http://informahealthcare.com/lpr ISSN: 0898-2104 (print), 1532-2394 (electronic) J Liposome Res, Early Online: 1–11 ! 2014 Informa Healthcare USA, Inc. DOI: 10.3109/08982104.2014.891231

REVIEW ARTICLE

Optimization of methazolamide-loaded solid lipid nanoparticles for ophthalmic delivery using Box–Behnken design Fengzhen Wang1,2, Li Chen1, Sunmin Jiang3, Jun He1, Xiumei Zhang1, Jin Peng4, Qunwei Xu1, and Rui Li1 Journal of Liposome Research Downloaded from informahealthcare.com by University of Maastricht on 07/07/14 For personal use only.

1

School of Pharmacy, Nanjing Medical University, Nanjing, People’s Republic of China, 2School of Pharmacy, China Pharmaceutical University, Nanjing, People’s Republic of China, 3Wuxi Hospital for Maternal and Child Health Care, Affiliated Hospital of Nanjing Medical University, Wuxi, People’s Republic of China, and 4General Hospital of Beijing Military Command, South Gate Position No. 5, Beijing, People’s Republic of China

Abstract

Keywords

The purpose of the present study was to optimize methazolamide (MTZ)-loaded solid lipid nanoparticles (SLNs) which were used as topical eye drops by evaluating the relationship between design factors and experimental data. A three factor, three-level Box–Behnken design (BBD) was used for the optimization procedure, choosing the amount of GMS, the amount of phospholipid, the concentration of surfactant as the independent variables. The chosen dependent variables were entrapment efficiency, dosage loading, and particle size. The generated polynomial equations and response surface plots were used to relate the dependent and independent variables. The optimal nanoparticles were formulated with 100 mg GMS, 150 mg phospholipid, and 1% Tween80 and PEG 400 (1:1, w/v). A new formulation was prepared according to these levels. The observed responses were close to the predicted values of the optimized formulation. The particle size was 197.8 ± 4.9 nm. The polydispersity index of particle size was 0.239 ± 0.01 and the zeta potential was 32.7 ± 2.6 mV. The entrapment efficiency and dosage loading were about 68.39% and 2.49%, respectively. Fourier transform infrared spectroscopy (FT-IR) study indicated that the drug was entrapped in nanoparticles. The optimized formulation showed a sustained release followed the Peppas model. MTZ-SLNs showed significant prolonged decreasing intraocular pressure effect comparing with MTZ solution in vivo pharmacodynamics studies. The results of acute eye irritation study indicated that MTZ-SLNs and AZOPT both had no eye irritation. Furthermore, the MTZ-SLNs were suitable to be stored at low temperature (4  C).

Box–Behnken design, emulsion-solvents evaporation, methazolamide, solid lipid nanoparticles

Introduction Glaucoma is a common ocular disease of optic papilla damage and visual field defects caused by increasing intraocular pressure, which is a major cause of blindness (Infeld & O’Shea, 1998). Carbonic anhydrase inhibitors (CAIs) became a mainstay in the medical treatment of glaucoma since 1954, as its function of reducing aqueous humor formation and decreasing intraocular pressure (IOP) by inhibiting the activity of carbonic anhydrase (Maren, 1967, 1978). At present, methazolamide (MTZ) is taken as a main oral drug medication of treating glaucoma at home (Zimmerman, 1978). Oral CAIs can effectively reduce IOP, but it has many side effects due to its low selectivity (Epstein & Gran, 1977; Everitt & Avorn, 1990). In order to avoid systemic medication side effects and increase drug bioavailability, they have developed a number of topical preparations (De Santis, 2000; Martinez et al., 1999). Here, we prepared Address for correspondence: Rui Li, School of Pharmacy, Nanjing Medical University, Nanjing 210029, China. Tel: +86 25 86868478. Fax: +86 25 86868478. E-mail: [email protected] Qunwei Xu, School of Pharmacy, Nanjing Medical University, Nanjing 210029, China. Tel/Fax: +86 25 86868468. E-mail: [email protected]

History Received 4 September 2013 Revised 3 December 2013 Accepted 19 January 2014 Published online 10 March 2014

MTZ into topical eye drops taking solid lipid nanoparticles (SLNs) as carrier (Rui et al., 2011). Thus, the drug can directly target to the site of action through which increases the absorption of drug and prolong release in cornea (Bourlals et al., 1998; Muller et al., 2000; Wissing et al., 2004). There are many factors affecting the production process of MTZ-SLNs such as lipid materials, solvents, and operational conditions. Some studies have demonstrated that the ingredients such as the choices of lipids and the emulsifiers and their concentration significantly affected the physicochemical properties and drug-release profiles of nanoparticles. The quality of SLNs is controlled by the relative amount of lipids, and the concentration of surfactant in the formulation. A pharmaceutical formulation development study was required to understand detailed relationship between process parameters and quality attributes. In recent years, many statistical methods were applied to investigate the preparation processing. Single factor design is a traditional design which keeps the other factors constant, just investigating one factor at a time. It ignores interactions between factors and may call for unnecessarily large number of runs (El-Malah et al., 2006). Nowadays, the application of a statistical experimental design was accepted to be efficient

