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Back to Journals »International Journal of Nanomedicine» Volume 10 »Issue 1

Authors: Fard Masoumi HR, Basri M, Sarah Samiun W, Izadiyan Z, Lim CJ

Published on October 13, 2015, Volume 2015: 10(1) pages 6469-6476

DOI https://doi.org/10.2147/IJN.S89364

Single anonymous peer review

Editor approved for publication: Dr. Thomas Webster

Hamid Reza Fard Masoumi, Mahran Basri, Wan Sarah Samiun, Zahra Izadiyan, Chaw Jiang Lim Nanodelivery Group, Department of Chemistry, Faculty of Science, University of Serdang, Selangor, Malaysia Schizophrenia has excellent treatment effects in terms of symptoms, and is the first atypical antipsychotic drug approved by the US Food and Drug Administration. A high-shear and high-pressure homogenizer was used to prepare the nanoemulsion containing aripiprazole. The mixture experiment design was chosen to optimize the composition of the nanoemulsion. Emulsions with very small droplet sizes can provide effective encapsulation for delivery systems in the body. Palm kernel oil ester (3–6 wt%), lecithin (2–3 wt%), Tween 80 (0.5–1 wt%), glycerin (1.5–3 wt%), and water (87–93 wt%) The influence of %) on the influence of the droplet size of aripiprazole nanoemulsion was studied. The mathematical model shows that the best formula for preparing aripiprazole nanoemulsion that meets the requirements is palm kernel oil ester 3.00%, lecithin 2.00%, Tween 80 1.00%, glycerol 2.25%, and water 91.75%. Under the best formula, the predicted response value of the corresponding droplet size is 64.24 nm, which is in good agreement with the actual value (62.23 nm), and the residual standard error is <3.2%. Keywords: schizoaffective disorder, antipsychotic drugs, bipolar type I disorder, D-optimal hybrid design, optimized formulation

Schizophrenia is a serious mental illness that affects approximately 1% of the global population. 1 This mental illness is characterized by positive symptoms (such as hallucinations, delusions, and confusion), negative symptoms (such as loss of motivation, limited emotional experience, and poor speech), and cognitive impairment. In recent years, a drug (aripiprazole) has received increasing attention in the treatment of schizophrenia. It has been proven that aripiprazole can effectively treat the positive and negative symptoms of schizophrenia or schizoaffective disorder. It is used in the acute and long-term treatment of adults at a dose of 10-30 mg/d. 2-6

Aripiprazole (Abilify®) is an atypical antipsychotic drug with D2 partial agonist properties and high D2 receptor affinity. This partial agonist can reduce the overactivation of D2 in the mesolimbic pathway, thereby alleviating the positive symptoms of schizophrenia, but it provides sufficient D2 receptor stimulation in the mesocortical pathway and substantia nigra striatum pathway to prevent separately Negative symptoms and extrapyramidal side effects. 7-10 was originally developed for the treatment of schizophrenia, but also for the treatment of bipolar I disorder (acute treatment of mania and mixed episodes and maintenance treatment of bipolar I disorder), major depression (as an antidepressant) Adjuvant therapy) and irritability associated with autism. Finally, aripiprazole injection is suitable for the acute treatment of agitation associated with schizophrenia or bipolar disorder. 11

Despite these tremendous advances, aripiprazole is insoluble in water, which makes it very challenging to incorporate it into pharmaceuticals. In order to increase the dissolution rate of molecules that are difficult to dissolve in water, the surface area is purposely increased by reducing the droplet size of drug molecules. Increasing the surface area greatly affects performance. 12 Another application route can be considered, in which oil is used as a biocompatible carrier for aripiprazole in nanoemulsion compositions. This can improve the solubility and bioavailability of aripiprazole.

The nanoemulsion-based aripiprazole carrier can improve the solubility of the drug in the dispersed phase and the ability of the drug to penetrate the blood-brain barrier and target cells due to its extremely small size. Therefore, a smaller dose of aripiprazole is preferred to reduce side effects. In this context, the development of new drug nano-delivery systems to improve drug bioavailability and reduce adverse reactions is considered a good choice.

