Formulation and Optimization of Rabeprazole Sodium-Loaded Liposomes using Design Expert Software
J Adlin Jino Nesalin, Chidananda B N*
Department of Pharmaceutics, T. John College of Pharmacy, Bengaluru, Karnataka, India.
*Corresponding Author E-mail: chidanandabn123@gmail.com
ABSTRACT:
In recent years, significant advancements have been made in drug delivery systems, particularly through the use of innovative microparticulate carriers such as microemulsions, nanoemulsions, nanoparticles, liposomes, and ethosomes. These systems have been extensively studied for their ability to enhance the delivery of both hydrophilic and hydrophobic drugs, improving therapeutic efficacy. Liposomes, which are phospholipid-based vesicles that self-assemble into bilayers, have emerged as a promising drug delivery system. Their ability to encapsulate active agents within a central aqueous compartment makes them suitable for targeted drug delivery.
In this study, Rabeprazole sodium, a BCS Class III drug, was encapsulated into liposomes to improve its bioavailability and efficacy in treating Gastroesophageal Reflux Disease (GERD). Rabeprazole sodium, being hydrophilic, presents challenges in absorption, which makes liposomal delivery a valuable approach for enhancing its therapeutic potential. The formulation process was guided by Design Expert software, utilizing a 2² central composite design to optimize the formulation. A total of 13 experimental runs were conducted, which allowed for the identification of an optimized liposomal formulation. This optimized formulation offers a promising strategy for improving drug delivery, targeting, and bioavailability, which could lead to more effective treatment of GERD. This research underscores the potential of liposomal drug delivery systems in enhancing the treatment of GERD and highlights the importance of design software in optimizing pharmaceutical formulations for improved clinical outcomes.
KEYWORDS: Liposomes, BCS Classification, GERD, Design of expert, Central composite design.
INTRODUCTION:
In the past two decades, the evaluation of medical treatments has shifted from a narrow focus on clinical effectiveness and safety to include patient-centered outcomes, particularly health-related quality of life (HRQoL)1-2.
This evolution reflects the growing recognition among healthcare providers and researchers of the importance of HRQoL measures in understanding the broader impact of illnesses and the effectiveness of treatments. Comprehensive HRQoL scales assess various aspects of physical, psychological, and social functioning, which are critical for evaluating the influence of diseases like gastroesophageal reflux disease (GERD)3,4. GERD, a prevalent digestive disorder affecting approximately 7.6%-30% of the Indian population, primarily manifests through symptoms such as heartburn and acid regurgitation5. Due to its significant morbidity and adverse effects on quality of life, GERD represents a serious health concern, emphasizing the need for a holistic approach to treatment that prioritizes patient well-being alongside traditional clinical measures6.
Statistics:7
The worldwide GERD statistics are given in Table 1
Table 1: Statistical data of GERD
|
Sl No. |
Continents |
% of Population Affected |
|
1 |
North America |
18.1% - 27.8% |
|
2 |
Europe |
8.8% - 25.9 % |
|
3 |
East Asia |
2.5% - 7.8% |
|
4 |
Middle East |
8.7% - 33.1% |
|
5 |
Australia |
11.60% |
|
6 |
South America |
23.00% |
|
7 |
Russia |
18% -46% |
|
8 |
India |
7.6% - 30% |
Figure 1: Worldwide GERD Statistics
Gastroesophageal Reflux Disease (GERD) is a common condition, affecting up to 26% of the population weekly, with its global prevalence on the rise. The primary goals of treatment for GERD are to alleviate symptoms, promote esophageal healing, and prevent recurrences. While early treatments like H2-receptor antagonists and first-generation proton pump inhibitors (PPIs) helped manage GERD symptoms, newer second-generation PPIs, such as rabeprazole sodium, have demonstrated improved efficacy in treating acid-related conditions like GERD, peptic ulcers, and Zollinger-Ellison syndrome8-10.
Despite these advances, Rabeprazole sodium, like other PPIs, has some notable drawbacks. It has a short half-life and is unstable in acidic environments, which can lead to inconsistent therapeutic outcomes, especially in long-term treatments. Additionally, Rabeprazole sodium’s selective action on active proton pumps means that nighttime acid production can still occur, particularly when dosing is not optimized. These factors can reduce patient adherence to the treatment and result in suboptimal outcomes.