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acquiring good understanding of the necessary information of the relationship between independent and dependent variables in formulating (Chang et al., 2007; Gohel & Amin, 1998; Nazzal & Khan, 2002). The response surface methodology (RSM) is an effective tool for optimizing process, which is a collection of statistical and mathematical techniques based on the fit of empirical models to the experimental data obtained in relation to experimental design (Atkinson & Donev, 1992). RSM has been demonstrated its successful application of optimizing conditions of food and pharmaceutical research (Batistuti et al., 1991; Ibanoglu & Ainsworth, 2004; Shieh et al., 1996). The Box–Behnken design (BBD), an RSM design, was principally used because it required fewer runs in a 3-facter experimental design than all other RSM designs and avoided extreme treatment combinations. BBD is utilized to investigate the liner and interactive influences of different factors on response, through which the optimum nanoparticle formulation can be obtained (Dong et al., 2009; Ferreira et al., 2007; Woitiski et al., 2009). This research was to investigate the main and interaction influence of compositional variation and to optimize the MTZ-SLNs formulation using the BBD. In this work, GMS was determined as a lipid material by reason of its high drug entrapment efficiency. Tween 80 and PEG400 were selected as the emulsifiers. The rate of combinations was set at 1:1(w/v). MTZ-SLNs was prepared by the method of emulsion-solvents evaporation. The physicochemical properties such as surface morphology, particle size, drug loading, FT-IR study, drug release behavior, and in vivo pharmacodynamic studies of MTZ-SLNs were investigated in detail.

Materials and methods Materials MTZ, of 99% purity, was purchased from Hangzhou Aoyipollen Pharmaceutical Co. Ltd. (Hangzhou, China); glycerol monostearate (GMS) was from Shanghai No. 4 Regent & H.V. Chemical Co., Ltd. (Shanghai, China); phospholipids (Lipid S100) was provided by Lipid (Ludwigshafen, Germany); Tween80 was obtained from Shanghai Shenyu Pharmaceutical & Chemical Co., Ltd. (Shanghai, China); PEG400 was from Xilong Chemical Co., Ltd. (Xilong, China); mannitol was obtained from Sinopharm Chemical Regent Co., Ltd. (Shanghai, China); 1% w/v brinzolamide eye drops (AZOPTÕ ) were purchased from Alcon (Puurs, Belgium); HPLC grade methanol was supplied by Jiangsu Hanbon Science and Technology Co., Ltd. (Jiangsu, China). Distilled water was purified by Hitech-K flow Water Purification System (Hitech Instruments Co., Ltd., Shanghai, China). All other chemicals were of analytical grade. Preparation of SLN The MTZ-SLNs were prepared by modified emulsion-solvent evaporation method (Liu & Jiang, 2011). Briefly, MTZ, GMS, and phospholipids were completely dissolved into 5 ml ethanol in hot water bath at 70  C, and this organic phase was dropped slowly into 15 ml inner aqueous solution

J Liposome Res, Early Online: 1–11

containing Tween80 and PEG 400 (1:1, w/v) under 1200 rpm stirring (RET Control-visc C, IKA, Werke Staufen, Germany) at the same temperature, then kept stirring. Initial emulsion was formed. The resultant oil-in-water emulsion was quickly dispersed into distilled water containing 5% mannitol and 0.01% benzalkonium bromide, and maintained at 1000 rpm stirring at low temperature (0–2  C) for 2 h. The obtained MTZ-SLN was placed at room temperature, and filtered by 0.45 mm microporous membrane (25 mm filter, Phenomenex, Torrance, CA). Experimental design The selected independent variables included the amount of GMS, the amount of phospholipids, and the concentration of surfactants which were the three main influence factors on response. As shown in Table 1, the three independent variables were listed (X1: the amount of GMS, X2: the amount of phospholipids, X3: the concentration of surfactants) and prescribed into three levels, coded + 1, 0, and 1 for the high, the middle, and the low value, respectively. The variables were coded according to the following equation: i ¼ ðXi  X0 Þ=DX

ð1Þ

where i (i ¼ 1, 2, 3) is the coded value of the variable; Xi is the real value of the variable; X0 is the actual value of the variable at centre point; DX is the step change. In this study, the 3-factor, 3-level BBD was carried out (Kim et al., 2007; Kramar et al., 2003; Nazzal et al., 2002). The design was employed to investigate the quadratic response surface and to construct a second-order polynomial model using Design-Expert software (Stat-Ease, Inc., Minneapolis, MN). The relationship of the variables on the response can be analyzed by the second-order equation as the following: Y ¼ 0 þ 1 1 þ 2 2 þ 3 3 þ 12 1 2 þ 13 1 3 þ 23 2 3 þ 11 21 þ 22 22 þ 33 23

ð2Þ

where Y is the response variable; 0 is a constant; 1, 2, 3 are linear coefficients; 12, 13,  23 are interaction coefficients between the three factors; 11,  22, 33 are quadratic coefficients. It was reported that 3D response surface plots has a function of understanding the main and their interaction effects of two factors, maintaining all other factors at fixed level. The three-dimensional response surface plots for entrapment efficiency (Y1), drug-loading rate (Y2), and particle size (Y3) were plotted according to the regression model by remaining one variable at the centre level. DesignExpert 7.1.3 was applied to analyze the experimental data.