The research on the influence of the mixture composition in the nanoemulsion formulation should be solved by the experiment design technology of the mixture, also known as the mixture experiment design (MED). In addition to helping to maximize the amount of information and minimize the number of experiments to be performed, these designs also allow for the characterization and identification of synergistic and antagonistic interaction effects between different components. However, in recent years, some studies on formulating ingredients through these technologies have shown that 13-16, if these technologies are used more frequently, formula research will be more appropriate. 17

In this study, by changing the five components of the mixture, MED was performed to formulate a nanoemulsion compound containing aripiprazole. Evaluate the droplet size of the nanoemulsion in response and develop a statistical mixture model. The measured response must be minimized to produce a product with the desired characteristics. In this case, the response includes the droplet size (<200 nm).

Palm kernel oil esters (PKOE) are synthesized in our laboratory by lipase-catalyzed transesterification of palm kernel oil and oleyl alcohol. 18 Pure soybean lecithin (Lipoid S75) was purchased from Lipoid GmbH (Ludwigshafen, Germany). Glycerin was purchased from JT Baker (Philipsburg, NJ, USA). Polysorbate 80 (Tween 80) was purchased from Fluka, Sigma-Aldrich Co. (St Louis, MO, USA). Aripiprazole was purchased from Malaysian laboratories and scientific companies. The Milli-Q filter system, EMD Millipore (Billerica, MA, USA) was used to deionize the water.

Determination of Aripiprazole in Oil

In order to evaluate the loading capacity of aripiprazole dispersions based on PKOE as an oil, various concentrations of poorly water-soluble drugs were added to the basic composition. The composition of the drug-carrying system and the observed instability are studied. Add different amounts of medicine to the oily lecithin (3%). Keep the solution under moderate magnetic stirring for 24 hours to reach equilibrium. The sample was then centrifuged at 4,500 rpm for 15 minutes. The optimal amount of drug observed in the composition formulation is 0.1%.

Preparation of emulsion formulations using low shear rate emulsification

Use an overhead stirrer (IKA® RW20 Digital, Nara, Japan) at a speed of 300–305 rpm to prepare the emulsion by stirring and emulsifying at a low shear rate. Aripiprazole (0.1%) is dissolved in the oil phase, which is PKOEs (3.0%-6.0%) containing lecithin (2.0%-3.0%) as an emulsifier. After the aripiprazole is completely dissolved, Tween 80 (0.5%–1.0%) is added to the oil phase as an auxiliary emulsifier. The oil phase is added dropwise to the water phase composed of glycerin, and continuously stirred to form a coarse emulsion. The mixing of the emulsion was carried out at a shear rate of 300-305 rpm for 3 hours.

Preparation of nanoemulsion using high shear and high pressure homogenization

The emulsion prepared by low shear rate emulsification was homogenized using a high shear homogenizer (Kinematica AG, Luzern, Switzerland) at high speed (3,500 rpm) for 15 minutes. The sample was further homogenized for 14 cycles using a high-pressure homogenizer 1,000 psi. Put the final product in a sample bottle.

Put the freshly prepared sample in a container and store it in a refrigerator at ±5°C for 9 months. To test the stability of the samples, the samples were centrifuged at 4,500 rpm for 15 minutes. Then observe the sample to see if any precipitate forms.

A commercial dynamic light scattering instrument (Zetasizer Nano ZS; Malvern Instruments, Malvern, UK) was used to determine the droplet size distribution, average droplet diameter, zeta potential, and polydispersity index (PDI) of the nanoemulsion formulation. Dilute the sample with deionized water by adding a drop of the sample to the water in the cuvette. The measurement is performed at 25°C±0.5°C. To demonstrate reproducibility, each experimental run was performed in triplicate.