To address these challenges, the formulation of Rabeprazole sodium into liposomes has been explored. Liposomes are microscopic spherical vesicles made of lipid bilayers, which act as carriers for both hydrophilic and lipophilic drugs11. By encapsulating Rabeprazole sodium in liposomes, the drug’s stability is enhanced, protecting it from degradation in acidic environments, and improving its bioavailability. Liposomes also provide controlled and sustained release, allowing the drug to maintain therapeutic levels over a longer period, reducing the need for frequent dosing12-13.
This advanced drug delivery system not only addresses the limitations of conventional PPI formulations but also offers targeted delivery, leading to better therapeutic outcomes and improved patient adherence. Liposomal Rabeprazole sodium, therefore, represents a promising solution for overcoming the current challenges in GERD treatment and other acid-related disorders.
Design-Expert software plays a vital role in the formulation of Rabeprazole sodium-loaded liposomes by employing a central composite design (CCD) to optimize key parameters. This software facilitates systematic exploration of the formulation space, allowing researchers to identify the optimal conditions for achieving desired liposome characteristics, such as size, encapsulation efficiency, and drug release profiles. With 13 experimental runs generated, Design-Expert enables efficient testing of various formulation combinations while minimizing resource use14-15.
By analyzing in vitro drug release and entrapment efficacy, researchers can gain valuable insights into the performance of the liposomes under controlled conditions. The software's statistical capabilities help in identifying significant factors and interactions that influence formulation outcomes. Overall, the use of Design-Expert streamlines the development process, enhances formulation efficiency, and contributes to the creation of a more effective drug delivery system, ultimately improving the therapeutic potential of rabeprazole sodium in clinical applications.
MATERIALS AND METHODS:
MATERIALS:
Rabeprazole sodium (API) from Triveni Chemicals in Gujarat. Soya lecithin was obtained from Techno lb Kraft, Mumbai. Cholesterol was obtained from S D Fine-Chem Limited, Mumbai. Additionally, ethanol and chloroform were sourced from Karnataka Fine Chem, Bengaluru.
PREPARATION OF RABEPRAZOLE SODIUM LIPOSOMES:
The preparation of Rabeprazole sodium liposomes involves several key steps, starting with the use of the rotary evaporation method. First, the required amounts of cholesterol and soya lecithin are measured and dissolved in ethanol at a predetermined ratio in a round bottom flask. Following this, a rotary evaporator is employed to evaporate the ethanol, resulting in a thin lipid film coating the walls of the flask. Next, the appropriate amount of Rabeprazole sodium is accurately weighed and dissolved in phosphate buffer, then added to the flask containing the lipid film. To facilitate liposome formation, the flask is gently shaken to hydrate the lipid film. The mixture is then filtered using a vacuum filtration system, with the filtrate reintroduced into the flask to ensure maximum recovery of the product. Finally, the liposomal formulation is collected, allowed to cool to room temperature, and stored in a sealed container for further analysis or use16-17.
EXPERIMENTAL DESIGN:
Rabeprazole Sodium liposomes were formulated by varying the concentrations of soya lecithin and cholesterol. A Central Composite Design (CCD) was utilized, focusing on two variables—soya lecithin (phospholipid) and cholesterol (stabilizer)—at two different levels. This approach was used to assess their impact on entrapment efficiency and in vitro drug release. The experimental batches were prepared based on this design (Table 2), which evaluates combinations of the two factors and includes five axial points, resulting in a total of 13 runs. The study employed the Response Surface Design-Central Composite Design, with 2 factors at 2 levels, using Design Expert software (Version 13, Stat-Ease Inc, Minneapolis, MN). To ensure statistical rigor, the run order was randomized to avoid time-related influences and maintain the independence of observations (Table 3).