Table 1. Independent variables and their levels for the Box–Behnken design. Symbol

Variable

Units

1 Level

0 Level

+1 Level

A B C

GMS PL surfactant

mg mg %

50 0 1

100 75 2

150 150 3

Optimization of MTZ-loaded SLNs

DOI: 10.3109/08982104.2014.891231

Particle size, zeta potential, and morphology

Drug in vitro release

The particle size, zeta potential, and polydispersity index (PI) were measured by photocorrelation spectroscopy with a zetasizer 3000HAS (Malvern Instruments Ltd, Malvern, UK). The samples were diluted to a suitable concentration before measurement. Experiments on all samples were repeated twice and data were reported as an average value ± standard deviation. The morphology of MTZ-SLNs was analyzed with a JEM-200 CX transmission electron microscopy (TEM, JEM-200 CX, JEOL, Tokyo, Japan).

For determination of MTZ-SLNs release in STF, 2 ml of MTZ-SLNs suspension and MTZ solution placed in dialysis bag were incubated in 100 ml of STF at 35 ± 0.5  C under stirring at 50 rpm (Ye et al., 2008). The free drug was removed from SLNs suspension. The release studies were carried out in triplicate. Samples regularly sampled were filtered with 0.45 mm filter, and the filtrate was collected for MTZ determination by HPLC. But the drug was dispersed again with the equivalent fresh media. They were calculated by the following equations:

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The amount of MTZ in SLN was determined by HPLC. About 1 ml prepared SLN was diluted to 25 ml by methanol which was used as the solvent to dissolve SLN. Thereafter, it was filtered with 0.45 mm filter. The drug concentration in filtrate was determined as the content of the initial drug. Likewise, 1 ml prepared SLN was placed in a super filter tube, and then centrifuged by a Sigma-3k30 Centrifuges (Sigma-Aldrich, Seelze, Germany) with 14 000 rpm for 10 min at the temperature of 4  C. The ultrafitrate was extracted by methanol, and filtered with a 0.45 mm filter. The drug concentration in ultrafitrate was determined as the content of the free drug. The encapsulation efficiency and loading capacity were calculated by the following equations (Luo et al., 2006): EE% ¼

DL% ¼

Winitial drug  Wfree drug  100% Winitial drug

ð3Þ

Winitial drug  Wfree drug  100% Winitial drug  Wfree drug þ Wemulsifiers þ Wlipid ð4Þ

where Winitial drug, Wfree drug, Wlipid, and Wemulsifers were the weight of the total drug, the weight of the free drug, the weight of lipid added in system, and the weight of the phospholipids and emulsifiers. Fourier transform infrared spectroscopy (FT-IR) spectra study Blank-SLNs and MTZ-SLNs were lyophilized by freezedrier (Free Zone 12 liter, Labconco Corp., Kansas City, MO). The chemical structure and complexes formation of MTZ, Blank-SLNs, and their physical mixture and MTZ-SLNs were analyzed by a FT-IR (TENSOR 27, Bruker, Germany). The samples used for the FT-IR spectroscopic characteristics were prepared by grinding the dry specimens with KBr and pressing them to form disks. These analyses were performed within the range of 400–4000 cm1. In vitro release study Drug release medium The media of MTZ-SLNs selected in this study was simulated tear fluid (STF), containing 6.78 g NaCl, 2.18 g NaHCO3, 0.084 g CaCl22H2O, 1.38 g KCl in 1 L water.

Qn ¼ Cn  V0 þ

n1 X

Ci  Vi

ð5Þ

i¼1

F% ¼ Qn =C0  100%

ð6Þ

In vitro release model fitting In order to explore the drug release kinetics the release data were fitted to the model: zero-order, first-order, Higuchi, Weibull, Hixson–Crowell, and Peppas model which represents as the cumulative amount of drug released versus time, ln cumulative percentage of drug remaining versus time, cumulative percentage of drug released versus square root of time, the natural logarithm of ln cumulative percentage of drug remaining versus ln time, cube root of drug remaining versus time, log cumulative percentage of drug released versus log time (Hitendra et al., 2012; Jifu et al., 2011). The regression coefficient (R2) was calculated by using a SPSS (SPSS Inc., Chicago, IL) nonlinear regression which was used to choose the best fitting. In vivo pharmacodynamics studies New Zealand albino rabbits of either sex, weighing 2.5–3.0 kg with normotensive eyes, were used in this study. Formulations were instilled topically into the lower conjunctival sac of the eye as follows: MTA solution (0.1%, w/v) and the 0.02% MTZ-loaded SLNs. One eye received 50 mL of the preparation and the other was not treated as a control. The IOP of all rabbits was measured at the interval of 1 h by an indentation tonometer (YJI, Suzhou Mingren Medical Apparatus and Instruments Co. Ltd., Suzhou, China) after dosage. In all cases, before IOP measurement one drop of 0.2% (w/v) lidocaine hydrochloride was instilled as local anesthetic. The percentage decrease in IOP was determined according to the following equation: % Decrease in IOP ¼

IOP control eye  IOP dosed eye  100% IOP control eye ð7Þ

The pharmacodynamic parameters’ maximum percentage decrease in IOP, time for maximum response (Tmax), area under percentage decrease in IOP versus time curve (AUC0–8h), and mean residence time (MRT) were calculated using the 3P87/97 software (ACM, New York, NY).