Composition is an interesting factor in MED. The main specification of the mixture formula is that the sum of the proportions of all its components must be 1. In addition, the response should only depend on the relative proportions of the components in the mixture, not on the volume of the mixture. 19 In this study, the D optimal experimental design was selected for modeling and the impact of five factors was evaluated. Influencing factors of nanoemulsion droplet size. This design provides the greatest amount of information obtained from the least number of experiments. In addition, when the result is expressed as a model, the best combination with the required criteria can be determined numerically or graphically.

The current work aims to evaluate the effects of five selected components on droplet size and emulsification ability. The following five components are selected according to the solubility and emulsifying ability of the drug: PKOEs (X1), lecithin (X2), Tween 80 (X3), glycerin (X4) and water (X5). In this work, the minimum and maximum molar ratios of these components are arbitrarily selected as follows: 3≤X1≤6%; 2≤X2≤3%; 0.5≤X3≤1%; 1.5≤X4≤3%; 87≤X5 ≤93% (Table 1). Mathematically, the sum of the percentages of the components must = 100%: X1 X2 X3 X4 X5 = 100%. Due to these constraints, the factor space of the design is obviously not a regular simplex but a convex polyhedron. 20 In addition, the ratios of the mixtures used for the components are constrained to comply with their relative quantities in actual commercial use. Pharmaceutical preparations. In order to build the final model, previous experiments have shown that a nonlinear response function must be expected. Therefore, the quadratic model is selected to explain the data results of D optimal experimental design, as shown in the following equation:

Table 1 Component proportion limit (%) Abbreviation: PKOE, palm kernel oil ester.

The coefficients βi and βij represent regression coefficients calculated from experimental data through multiple regression. The generated model contains a quadratic term, which explains the non-linear nature of the response and the multi-factor term that explains the interaction between the factors. The generated model contains a quadratic term, which explains the non-linear nature of the response and the multi-factor term that explains the interaction between the factors.

The calculation work, including experimental point design, randomization, analysis of variance (ANOVA), finding outliers, second-order polynomial model fitting, optimization and graphical representation (ternary graph), is performed using the statistical software package Design-Expert, Version 7.0 (Stat-Ease Inc., Minneapolis, MN, USA) and Statistica, version 12 (Statsoft Inc., Tulsa, OK, USA). The goodness of fit of the test model determines the correlation (R2), and the analysis of variance is applied to verify the adequacy of the regression model in the lack of fit test. The results of the analysis of variance are based on the confidence level α=0.05, and the validity of each variable should be determined according to its probability value (P value). Therefore, the term with probability P≥95% (α≤0.05) is significant.

Some physicochemical properties of aripiprazole nanoemulsion

PKOE is used as one of the variables in MED. PKOEs are selected based on their behavior in the drug carrier system. PKOE is composed of relatively short chain esters, which are potentially good carriers for the delivery of active ingredients into the body. 18 Tween 80 as an auxiliary emulsifier can provide the smallest droplet size and PDI. Lecithin is a natural emulsifier that mimics the biological system in the brain through electrostatic or covalent binding, and is known to help particles pass through the blood-brain barrier. 21 However, lecithin alone is not enough to form a good nanoemulsion system. It has been reported that the use of lecithin as an emulsifier may lead to the formation of hemolytic derivatives. 22 The formation of hemolytic derivatives should be controlled to prevent hemolysis in the body. However, the use of auxiliary emulsifiers such as Tween 80 can minimize this undesirable problem. The use of Tween 80 in pharmaceutical applications can produce good encapsulation efficiency. 23 Therefore, Tween 80 was selected as the co-emulsifier in this study.

The change in droplet size of the nanoemulsion was predicted by adopting the D-optimum MED as the response function of the formulation composition containing aripiprazole. The effect of five independent variables (Table 1) was studied using D optimal MED. Table 2 shows the results of 25 experiments. According to this experimental design, Zetasizer was used to prepare and measure the experimental mixture 3000 (Malvern Instruments) by photon correlation spectroscopy, which can measure droplet sizes between 10 nm and 5,000 nm.

Table 2 The predicted and actual values ​​of the droplet size of the nanoemulsion obtained from the D-optimal mixture experiment design Note: A, B, C, D, and E represent the weight percentages of PKOE, lecithin, Tween 80, glycerol and water, respectively. Abbreviation: PKOE, palm kernel oil ester.