Table 2: Variables in 22 Central Composite Design
|
Independent variable |
Levels |
|
|
Low |
High |
|
|
Soya Lecithin (mg) |
100 |
150 |
|
Cholesterol (mg) |
10 |
30 |
|
Dependent variables |
||
|
Y1: Entrapment efficacy |
||
|
Y2: In-Vitro Drug Release |
||
Table 3: Matrix of Central Composite Design for Rabeprazole sodium loaded liposomes
|
STD |
RUN |
FACTOR 1 |
FACTOR 2 |
|
Soya Lecithin |
Cholesterol |
||
|
(mg) |
(mg) |
||
|
6 |
1 |
160.355 |
20 |
|
5 |
2 |
89.6447 |
20 |
|
3 |
3 |
100 |
30 |
|
2 |
4 |
150 |
10 |
|
11 |
5 |
125 |
20 |
|
1 |
6 |
100 |
10 |
|
10 |
7 |
125 |
20 |
|
7 |
8 |
125 |
5.85786 |
|
13 |
9 |
125 |
20 |
|
8 |
10 |
125 |
34.1421 |
|
12 |
11 |
125 |
20 |
|
4 |
12 |
150 |
30 |
|
9 |
13 |
125 |
20 |
Statistical analysis, including ANOVA, was conducted using Design Expert. The F-value was derived by comparing the variance between treatments to the error variance. Additionally, the multiple correlation coefficient was calculated to determine how much variation in the data was explained by the model. All assumptions required for ANOVA were validated to ensure accurate and reliable results.
EVALUATION OF LIPOSOMES:
METHODOLOGY:
Fourier-transformed infrared (FTIR) spectroscopy:
The FTIR spectra of Rabeprazole sodium was carried out by IR-Affinity-1-FTIR Spectrophotometer,
Shimadzu, Japan, FTIR Spectrophotometer in the region of 4000to 600 cm−119.
Drug content determination:
The drug content in the liposomes was quantified by dissolving 1 ml of the formulation in 9 ml of a chloroform-methanol mixture (2:1 ratio), and then diluting the solution to 100 ml with methanol. The resulting mixture was analyzed using a UV-Visible spectrophotometer at 284 nm, with methanol serving as the blank20.
Drug content = (Actual drug content in Liposomes)/(Theoretical drug content)*100
The individual values for three replicates were determined, and their mean values are reported.
Zeta potential and particle size distribution:
The zeta measurement potential was carried out using a NanoZS (Malvern UK) employing a 532 nm laser at a hack scattering angle of 173°.21
Entrapment Efficiency (%EE):
Entrapment efficiency was measured using the centrifugation method. The liposome dispersion was centrifuged (REMI LJ 01, Mumbai, India) at 15,000 rpm for 40 minutes. The clear supernatant was collected to determine the amount of unencapsulated drug. The concentration of the free drug in the solution was analyzed using a UV spectrophotometer (Shimadzu-1800, Japan) at a wavelength of 250 nm22.
The percentage of drug encapsulation was calculated by the following equation:
Loading efficiency = (Actual drug content in Liposomes)/(Theoretical drug content)*1
In-vitro release study:
The in-vitro dissolution study was conducted using a USP Type 2 (Paddle) apparatus set at 100 rpm. Phosphate buffer (pH 7.4) was used as the dissolution medium, with the temperature maintained at 37±0.5°C. At specific intervals over a 10-hour period, 1 ml samples were taken from the dissolution apparatus and replaced with an equal volume of pre-warmed fresh buffer. The samples were then filtered using Whatman filter paper and diluted to the appropriate concentration with phosphate buffer (pH 7.4). Absorbance measurements were taken at 284 nm using a UV spectrophotometer.
Kinetic analysis of In-vitro release rates of Rabeprazole Sodium loaded Liposomes formulation:
To analyze the drug release kinetics and mechanism, the in-vitro release data for the liposomes were fitted to different kinetic models. These included zero-order (cumulative % release vs. time), first-order (log % drug remaining vs. time), Higuchi’s model (cumulative % release vs. square root of time), and the Peppas model (log cumulative % release vs. log time). The correlation coefficient (R²) and release rate constant (k) were calculated from the linear regression analysis of the curves generated by these models.
RESULTS:
The IR spectra of pure drug Rabeprazole Sodium liposomes:
Figure 2: IR spectrum of Rabeprazole sodium
The FTIR spectrum shows that there were no significant changes in the chemical integrity of drug and also indicates that the polymer and drug are compatible with each other.