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Eye irritation experiment Due to the SLNs contained surfactants, it was essential to evaluate its irritation as it served as eye drops. The eye irritation experiment was conducted in rabbits (either sex, 2.5–3.0 kg in body weight) with no abnormalities in the anterior eye parts were used. The rabbits were randomly divided into two groups, and every group included six rabbits. 50 ml of samples (AZOPT or MTZ-SLNs) was instilled into the conjunctival sac of the left eye of each rabbit. The lids were gently held together for about 30 s in order to prevent loss of the material. The right eye served as a control was instilled into saline. The responses of cornea, iris, and conjunctivae were evaluated at 8 h according to Draize’s scale of weighted scores for grading the severity of ocular lesions and the average score was calculated (Draize et al., 1994; Makoto et al., 2011) (Appendix Tables A1 and A2). Stability study The stability of MTZ-SLNs was preliminary investigated taking appearance, EE, and DL as indicators. The prepared MTZ-SLNs were settled at room temperature (25  C) and 4  C for 30 d, respectively. The changes of the appearance, EE, DL and zeta potential were determined.

Results and discussion Statistical analysis of experimental data by Design-expert software The experiment conditions and the observed responses for the 17 formulations were analyzed using Design-Expert software and are shown in Table 2. The number of experiments included the mid-point of each edge and the replicated center points. The selected independent variables including the amount of GMS, the amount of phospholipids, and the concentration of emulsifiers significantly influenced the observed responses for EE (%), DL (%), and particle size, which are presented in Table 2. Polynomial equations were generated which explained the individual main effects and interaction effects of independent factors on each dependent variables by the Design-Expert software.

The three-dimensional response surface plots and the contour plots for entrapment efficiency (Y1), drug-loading rate (Y2), and particle size (Y3) were obtained as seen in Figures 1 and 2. Effects on entrapment efficiency (Y1) According to multiple regression analysis on the experimental data, the relationship of the variables on entrapment efficiency (Y1) was illustrated by the following equation: Y1 ¼ 36:43 þ 4:881 þ 17:972  8:653 þ 4:141 2  0:301 3  9:472 3  6:6221  2:9722  2:3523 ð8Þ The summary of analysis results for observed response is shown in Table 3. The effect of each factor was tested using ANOVA test with a corresponding p value. Probability 4 F less than 0.0001 suggests that the model is significant, while greater than 0.0001 suggests that the model is not significant. The larger F-values and smaller p values were, the more significant the corresponding coefficients were. The determination coefficient (R2 ¼ 0.9902) is shown in Table 3 by ANOVA of the regression model (Y1), indicating that only 0.98% of the variation in response cannot be explained by this model. It can be seen from Table 3 that the model was significant while the lack of fit was not significant, which implies that the model was adequate for prediction with the range of experimental variables. From the Table 3, we found that the amount of phospholipids (X2), the concentration of emulsifiers (X3), and interactive influence of them (X2X3) were the main factors affected the EE. The positive coefficients before independent variables of quadratic model indicate a favorable effect on the EE, while the negative coefficients indicate an unfavorable effect on the EE. The largest coefficient of the amount of phospholipids (X2) indicated that the effect of the amount of phospholipids was found to be the main influential factor and had a significant and positive effect on Y1. What we can see from Figure 1(a), Y1 increased from 9.85% to 35.74% and from 9.64% to 52.11% when the amount of phospholipids increased from 0

Table 2. Experimental runs and observed responses for the Box–Behnken design.

Run 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Factor 1, X1: GMS (mg)

Factor 2, X2: PL (mg)

Factor 3, X3: surfactant (%)

Response 1, EE%

Response 2, DL%

Response 3, particle size (nm)

0 1 1 1 0 0 1 1 0 1 0 0 0 0 1 0 1

0 0 0 1 1 1 1 1 0 1 1 0 1 0 0 0 0

0 1 1 0 1 1 0 0 0 0 1 0 1 0 1 0 1

33.42 41.65 29.62 9.85 12.60 11.92 9.64 35.74 33.81 52.11 31.35 38.11 68.54 38.33 13.86 38.46 24.70

1.06 1.58 1.61 0.42 0.34 0.71 0.32 1.06 1.08 1.31 0.66 1.23 2.49 1.23 0.36 1.24 0.55

