Dry eye disease is a common disease of the tear film caused by decreased tear production or increased evaporation. The objective of this study was to develop and evaluate poly (dl-lactide-co-glycolide) (PLGA) nanoparticles for CsA (CsA) ophthalmic delivery, for the treatment of dry eye disease. Topical CsA is currently the only and safe pharmacologic treatment of severe dry eye symptoms. Nanoparticles (NPs) were prepared by W/O solvent evaporation technique followed by probe sonicator and characterized for various properties such as particle size, entrapment efficiency, zeta potential,
Dry eye disease can also be known as Keratoconjunctivitis sicca, either due to insufficient tear production or excessive tear evaporation, both resulting in tears hyperosmolarity that leads to symptoms of discomfort and ocular damage. Dry eye disease is a prevalent disease that affects visual acuity, activities of daily living, and quality of life. Various environmental factors like contact lenses, pollution, working at video display terminals can affect the tear film and proceed up to infection, corneal ulcer, and blindness [
Nanoparticles systems accelerate the drug penetration, increase corneal uptake, and avoid systemic absorption. It is able to deliver more intact drug at site of action as compared to free drug [
The best known class of biodegradable polymers for sustained drug delivery is poly (dL-lactide-co-glycolide) (PLGA). PLGA is a biodegradable and biocompatible polymer that is hydrolytically degraded into nontoxic oligomer and monomer, lactic acid, and glycolic acid [
The poly(lactic-co-glycolic acid) (PLGA) polymer Resomer RG 503 was obtained from Sigma Aldrich Pvt. Ltd. Mumbai, India and Eudragit RL100 from Evonic degusa, Mumbai, India. Cyclosporine
The composition of simulated fluid (SLF), pH 7.4, was 8.3 g of NaCl, 0.084 g of CaCl2·2H2O, and 1.4 g of KCl in 1 litre of ultraPurified water [
Polymeric nanoparticle can be prepared in several ways. The formulations of drug loaded nanoparticles were done with solvent evaporation (o/w emulsification) followed by lyophilization, [
The design of experiments (DOE) technique was used to provide an efficient means to optimize the polymer concentrations. DOE is an approach for effectively and efficiently exploring the cause and effect relationship between process variables and the output.
Factorial design parameters and experimental condition
Factors | Levels used, Actual (coded) | ||
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Low (−1) | Medium ( |
High (+1) | |
A = polymer PLGA (mg) | 25 | 50 | 75 |
B = Eudragit RL100 (mg) | 25 | 50 | 75 |
Freshly prepared NPs were filled in 3 different amber coloured glass vials, sealed, and placed in stability chamber (CHM-10S, Remi Instruments. Ltd. Mumbai, India) maintained at
The solvent evaporation method described here appeared to be a suitable and simple technique to prepare PLGA containing NPs loaded with CsA. It is a one-step process, easy, and rapid.
Nine formulations of CsA loaded nanoparticle were prepared by emulsification solvent evaporation using factorial design, in which the independent variables were polymer concentrations PLGA 25 to 75 mg (
Summary of results of regression analysis for responses
Models |
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Adjusted |
Predicted |
SD | % CV |
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Response ( |
0.6485 |
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32.39 |
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Response ( |
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Results of analysis of variance for particle size.
Parameters | DF* | SS* | MS* |
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Significance of |
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Particle size | |||||
Model | 2 | 1161.1 | 5806.5 | 5.53 | 0.0434 significant |
Residual | 6 | 6295.87 | 1049.3 | — | — |
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Total | 8 | 17908.98 | — | — | — |
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Zeta potential | |||||
Model | 5 | 132.79 | 26.56 | 29.34 | 0.0095 significant |
Residual | 3 | 2.72 | 0.91 | — | — |
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Total | 8 | 135.51 | — | — | — |
Where, DF* indicates degrees of freedom; SS* sum of square; MS* mean sum of square and
It was observed that independent variables
Consider the following:
The coefficients with more than one-factor term in the regression equation represent interaction terms. It also shows that the relationship between factors and responses is not always linear. When more than one factor is changed simultaneously and used at different levels in a formulation, a factor can produce different degrees of response. The interaction effects of
Response surface plots for the
Response surface plots for the
The yield of production was found in the range between 52.29 and 85.30% (Table
Particle size, PDI of CsA loaded NPs after and before freeze drying (FD) and production yield of NPs.
NPs code | Particle size before FD (nm) | Polydispersity index (PDI) before FD | Particle size after FD (nm) | Polydispersity index (PDI) after FD | Production yeild |
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F1 | 160.0 ± 08 |
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161.20 ± 10 | 0.640 ± 0.053 | 52.29 ± 2.4 |
F2 | 182.98 ± 13 | 0.265 ± 0.084 | 204.30 ± 12 | 0.460 ± 0.081 | 55.72 ± 3.1 |
F3 | 130.5 ± 10 | 0.105 ± 0.042 | 145.5 ± 12 | 0.262 ± 0.054 | 85.30 ± 2.1 |
F4 | 128.48 ± 13 | 0.388 ± 0.060 | 145.7 ± 13 | 0.582 ± 0.065 | 64.90 ± 3.0 |
F5 | 144.53 ± 13 | 0.208 ± 0.045 | 170.5 ± 14.5 | 0.508 ± 0.051 | 80.45 ± 2.6 |
F6 | 210.75 ± 16 | 0.458 ± 0.043 | 226.3 ± 18 | 0.655 ± 0.048 | 81.90 ± 1.9 |
F7 | 235.2 ± 19.5 | 0.198 ± 0.058 | 244.1 ± 23 | 0.669 ± 0.063 | 56.87 ± 2.8 |
F8 | 240.68 ± 22 | 0.410 ± 0.063 | 258.3 ± 24.5 | 0.620 ± 0.058 | 80.39 ± 2.5 |
F9 | 253.50 ± 18 | 0.404 ± 0.057 | 260.0 ± 26 | 0.474 ± 0.066 | 83.40 ± 2.8 |
Data as mean
Zeta potential and percent entrapment efficiency of different PLGA loaded NPs.