EVALUATION OF RABEPRAZOLE SODIUM LOADED LIPOSOMES:
Determination of entrapment efficiency:
Table 4: percentage entrapment efficiency of formulation (F1-F13)
|
FORMULATION |
ENTRAPMENT EFFICIENCY |
|
F1 |
82.31±0.15 |
|
F2 |
69.76±0.19 |
|
F3 |
73.78±0.18 |
|
F4 |
82.78±0.12 |
|
F5 |
77.96±0.18 |
|
F6 |
79.36±0.17 |
|
F7 |
77.68±0.17 |
|
F8 |
80.45±0.15 |
|
F9 |
79.05±0.13 |
|
F10 |
80.88±0.16 |
|
F11 |
78.14±0.14 |
|
F12 |
85.05±0.16 |
|
F13 |
79.22±0.19 |
|
F14 |
84.97±0.16 |
Mean (X ± S.D) (n = 3)
Percentage in– vitro drug release of formulation (F1 – F14):
In-vitro dissolution study:(F1-F7):
Table 5: Percentage In-vitro release (F1 – F7)
|
Time (min) |
F1 |
F2 |
F3 |
F4 |
F5 |
F6 |
F7 |
|
30 |
18.77±0.52 |
21.67±0.95 |
23.48±0.73 |
21.67±0.56 |
20.25±0.45 |
22.6±0.74 |
18.97±0.44 |
|
60 |
27.8±0.52 |
37.86±0.9 |
36.64±0.34 |
32.9±0.81 |
34.37±1.14 |
34.57±0.37 |
34.27±0.76 |
|
120 |
39.36±0.97 |
47.08±1.48 |
48.01±0.81 |
45.01±0.37 |
46.44±0.53 |
47.76±0.53 |
45.65±0.23 |
|
180 |
47.01±0.59 |
56.7±0.76 |
54.98±0.52 |
51.15±0.66 |
52.47±0.86 |
55.86±0.45 |
51.54±0.22 |
|
240 |
50.74±0.6 |
64.52±1.66 |
63.09±0.89 |
60.33±0.37 |
60.34±0.31 |
64.61±0.74 |
58.12±0.89 |
|
300 |
55.51±0.59 |
69.69±0.43 |
67.87±0.98 |
65.06±0.86 |
65.41±0.52 |
69.2±0.89 |
63.78±0.66 |
|
360 |
61.95±0.59 |
76.54±1.00 |
71.63±1.05 |
69.16±0.47 |
70.88±0.66 |
73.05±0.74 |
69.05±0.39 |
|
420 |
66.24±0.61 |
82.22±0.76 |
74.65±1.00 |
74.58±0.44 |
75.08±0.89 |
77.26±0.53 |
72.66±0.44 |
|
480 |
68.67±0.84 |
85.94±0.09 |
79.79±0.56 |
78.74±0.61 |
79.14±0.96 |
80.58±0.9 |
76.62±0.22 |
|
540 |
76.25±0.37 |
89.52±0.78 |
85.67±0.97 |
82.36±0.45 |
83.25±0.52 |
85.23±0.26 |
81.56±0.98 |
|
600 |
81.1±0.82 |
92.86±0.51 |
89.49±0.47 |
85.00±0.44 |
87.12±0.67 |
88.03±0.81 |
84.94±0.62 |
In-vitro dissolution study:(F8-F14)
Table 6: Percentage In-vitro release (F8 – F14)
|
F8 |
F14 |
F10 |
F11 |
F12 |
F13 |
F14 |
|
20.2±0.31 |
19.71±0.39 |
18.28±0.22 |
19.51±0.37 |
20.88±0.44 |
20.64±0.45 |
19.56±0.29 |
|
32.75±0.66 |
33.39±0.76 |
31.97±0.39 |
34.77±0.44 |
34.57±0.52 |
33.15±0.53 |
29.29±0.15 |
|
44.91±0.22 |
45.85±0.53 |
43.73±0.37 |
41.09±0.56 |
41.97±0.47 |
41.53±0.31 |
38.58±0.15 |
|
52.23±0.39 |
51.69±0.31 |
49.67±0.61 |
49.08±0.56 |
50.65±0.61 |
50.7±0.31 |
45.98±0.15 |
|
58.52±0.37 |
58.22±0.47 |
57.18±1 |
58.07±0.31 |
56.55±0.68 |
55.57±0.74 |
53.87±0.09 |
|
64.08±0.73 |
62.41±0.47 |
62.55±0.22 |
64.22±0.37 |
62.11±0.45 |
62.25±0.47 |
59.42±0.31 |
|
70.87±0.96 |
68.66±0.52 |
69.83±0.22 |
71.8±0.61 |
67.38±0.52 |
68.8±0.52 |
65.52±0.23 |
|
74.87±0.89 |
74.38±0.31 |
74.23±0.23 |
74.87±0.44 |
72.31±0.45 |
73.19±0.31 |
70.1±0.37 |
|
77.9±0.92 |
78.54±0.45 |
76.71±0.39 |