97.0 167.6 101.6 31.4 32.0 186.5 230.3 82.6 97.6 136.7 92.8 96.6 166.5 96.0 93.9 96.0 83.8

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DOI: 10.3109/08982104.2014.891231

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Figure 1. Response surface plots (3D) and contour plots (2D) showing the effects of variables (X1: the amount of GMS, X2: the amount of phospholipids, X3: the concentration of surfactants) on the response entrapment efficiency (Y1).

to 150 mg at the low and high levels of GMS (X1), respectively, showing that EE increased rapidly with the amount of phospholipids increasing. However, when the amount of GMS was maintained at the medial level, Y1 increased from 12.60% to 68.54% at the condition of the concentration of emulsifiers (X3) maintained at low level (Figure 1e). Thus, we can found that the high amount of phospholipids and the medial amount of GMS were favorable to formulation. The EE increased with the amount of phospholipids increasing may attribute to lipid material formed regular crystal lattice when low-temperature curing, which had an exclusive effect on entrapping drug. The phospholipids could dissolve in the lipid materials and formed the molecular solid dispersion, which destroyed the integrity

of the lattice of lipid materials, thus provided more sparer to accommodate excessive drugs (Shah & Pathak, 2010). The negative value before the concentration of emulsifiers (X3) in the regression equation suggested that the response Y1 decreased as the concentration of emulsifiers (X3) increased. In Figure 1(c) and (e), EE increased by decreasing the concentration of emulsifiers (X3). When the amount of GMS was maintained at medial level, Y1 increased from 31.35% to 68.54% as the concentration of emulsifiers (X3) decreasing from 3% to 1% at the high level of phospholipids (X2) (Figure 1e). Because at high concentration, the emulsifier might be gathered at organic solvent/water interface to reduce the interface tension, leading to significant increase in the net shear stress during emulsification, which promoted the

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Figure 2. Response surface plots (3D) and contour plots (2D) showing the effects of variables (X1: the amount of GMS, X2: the amount of phospholipids, X3: the concentration of surfactants) on the response entrapment efficiency drug-loading rate (Y2).

formation of smaller emulsion droplets (Budhian et al., 2007; Tesch & Schubert, 2002). Thus, the entrapment efficiency (Y1) decreased as the concentration of emulsifiers (X3) raised. Effects on drug loading (Y2) The following equation can explain the effect of factor levels on DL%: Y2 ¼ 1:17 þ 0:0391 þ 0:472  0:563 þ 0:0871 2 þ 0:0551 3  0:372 3  0:2121  0:1822 þ 0:06523 ð9Þ What we can see from Table 3 was that the significance of the model (Y2) was assessed from the coefficient (R2)

which was 0.9884, suggesting that the only 1.16% of the total variations was not explained by the model. The models were significant while the lack of fit was not significant as shown in Table 3. It can be seen from Table 3 that the model, liner coefficients (X2, X3) were significant model terms, while others were not, which indicated that the two factors mainly affected the response (Y2). The coefficients before the two variables indicated phospholipids had a positive effect on DL, while the concentration of emulsifiers had a negative effect. GMS showed also showed positive effect. The DL increased as the amount of phospholipids and GMS increased (Figure 2). What we can see from Figure 2(a), Y2 increased from 0.42% to 1.06% and from 0.32% to 1.315% when the amount of phospholipids increased from 0 to 150 mg at the low and high levels of GMS (X1), respectively, showing

Optimization of MTZ-loaded SLNs

DOI: 10.3109/08982104.2014.891231

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Table 3. Statistical analysis results of entrapment efficiency, drug loading, and particle size. EE% (Y1)

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Source Model 1 2 3 12 13 23 12 22 32 Residual Lack of fit Pure error

DL% (Y2)

Sum of square

p4F

Sum of square

p4F

Sum of square

p4F

4065.44 190.42 2582.29 598.93 68.72 0.35 358.53 184.41 37.22 23.26 40.05 13.58 26.48

50.0001 0.0007 50.0001 50.0001 0.0105 0.8107 50.0001 0.0008 0.0381 0.0836 – 0.6070 –

5.18 0.012 1.74 2.51 0.031 0.012 0.53 0.18 0.14 0.18 0.061 0.028 0.032

50.0001 0.2777 50.0001 50.0001 0.1023 0.2761 0.0001 0.0026 0.0050 0.1967 – 0.4240 –

24 703.73 11 927.40 0.32 12 776.01 – – – – – – 18 041.59 18 039.71 1.87

0.0089 0.0117 0.9881 0.0096 – – – – – – – 50.0001 –

R-square analysis

R-square analysis

R-square analysis

0.9902 0.9884 0.5779

0.9777 0.9735 0.4805

0.9370 0.9037 0.1402

R2 Adjusted R2 Predicted R2

Table 4. Predicted and measured values of MTZ-SLNs (n ¼ 3, mean ± SD). EE% Predicted Measured RSD (%)

67.36 68.39 ± 0.22 1.07

Particle size (Y3)

DL% 2.44 2.49 ± 0.05 1.43

Table 5. Particle size, polydisperity index, and zeta potential. (n ¼ 3, means ± SD).

