://doi.org/10.1093/emboj/20.22.6347
Preeti null, Sambhakar S, Malik R, et al (2023) Nanoemulsion: An Emerging Novel Technology for Improving the Bioavailability of Drugs. Scientifica (Cairo) 2023:6640103. https://doi.org/10.1155/2023/6640103
Mohite P, Singh S, Pawar A, et al (2023) Lipid-based oral formulation in capsules to improve the delivery of poorly water-soluble drugs. Front Drug Deliv 3:1232012. https://doi.org/10.3389/fddev.2023.1232012
Nguyen VH, Thuy VN, Van TV, et al (2022) Nanostructured lipid carriers and their potential applications for versatile drug delivery via oral administration. OpenNano 8:100064. https://doi.org/10.1016/j.onano.2022.100064
Morris HR, Spillantini MG, Sue CM, Williams-Gray CH (2024) The pathogenesis of Parkinson’s disease. Lancet 403:293–304. https://doi.org/10.1016/S0140-6736(23)01478-2
Rizek P, Kumar N, Jog MS (2016) An update on the diagnosis and treatment of Parkinson disease. CMAJ 188:1157–1165. https://doi.org/10.1503/cmaj.151179
Bhosale A, Paul G, Mazahir F, Yadav AK (2023) Theoretical and applied concepts of nanocarriers for the treatment of Parkinson’s diseases. OpenNano 9:100111. https://doi.org/10.1016/j.onano.2022.100111
Najib J (2001) Entacapone: A catechol-O-methyltransferase inhibitor for the adjunctive treatment of parkinson’s disease. Clinical Therapeutics 23:802–832. https://doi.org/10.1016/S0149-2918(01)80071-0
Aboofazeli R, Patel N, Thomas M, Lawrence MJ (1995) Investigations into the formation and characterization of phospholipid microemulsions. IV. Pseudo-ternary phase diagrams of systems containing water-lecithin-alcohol and oil; The influence of oil. International Journal of Pharmaceutics 125:107–116. https://doi.org/10.1016/0378-5173(95)00125-3
Deane K, Spieker S, Clarke CE (2004) Catechol-O-methyltransferase inhibitors for levodopa-induced complications in Parkinson’s disease. Cochrane Database of Systematic Reviews 2010:. https://doi.org/10.1002/14651858.CD004554.pub2
Müller T (2015) Catechol-O-Methyltransferase Inhibitors in Parkinson’s Disease. Drugs 75:157–174. https://doi.org/10.1007/s40265-014-0343-0
Amidon GL, Lennernäs H, Shah VP, Crison JR (1995) A theoretical basis for a biopharmaceutic drug classification: the correlation of in vitro drug product dissolution and in vivo bioavailability. Pharm Res 12:413–420. https://doi.org/10.1023/a:1016212804288
Kumar S, Kaur R, Rajput R, Singh M (2018) Bio Pharmaceutics Classification System (BCS) Class IV Drug Nanoparticles: Quantum Leap to Improve Their Therapeutic Index. Adv Pharm Bull 8:617–625. https://doi.org/10.15171/apb.2018.070
Agrawal Y, Patil K, Mahajan H, et al (2022) In vitro and in vivo characterization of Entacapone-loaded nanostructured lipid carriers developed by quality-by-design approach. Drug Delivery 29:1112–1121. https://doi.org/10.1080/10717544.2022.2058651
Khatri DK, Preeti K, Tonape S, et al (2023) Nanotechnological Advances for Nose to Brain Delivery of Therapeutics toImprove the Parkinson Therapy. CN 21:493–516. https://doi.org/10.2174/1570159X20666220507022701
Silva S, Almeida A, Vale N (2021) Importance of Nanoparticles for the Delivery of Antiparkinsonian Drugs. Pharmaceutics 13:508. https://doi.org/10.3390/pharmaceutics13040508
Hassan DM, El-Kamel AH, Allam EA, et al (2024) Chitosan-coated nanostructured lipid carriers for effective brain delivery of Tanshinone IIA in Parkinson’s disease: interplay between nuclear factor-kappa β and cathepsin B. Drug Deliv and Transl Res 14:400–417. https://doi.org/10.1007/s13346-023-01407-7
Ammar HO, Salama HA, Ghorab M, Mahmoud AA (2009) Nanoemulsion as a potential ophthalmic delivery system for dorzolamide hydrochloride. AAPS PharmSciTech 10:808–819. https://doi.org/10.1208/s12249-009-9268-4
Anton N, Gayet P, Benoit J-P, Saulnier P (2007) Nano-emulsions and nanocapsules by the PIT method: an investigation on the role of the temperature cycling on the emulsion phase inversion. Int J Pharm 344:44–52. https://doi.org/10.1016/j.ijpharm.2007.04.027