79.12±0.61 |
75.83±0.29 |
77.99±0.34 |
74.39±0.15 |
|
81.72±0.76 |
82.45±0.81 |
79.55±0.22 |
82.35±0.47 |
78.61±0.52 |
82.29±0.47 |
77.86±0.15 |
|
85.59±0.3 |
84.6±0.45 |
82.58±0.47 |
86.52±0.37 |
81.69±0.37 |
87.24±0.31 |
81.13±0.23 |
Determination of In-vitro drug release:
Table 7: In-vitro drug release formulation (F1-F13)
|
FORMULATION |
IN-VITRO DRUG RELEASE |
|
F1 |
81.09±0.82 |
|
F2 |
92.85±0.50 |
|
F3 |
89.49±0.47 |
|
F4 |
85.00±0.44 |
|
F5 |
87.11±0.66 |
|
F6 |
88.02±0.81 |
|
F7 |
84.94±0.61 |
|
F8 |
85.58±0.29 |
|
F9 |
84.60±0.44 |
|
F10 |
82.57±0.47 |
|
F11 |
86.51±0.37 |
|
F12 |
81.69±0.37 |
|
F13 |
87.24±0.30 |
|
F14 |
81.13±0.22 |
Mean (X ± S.D) (n = 3)
Observed response in Central Composite Design for Rabeprazole Sodium Liposomes:
Table 8: Observed response in Central Composite Design for Rabeprazole Sodium Liposomes
|
|
FACTOR |
FACTOR |
RESPONSE |
RESPONSE |
|
|
1 |
2 |
1 |
2 |
||
|
Std |
RUN |
A: Soya |
B: |
Entrapment efficiency (%) |
In-vitro drug release (%) |
|
Run |
lecithin |
Cholesterol |
|||
|
6 |
1 |
160.355 |
20 |
82.31 |
81.09 |
|
5 |
2 |
89.6447 |
20 |
69.76 |
92.85 |
|
3 |
3 |
100 |
30 |
73.78 |
89.49 |
|
2 |
4 |
150 |
10 |
82.78 |
85.6 |
|
11 |
5 |
125 |
20 |
77.96 |
87.11 |
|
1 |
6 |
100 |
10 |
79.36 |
88.02 |
|
10 |
7 |
125 |
20 |
77.68 |
84.94 |
|
7 |
8 |
125 |
5.85786 |
80.45 |
85.58 |
|
13 |
9 |
125 |
20 |
79.05 |
84.6 |
|
8 |
10 |
125 |
34.1421 |
80.88 |
82.57 |
|
12 |
11 |
125 |
20 |
78.14 |
86.51 |
|
4 |
12 |
150 |
30 |
85.05 |
81.69 |
|
9 |
13 |
125 |
20 |
79.22 |
87.84 |
Response 1 :Entrapment efficacy:
Figure 3: percentage entrapment efficiency
Figure 4: 3D surface of percentage entrapment efficiency
Response 2: In vitro Drug release:
Figure 6: 3D surface of in-vitro drug release
To obtain the optimized formulation the required limits of response values were clearly defined Entrapment efficiency of a minimum of 78.80% and maximum of 83.38%, In-vitro drug release of minimum of 81.09% maximum of 92.85%. The combinations of variables which resulted in formulation meeting the required specifications were calculated using the design expert software. The overlapping of obtained result over the predicted values confirms the practicability and validation of the model.
Table 9: Optimization of Rabeprazole Sodium Liposome
|
Name |
Goal |
Lower Limit |
Upper Limit |
Lower Weight |
Upper Weight |
Import-ance |
|
A:Soya lecithin |
Is in range |
100 |
150 |
1 |
1 |
3 |
|
B: Cholestrol |
is in range |
10 |
30 |
1 |
1 |
3 |
|
Entrapment efficacy |
Maximize |
69.76 |
85.05 |
1 |
1 |
3 |
|
In vitro Drug release |
Minimize |
81.09 |
92.85 |
1 |
1 |
3 |
Figure 7: Graphical Optimization of Rabeprazole Sodium Liposomes.