Particle size (nm) 151.60 197.8 ± 4.9 18.70

Batch of SLNs Blank-SLNs (have pL) MTA-SLNs (no PL) MTA-SLNs (have PL)

Particle size (nm)

Zeta potential (mV)

PI

170.9 ± 2.3 327.7 ± 5.9 197.8 ± 4.9

23.5 ± 1.7 34.6 ± 2.9 32.7 ± 2.6

0.295 ± 0.02 0.303 ± 0.01 0.239 ± 0.01

that DL increased rapidly with the amount of phospholipids increasing. This is because when the amount of phospholipids and GMS increased, the content of drug entrapped in nanoparticles improved. The DL decreased as the concentration of emulsifiers decreasing might due to the same reason with the EE. And as the concentration of surfactant increasing, the entrapped drug decreased.

to predicted values, however, the measured value of particle size had a significant difference between the predicted values. Although the particle size model could not predicted, the measured particle size was small enough and met all requirements.

Effects on particle size (Y3)

We can observe form Table 5 that nanoparticle mean diameter and PI decreased by adding phospholipids which had a function of emulsification and stabilization. Blank-SLNs and MTZ-SLNs added that phospholipids mean diameter was approximately 200 nm. Polydispersity index was 0.239 ± 0.01. The zeta potential is a indicator which reflects the stability of the colloidal system. Zeta potential of MTZ-SLNs (+32.73 mV) was higher than +30 mV which showed higher stabilization of nanoparticles in suspension by the reason of particles would repel each other, leading to lower aggregation tendency. The morphology of MTZ-SLNs summarized in Figure 3 showed that the obtained MTZ-SLNs were almost spherical with uniform particle size.

The obtained following equation explains the influence of different factors on response (Y3) which was generated: Y3 ¼ 111:11 þ 38:611  0:202  39:963

ð10Þ

The determination coefficient (R2 ¼ 0.5779) is shown in Table 3, implying that 42.21% of the variation in response cannot be explained by this model (Y3). The significant lack of fit showed in Table 3 indicated that the models were not adequate for the prediction with the range of experimental variables. The optimum values of the variables were obtained by graphical and numerical analyses using the Design-Expert software on the base of restricting the desirable range of the each response (Myers & Montgomery, 2002). The optimum nanoparticles were formulated with 100 mg GMS, 150 mg phospholipids and 1% Tween80 and PEG 400 (1:1, w/v). The optimum nanoparticle formulation was demonstrated by practical experiments. As listed in Table 4, the predictive values, practical values, and predicted error of EE, DL, and particle size were compared (Kim et al., 2007; Motwani et al., 2008). The practical values of EE and DL were similar

Particle size, zeta potential, and morphology

FT-IR spectra study As can be seen in Figure 4(a) and (b), the peak at 1595 cm1 was assigned the amine groups (CONH) of MTZ, suggesting that the physical mixture is simply stack. However, the peak at 1595 cm1 significantly disappeared in FT-IR spectra of MTZ-SLNs (Figure 4d) and two new characteristic peaks at 1738 cm1 and 1458–1460 cm1 appeared, which was similar to FT-IR spectra of blank SLNs (Figure 4c). The results

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Figure 5. In vitro release profiles of MTZ solution and MTZ-SLNs (mean ± SD, n ¼ 3).

In vitro release model fitting Figure 3. Transmission electron microscopy micrograph of MTZ-SLNs (Bar ¼ 1 mm).

Figure 4. FT-IR spectra of MTZ (a), physical mixture (b), blank SLNs (c) and MTZ-SLNs (d).

indicate that MTZ has been entrapped in SLNs, and MTZ-SLNs were formed. In vitro release study Drug in vitro release The release curve of MTZ-SLNs is shown in Figure 5, taking the time (min) as abscissa and release percentage (%) as ordinate. As seen in Figure 5, MTZ solution released rapidly, the drug had been almost completely released at 120 min and the accumulative release rate was 95.46% while the accumulative release rate of MTZ-SLN was 66.65% at the same time. MTZ release from nanoparticles in simulated tear fluid (STF) was prevented during 480 min, and over 87.69% of MTZ was released after 600 min in simulated tear fluid, implying that MTZ-SLNs had a delayed release effect.