Araújo FA, Kelmann RG, Araújo BV, et al (2011) Development and characterization of parenteral nanoemulsions containing thalidomide. Eur J Pharm Sci 42:238–245. https://doi.org/10.1016/j.ejps.2010.11.014
Benita S, Friedman D, Weinstock M (1986) Physostigmine emulsion: a new injectable controlled release delivery system. International Journal of Pharmaceutics 30:47–55. https://doi.org/10.1016/0378-5173(86)90134-1
Baroli B, López-Quintela MA, Delgado-Charro MB, et al (2000) Microemulsions for topical delivery of 8-methoxsalen. J Control Release 69:209–218. https://doi.org/10.1016/s0168-3659(00)00309-6
Aungst BJ (1993) Novel formulation strategies for improving oral bioavailability of drugs with poor membrane permeation or presystemic metabolism. J Pharm Sci 82:979–987
Chattopadhyay P, Gupta RB (2001) Production of griseofulvin nanoparticles using supercritical CO(2) antisolvent with enhanced mass transfer. Int J Pharm 228:19–31. https://doi.org/10.1016/s0378-5173(01)00803-1
Chen H, Khemtong C, Yang X, et al (2011) Nanonization strategies for poorly water-soluble drugs. Drug Discov Today 16:354–360. https://doi.org/10.1016/j.drudis.2010.02.009
Yi C, Zhong H, Tong S, et al (2012) Enhanced oral bioavailability of a sterol-loaded microemulsion formulation of Flammulina velutipes, a potential antitumor drug. Int J Nanomedicine 7:5067–5078. https://doi.org/10.2147/IJN.S34612
Kentish S, Wooster TJ, Ashokkumar M, et al (2008) The use of ultrasonics for nanoemulsion preparation. Innovative Food Science & Emerging Technologies 9:170–175. https://doi.org/10.1016/j.ifset.2007.07.005
Kumar M, Bishnoi RS, Shukla AK, Jain CP (2019) Techniques for Formulation of Nanoemulsion Drug Delivery System: A Review. pnf 24:225–234. https://doi.org/10.3746/pnf.2019.24.3.225
Vadlamudi HC, Yalavarthi PR, Mandava Venkata BR, et al (2016) Potential of microemulsified entacapone drug delivery systems in the management of acute Parkinson’s disease. Journal of Acute Disease 5:315–325. https://doi.org/10.1016/j.joad.2016.05.004
Che Marzuki NH, Wahab RA, Abdul Hamid M (2019) An overview of nanoemulsion: concepts of development and cosmeceutical applications. Biotechnology & Biotechnological Equipment 33:779–797. https://doi.org/10.1080/13102818.2019.1620124
Kumar N, Verma A, Mandal A (2021) Formation, characteristics and oil industry applications of nanoemulsions: A review. Journal of Petroleum Science and Engineering 206:109042. https://doi.org/10.1016/j.petrol.2021.109042
Kumar N, Mandal A (2018) Thermodynamic and physicochemical properties evaluation for formation and characterization of oil-in-water nanoemulsion. Journal of Molecular Liquids 266:147–159. https://doi.org/10.1016/j.molliq.2018.06.069
Pal N, Kumar N, Saw RK, Mandal A (2019) Gemini surfactant/polymer/silica stabilized oil-in-water nanoemulsions: Design and physicochemical characterization for enhanced oil recovery. Journal of Petroleum Science and Engineering 183:106464. https://doi.org/10.1016/j.petrol.2019.106464
Faheim S, Gardouh A, Nouh A, Ghorab M (2018) Review article on nanoemulsions and nanostructured lipid carriers. Records of Pharmaceutical and Biomedical Sciences 2:23–31. https://doi.org/10.21608/rpbs.2018.5223.1011

No competing interests reported.

GraphicalAbstract.png

Download PDF

Reviews received at journal
26 Apr, 2024
Reviewers agreed at journal
17 Apr, 2024
Reviewers invited by journal
11 Apr, 2024
Editor assigned by journal
13 Mar, 2024
Submission checks completed at journal
12 Mar, 2024
First submitted to journal
12 Mar, 2024

You are reading this latest preprint version

Entacapone Nanoemulsion: Formulation Design, Optimization, and Evaluation

Status:

Version 1

Abstract

Figures

1 Introduction

2 Materials and methods [21-29]

3 Results and discussion

4 Conclusion

Abbreviations

Declarations

Funding

Competing interests

Consent for publication

Author contribution

References

Additional Declarations

Supplementary Files

Status:

Version 1