KINETICS STUDIES OF RABEPRAZOLE SODIUM LIPOSOMES:
The release kinetics of all five formulations were analyzed by fitting the dissolution data to various models, including zero-order, first-order, and Higuchi models (Table 11). The higher R² values indicated that drug release from all formulations followed first-order kinetics and aligned with the Higuchi model. According to the Higuchi model, the release mechanism was determined to be governed by swelling and diffusion. To further examine the release mechanism, the Peppas model was applied to differentiate between Fickian diffusion, non-Fickian diffusion, and zero-order release. The release exponent (n) from the Korsmeyer-Peppas model was found to be less than 0.50 for all formulations, indicating that drug release followed a Fickian diffusion mechanism.
In- vitro drug release for Rabeprazole sodium loaded liposomes:
KINETIC EVALUATION OF RABEPRAZOLE SODIUM LOADED LIPOSOMES:
Table 10: Kinetic studies of formulation (F1-F13)
|
Formulation |
Zeroorder(r2) |
FirstOrder(r2) |
Higuchi(r2) |
|
Korsmeyer-Peppa’s |
||
|
Mechanism |
r2 |
n |
Mechanism |
||||
|
F1 |
0.912 |
0.9778 |
0.9951 |
Sustain release |
0.9708 |
0.6571 |
Nonfickian Diffusion |
|
F2 |
0.884 |
0.9896 |
0.9916 |
0.9621 |
0.6832 |
||
|
F3 |
0.8691 |
0.9766 |
0.9871 |
0.9531 |
0.6691 |
||
|
F4 |
0.8817 |
0.9888 |
0.9922 |
0.9618 |
0.6685 |
||
|
F5 |
0.8801 |
0.9876 |
0.9907 |
0.9634 |
0.6729 |
||
|
F6 |
0.8617 |
0.9866 |
0.9862 |
0.9585 |
0.674 |
||
|
F7 |
0.8778 |
0.9843 |
0.9889 |
0.9642 |
0.6701 |
||
|
F8 |
0.8832 |
0.9886 |
0.9922 |
0.9654 |
0.6714 |
||
|
F9 |
0.8838 |
0.9872 |
0.9909 |
0.9645 |
0.6703 |
||
|
F10 |
0.882 |
0.9854 |
0.9905 |
0.9696 |
0.6716 |
||
|
F11 |
0.8989 |
0.9913 |
0.9933 |
0.9674 |
0.673 |
||
|
F12 |
0.8775 |
0.9838 |
0.9901 |
0.959 |
0.661 |
||
|
F13 |
0.9036 |
0.986 |
0.9965 |
0.9658 |
0.6683 |
||
|
F14 |
0.9113 |
0.9921 |
0.9982 |
0.9711 |
0.663 |
||
FORMULATION AND EVALUATION OF OPTIMIZED RABEPRAZOLE SODIUM LIPOSOMES:
Physical Appearance:
The Optimized formulation containing Liposomes vesicles were investigated for the clarity, appearance and homogeneity.
Evaluation of Optimized Rabeprazole Sodium Liposomes:
Table 11: Percentage entrapment efficiency, In-vitro drug release and drug content of Optimized Rabeprazole Sodium loaded liposomes
|
SI NO |
Entrapment efficiency (%) |
In-vitro drug release (%) |
Drug content |
|
1. |
84.97±0.08 |
81.13±0.23 |
82.46±0.16 |
Mean (X ± S.D) (n = 3)
Table 12: Zeta Potential of Rabeprazole sodium loaded liposomes
|
Zeta Potential |
-9.87(mV) |
|
Polarity |
Negative |
|
Temperature |
25.0 OC |
Figure 9: Zeta potential of Rabeprazole sodium loaded liposomes
Particle size Distribution:
Figure 10: Particle size of Rabeprazole sodium loaded liposomes
CONCLUSION:
The formulation of Rabeprazole sodium-loaded liposomes using the 22 Central Composite Design in Design Expert software successfully identified an optimized formulation, F14. This formulation, containing 150 mg of soya lecithin and 30 mg of cholesterol, demonstrated high drug entrapment efficiency and controlled drug release, making it a promising candidate for further development. The results indicate that the optimized liposomal formulation can effectively balance maximum drug encapsulation with minimal release, enhancing its potential for improved therapeutic performance
REFERENCE:
1. Tan ML, Choong PF, Dass CR. Recent developments in liposomes, microparticles and nanoparticles for protein and peptide drug delivery. Peptides. 2010; 31(1): 184-193.