What we can see from Table 6, the drug release data showed the best fit to Weibull equation (R2 ¼ 0.986) which only expressed the release feature rather than the release mechanism. Meanwhile, the Peppas model (R2 ¼ 0.955) could explain the potential release mechanism. According to description in other studies about Ritger–Peppas equation (Hitendra et al., 2012; Jifu et al., 2011), the release mechanism might involve diffusion in this study. However, the mechanism of release was somewhat complex. In general, drug properties and the nature of the lipid carriers and other factors contribute to the release of drug from a lipid-based drug delivery system. In our previous studies, MTZ showed hydrophobic and not extremely good fat-soluble. Therefore, not all MTZ was incorporated into the core of lipid nanoparticles and some of molecules could enrich in the outer layer of SLNs which might become a main reason of the relatively fast release in the first 2 h (Ying et al., 2010). Meanwhile, as we removed the free drug from the MTZ-SLNs, the relative fast release at initial stage might also due to the nanoparticles had large specific surface area and some drug absorbed on the surface of nanoparticles (Zur Muhlen & Mehnert, 1998). Moreover, osmotic pressure difference, namely, the drug concentration in dialysis bag was higher than the drug concentration in the mediator, leading to drug fast release into the release medium as well. As the in vitro release condition and ocular environment is not fully same, the measured results cannot exactly reflect the real release of the drug in vivo. Therefore, the correlation of in vivo absorption and in vitro release of MTZ-SLNs remains to be further studied. In vivo pharmacodynamics studies Figure 6 and Table 7 exhibited the variations of decrease in IOP and pharmacodynamic parameters after the rabbits were administrated MTZ solution and MTZ-SLNs. The maximal effect of MTZ solution and MTZ-SLNs was obtained at 2 h and 3.1 h after administration, respectively, while the maximal reduction in IOP after MTZ-SLNs

Optimization of MTZ-loaded SLNs

DOI: 10.3109/08982104.2014.891231

9

Table 6. The regression of MTZ solution and MTZ-SLNs release in vitro. Model Zero-order First-order Higuchi Weibull Hixson–Crowell

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Peppas

Formulations

Regression equation

R2

MTZ solutions MTZ-SLNs MTZ solutions MTZ-SLNs MTZ solutions MTZ-SLNs MTZ solutions MTZ-SLNs MTZ solutions MTZ-SLNs MTZ solutions MTZ-SLNs

F ¼ 0. 054 t + 76.56 F ¼ 0. 097 t + 43.51 ln(100F)¼ 0.010 t + 3.255 ln(100F)¼ pffi 0.003 t + 4.040 F ¼ 1.792pffit + 65.41 F ¼ 2.963 t + 26.57 Ln ln[100/(100F)]¼0.52 ln t 1.424 ln ln[100/(100F)]¼0.507 ln t 2.358 ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi p 3 100  Fffi ¼ 0.005 t + 2.862 ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi p 3 100  F ¼ 0.003 t + 3.833 log F ¼ 0.150 log t + 1.629 log F ¼ 0.309 log t + 1.143

R2 ¼ 0.406 R2 ¼ 0.730 R2 ¼ 0.915 R2 ¼ 0.873 R2 ¼ 0.576 R2 ¼ 0.889 R2 ¼ 0.948 R2 ¼ 0.986 R2 ¼ 0.848 R2 ¼ 0.831 R2 ¼ 0.720 R2 ¼ 0.955

Table 8. Eye irritation study of MTZ-SLNs in rabbits (n ¼ 6). AZOPT

MTZ-SLN

Acute eye irritation study

Left

Right

Left

Right

Corneal opacity (mean score) Abnormality of iris (mean score) Conjunctival redness (mean score) Chemosis (mean score) Discharge (mean score)

0.3 0.1 0 0 0

0 0.2 0.1 0 0

0 0 0 0 0

0. 1 0 0 0 0

Mean score ¼ total score/6. Table 9. Particle Size, PI, EE of MTZ-SLNs after a month storage at 4  C and 25  C. Time (d)

EE %

Particle size (nm)

PI

Zeta potential (mV)

4 C

0 7 14 21 30

68.39 ± 0.2 68.23 ± 0.2 66.93 ± 1.5 64.36 ± 2.1 62.71 ± 0.2

197.8 ± 4.9 202.9 ± 3.4 201.3 ± 4.6 202.8 ± 0.6 207.7 ± 2.9

0.239 ± 0.012 0.153 ± 0.023 0.241 ± 0.002 0.221 ± 0.003 0.252 ± 0.015

32.7 ± 2.6 31.7 ± 0.9 37.6 ± 1.2 30.2 ± 2.7 34.6 ± 0.9

25  C

0 7 14 21 30

68.39 ± 0.2 62.08 ± 0.6 58.89 ± 0.3 53.21 ± 1.7 49.99 ± 0.9

197.8 ± 4.9 204.5 ± 2.0 213.9 ± 2.2 215.1 ± 2.4 214.8 ± 1.2

0.239 ± 0.012 0.185 ± 0.029 0.231 ± 0.011 0.232 ± 0.014 0.234 ± 0.005

32.7 ± 2.6 33.0 ± 1.1 33.9 ± 5.7 25.0 ± 1.2 27.2 ± 4.3

Figure 6. Percentage decrease in IOP after administration of MTZ-SLNs, MTZ solution (mean ± SD, n ¼ 4). Table 7. Pharmacodynamic parameters after administration of MTZ solution, MTZ-SLNs (mean ± SD). Pharmacodynamic parameters Formula

DIOP%max

Tmax (h)

AUC0–8h (mmHg h)

Ratio

MRT (h)