NPs Code | Factor |
Factor |
Zeta potential (mV) in UPW | Zeta potential |
Entrapment efficiency |
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F1 | 25 | 25 | +20.3 ± 6.4 | +16.4 ± 5.2 | 58.35 ± 2.4 |
F2 | 50 | 25 | +21.0 ± 2.3 | +18.6 ± 2.1 | 63.41 ± 3.2 |
F3 | 75 | 25 | +24.7 ± 1.5 | +22.3 ± 1.4 | 91.69 ± 1.4 |
F4 | 25 | 50 | +25.6 ± 3.2 | +15.9 ± 3.7 | 59.65 ± 2.3 |
F5 | 50 | 50 | +25.2 ± 4.7 | +19.8 ± 4.3 | 86.37 ± 1.7 |
F6 | 75 | 50 | +24.0 ± 5.0 | +21.0 ± 4.8 | 88.96 ± 1.73 |
F7 | 25 | 75 | +32.5 ± 5.4 | +26.2 ± 5.3 | 60.21 ± 3.4 |
F8 | 50 | 75 | +31.8 ± 5.9 | +24.2 ± 6.0 | 85.66 ± 2.72 |
F9 | 75 | 75 | +34.5 ± 4.8 | +30.4 ± 5.9 | 89.65 ± 2.6 |
Data as mean ± SD,
The major objective of using general optimal design was to determine the levels of the two factors, that is, PLGA concentrations and Eudragit RL100 concentrations, which produce the NPs with minimum particle size. Particle size and Polydispersity index (PDI) of the fabricated batches were in the range of 128.48 to 253.50 nm and 0.22 to 0.669 before freeze drying and after freeze drying were 145.60 to 260.0 and 0.105 to 0.404, respectively, (Table
Effect of polymer concentration on particle size.
Zeta potential measurement is an adequate method in order to evaluate NPs surface properties and to detect any eventual modification after freeze drying. The zeta potential values were found to be 20.3 to 34.5 mV dependent on the polymer type used (Table
Zeta potential of different batches of CsA-NPs in UPW and SLF.
Nine different batches of nanoparticles were prepared by varying the polymer concentrations. The amount of drug was kept constant for all the batches. The entrapment efficiency of the CsA loaded NPs is shown in Table
Effect of polymer concentration on percent entrapment efficiency.
In this study, another reason of high burst might be the result of crystal structure of CsA being transformed to an amorphous structure after the lyophilization process. Formation of amorphous structure from crystal may lead to an increase in CsA solubility. During preparation of NPs, CsA could precipitate as amorphous substance in the PLGA matrix. After the initial burst effect, the drug was released slowly.
Model fitting of the release profile using four different models.
Batch code | Coefficient of determination ( |
Best fit model | ||
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Zero order | First order | Higuchi | ||
F3 |
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Higuchi |
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Korsmeyer Peppa's equation | ||||
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Mechanism | |
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F3 |
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Quasi fickian |
The bold values refer to coefficient of variation and its correct according to given headings.
Franz diffusion cell study aimed to obtain the preinformation about
The morphology of the optimized formulation (F3) nanoparticles was examined by scanning electron microscopy (Figure
SEM image of optimized formulation (F3).
The thermogram of CsA exhibited a sharp endothermic peak at 115.15°C, indicated melting point which was reported in the literature. Characteristic peak of CsA disappeared in the drug loaded nanoparticles. DSC studies revealed that CsA was molecularly dispersed inside the nanoparticle (Figure
DSC thermogram of A-Cyclosporine, B-Cyclosporine with PLGA, C-PLGA, D-Eudragit RL100, and E-NPs optimized batch F3 (CsA P75-E25).
The X-ray diffraction spectra were recorded for CsA, blank nanoparticle and drug loaded nanoparticle for investigating the crystallinity of the drug in the polymeric nanoparticle (Figure
A-Cyclosporine, B-blank nanoparticles, and C-drug loaded nanoparticles.
Particle size and Zeta potential variations during 3 months of storage were assessed. Respective data are given in Table
Stability characteristics of cyclosporine loaded NPs in terms of mean particle size and zeta potential.
Stability parameter | Test period | |||
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0 month | 1 month | 2 months | 3 months | |
Particle size (nm) | 145.5 ± 12 | 147.87 ± 6.89 | 148.17 ± 9.28 | 148.56 ± 7.80 |
Zeta potential | +22.3 ± 1.4 | +21.0 ± 1.0 | +20.3 ± 0.9 | +19.8 ± 1.6 |
Data as mean (mean
The present study reports the preparation and physicochemical characterization of CsA NPs which combine the PLGA with the positively charged properties of Eudragit RL100. The results indicate that both the mean diameter and the surface charge on NPs were markedly affected by the polymer type. The PLGA, Eudragit RL100-CsA (75 : 25 or Batch F3) NPs, showed small particle size and positive surface charge, which makes them suitable for ocular use. In conclusion, we have demonstrated that NPs with different properties could modulate the drug release in the
None of the authors have any financial and personal relationships with other people or organizations that could inappropriately influence (bias) their work.