2. Dunnhaupt S, Kammona O, Waldner C, Kiparissides C. A. Nano-carrier systems: strategies to overcome the mucus gel barrier. Eur J Pharm Biopharm. 2015; 96(3): 447-53.
3. Kanasova M, Nesmerak K. Systematic review of liposomes characterization methods. Monatsh Chem. 2017; 148(2): 1581-93.
4. Wood M, Maton PN, Sorensen S. The impact of gastroesophageal reflux disease on health-related quality of life. Am. J. Med. 1998 Mar 1; 104(3): 252-8
5. Clarrett DM, Hachem C. Gastroesophageal reflux disease (GERD). Missouri medicine. 2018 May; 115(3): 214.
6. Kellerman R, Kintanar T. Gastroesophageal reflux disease. Primary care. 2017 Oct 5; 44(4): 561-73.
7. El-Serag HB, Sweet S, Winchester CC, Dent J. Update on the epidemiology of gastro-oesophageal reflux disease: a systematic review. Gut. 2014 Jun 1;63(6):871-80.
8. Scarpignato C, Hongo M, Wu JC, Lottrup C. Pharmacologic treatment of GERD: Where we are now, and where are we going? Annals of the New York Academy of Sciences. 2020 Dec; 1482(1): 193-212.
9. Rackoff A, Agrawal A, Hila A. Histamine-2 receptor antagonists at night improve gastroesophageal reflux disease symptoms for patients on proton pump inhibitor therapy. Diseases of the Esophagus.2005 Dec 1;18(6): 370-3
10. Malfertheiner P, Kandulski A, Venerito M. Proton-pump inhibitors: understanding the complications and risks. Nature Reviews Gastroenterology & Hepatology. 2017 Dec; 14(12): 697-710.
11. Manish G, Vimukta S. Targeted drug delivery system: a review. Res J Chem Sci. 2011 May; 1(2): 135-8.
12. Allen TM, Cullis PR. Liposomal drug delivery systems: from concept to clinical applications. Advanced Drug Delivery Reviews. 2013 Jan 1;65(1):36-48.
13. J.S. Dua, A. C. Rana, A. K. Bhandari. Liposome: Methods of preparation and applications. IJPSR 2012;3(2):14-20.
14. Bhattacharya S. Central composite design for response surface methodology and its application in pharmacy. Response Surface Methodology in Engineering Science 2021 Jan 28. IntechOpen
15. Sopyan IY, Gozali DO, Guntina RK. Design-expert software (DOE): An application tool for optimization in pharmaceutical preparations formulation. Int. J. Appl. Pharm. 2022:55-63.
16. Kumari M, Jain NP. Formulation Development & Evaluation of Buffered Tablet of Proton Pump Inhibitors Drug Rabeprazole Sodium. JDDT. 2019 Aug 15; 9(4-s): 315-21.
17. Bhavani k, matsyagiri l. Formulation and in vitro evaluation of rabeprazole sodium delayed release tablets.
18. Njoku CN, Otisi SK. Application of central composite design with design expert v13 in process optimization. InResponse Surface Methodology-Research Advances and Applications 2023 Jan 23. IntechOpen
19. Patel P M, Desai H J, Patel R C. Spectrophotometric method for estimation of rabeprazole, of Indian J. Pharm. Sci. 2007; 69(2): 318- 320.
20. Fan Y, Marioli M, Zhang K. Analytical characterization of liposomes and other lipid nanoparticles for drug delivery. Journal of Pharmaceutical and Biomedical Analysis. 2021 Jan 5; 192: 113642.
21. Kaszuba M, Corbett J, Watson FM, et., al. High-concentration zeta potential measurements using light-scattering techniques. Philosophical transactions of the Royal Society a: Mathematical, Physical and Engineering Sciences. 2010 Sep 28; 368(1927): 4439-51.
22. Ran C, Chen D, Xu M, et. al. A study on characteristic of different sample pretreatment methods to evaluate the entrapment efficiency of liposomes. Journal of Chromatography B. 2016 Aug 15; 1028: 56-62.
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Received on 17.10.2024 Revised on 18.02.2025 Accepted on 25.04.2025 Published on 05.07.2025 Available online from July 10, 2025 Asian J. Res. Pharm. Sci. 2025; 15(3):237-244. DOI: 10.52711/2231-5659.2025.00036 ©Asian Pharma Press All Right Reserved
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