MTA solution 14.21 ± 1.63 2 ± 0.00 39.95 ± 2.35 – 2.57 ± 0.20 MTA-SLNs 28.93 ± 2.46a 3.1 ± 0.4 147.38 ± 10.94a 3.69 4.00 ± 0.27a

AUC0–8h, area under the percentage decrease in IOPtime curve; Tmax, time required to reach the peak effect; MRT, mean residence time. a Significant difference from the group of MTA solution (p50.05).

administration was 28.93% which was more statistically significant than MTZ solution administrated (Table 7). Compared with MTZ solution, 3.69 times AUC0–8h was observed when MTZ-SLNs were administrated (Table 7). The mean residence time (MRT) had significant difference between administrating MTZ solution and MTZ-SLNs (Table 7). The in vivo pharmacodynamics studies of MTZSLNs showed that the nanoparticles had a certain decreasing IOP effect and prolonged effect. Eye irritation experiment A summary of the results of the eye irritation experiments with AZOPT and MTZ-SLNs is presented in Table 8. No ocular responses such as corneal opacity, conjunctival

redness, abnormality of the iris, and chemosis were detected in any groups in rabbits instilled with MTZ-SLNs and AZOPT. The results indicated that MTZ-SLNs and AZOPT both had no eye irritation. Study of stability The changes of MTZ-SLNs properties are shown in Table 9. What we can see from Table 9, at the condition of 4  C the particle size, EE, value of PI and zeta potential of MTZSLNs had no significant changes after 30 d, and the suspension did not have agglomeration. The results suggested that MTZ-SLNs were relatively stable at this condition. While at the condition of 25  C MTZ-SLNs showed relatively poor stability after 30 d compared with MTZ-SLNs at 4  C. The formation of the aggregates were observed which might caused by the precipitated drug and lipids. The slow of oxidation of phospholipids at temperature leads to the changes of original crystal structure of SLNs, which caused the release of the hydrophobic drug.

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F. Wang et al.

It might be the main reason for the decreased entrapment efficiency and drug loading (Yan et al., 2012). Meanwhile, the zeta potential had a faster decrease at temperature. The zeta potential of nanoparticles related to steric stabilization and maintaining at the level of 25 mV is essential to physically stabilize SLN suspension. All results indicated that the nanoparticles were suitable to be stored at low temperature (4  C).

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Conclusion The MTZ-SLNs were successfully formulated by the modified emulsion-solvent evaporation method. A 3-factor, 3-level BBD was used to evaluate the interaction and quadratic effects of the selected three main influence factors on the EE, DL, particle size, and to optimize the formulation parameters. Based on the experimental responses and evaluating the constraints by mathematical approach, the optimal nanoparticles’ formulation was determined as 100 mg GMS, 150 mg phospholipid, and 1% Tween80 and PEG 400 (1:1, w/v). The in vitro release of the obtained MTZ-SLNs showed sustained release followed by sustained release followed Peppas model. The result of in vivo pharmacodynamics studies revealed that the MTZ-SLNs could be favor of decreasing IOP comparing with MTZ solution. The results of acute eye irritation study showed MTZ-SLNs had no eye irritation. In conclusion, it is feasible to prepare MTZ into topical eye drops taking SLNs as a carrier.

Declaration of interest The authors report no declarations of interest. This work was supported by National Natural Science Foundation of China (No. 81100977) and Natural Science Foundation of Jiangsu Province (No. BK 2009420).

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Appendix Table A1. Draize’s scale of weighted scores for grading the severity of ocular lesions.

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Assessment

Score

Cornea: No ulceration or opacity Scattered or diffuse area; details of iris clearly visible Easily discernible translucent areas; details of iris slightly obscured Opalescent areas; no details of iris visible, size of pupil barely discernible Opaque; iris invisible

0 1 2 3 4

Iris: Normal Folds above normal, congestion, swelling, and/or circumcorneal injection; iris still reacting to light (sluggish reaction is positive) No reaction to light, hemorrhage, and/or gross destruction

2

Conjunctivae: A. Redness of palpebral conjunctivae Normal Vessels definitely injected above normal More diffuse, deeper crimson red; individual vessels not easily discernible Diffuse beefy red

0 1 2 3

B. Chemosis Normal Any swelling above normal (includes nictitating membrane) Obvious swelling with partial reversion of the lids Swelling with lids about half closed Swelling with lids about half closed to completely closed

0 1 2 3 4

C. Discharge Normal Any amount different from normal Discharge with moistening of the lids and hairs just adjacent to the lids Discharge with moistening of the lids and considerable area around the eye Total score ¼ sum of all scores obtained for the cornea, iris and conjunctivae

Table A2. Scoring proposed for regulatory agencies. Average score

Assessment of irritation

0–3 4–8 9–12 13–16

Nonirritant Mild irritation Moderate irritation Intensity of irritation

11

0 1

0 1 2 3 16

Optimization of methazolamide-loaded solid lipid nanoparticles for ophthalmic delivery using Box-Behnken design.

The purpose of the present study was to optimize methazolamide (MTZ)-loaded solid lipid nanoparticles (SLNs) which were used as topical eye drops by e...
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