Use Design-Expert software version 7.0 to fit the quadratic model to the experimental results. Fit the best model according to the following seven main criteria: high F value, low P value (<0.05), insignificant underfitting, high R2 (>0.90), low standard deviation, random scatter plot of residuals , And whether it can predict the validation set well. According to the actual factors of the mixture components, the final model used to predict the droplet size of the nanoemulsion can be expressed as follows:

Y =155.26A 267.66B 2007.10C 162.98D 84.03E -161.72A -2777.75AC -73.86AD 23.62AE -2501.03BC -300.65BD -234.29CE -234.29CE -234.59CE -234.59CE -234.59CE

Wherein A, B, C, D and E represent the weight percentages of PKOE, lecithin, Tween 80, glycerin and water, respectively.

It can be seen from Table 2 that the minimum droplet size first appeared in the 15th run with a value of 65.25 nm, and the second minimum droplet size appeared in the 19th run with a value of 65.55.

Figure 1 shows the predicted droplet size value (from the model) and the actual droplet size value (obtained from the experiment). The figure shows that the model successfully captures the correlation between the mixed components, with R2 of 0.9957.

Figure 1 A scatter plot of predicted droplet size value (PDSV) and actual droplet size value (ADSV) from D's best experimental mixture design.

According to Table 3, the response (droplet size) is very suitable for the quadratic model, and the F value and P value are 98.65 and <0.0001, respectively. According to the value of the linear term in Table 3 and Equation 2, it can be said that all linear mixing components (A, B, C, D, and E) respond effectively to linear mixtures according to their coefficients and P values. Factor C (Tween 80) shows the greatest impact on droplet size.

Table 3 Analysis of variance of nanoemulsion droplet size fitting linear/quadratic equation Note: A, B, C, D, and E represent the weight percentages of PKOE, lecithin, Tween 80, glycerol, and water, respectively. Abbreviations: N/A, not applicable; PKOE, palm kernel oil ester.

The response to outliers was investigated and it was found that all points are in a normal distribution. Table 4 shows that the "predicted R2" of 0.9756 is reasonably consistent with the "adjusted R2" of 0.9856. "Sufficient accuracy" measures the signal-to-noise ratio. Ratio> 4 is desirable. A ratio of 31.944 indicates sufficient signal. This model can be used to navigate the design space. The results show that >90% of the response change in the independent variable (droplet size) can be described as a function of the main components by the mixture design model.

Table 4 The abbreviation of the regression coefficient of the final reduced model: PRESS, the sum of squares of the predicted residuals.

Therefore, it can be concluded that the quadratic model is a model suitable for analysis and can show the trend well. The interaction between the parameters is more effective for the droplet size of the nanoemulsion. The interaction AC (between PKOE and Tween 80) According to the final mathematical formula 2, compared with other interactions, it has the greatest impact on the response (droplet size).

Figure 2-4 shows a three-dimensional surface map showing the effect of the interaction between the five different components on the size of the nanoemulsion droplets. Figure 2 shows that the droplet size value increases as the amount of oil (PKOE) increases, where the maximum droplet size can be seen (red area); however, the lowest value of the nanoemulsion is observed at a higher amount of lecithin Droplet size value. This is because when the amount of oil is reduced, a sufficient amount of lecithin can be used to emulsify the oil and water phases. The drawn model depicts a linear increase in droplet size as the amount of oil increases.

Figure 2 The ternary diagram shows the interaction of the response (droplet size) among the three variables (PKOE, lecithin, water). The two variables remain unchanged (Tween 80 and glycerin). Abbreviation: PKOE, palm kernel oil ester.

Figure 3 The ternary diagram shows the interaction of the response (droplet size) among the three variables (lecithin, glycerin, water). The two variables remain unchanged (PKOE and Tween 80). Abbreviation: PKOE, palm kernel oil ester.

Figure 4 The ternary diagram shows the interaction of the response (droplet size) among the three variables (lecithin, Tween 80, and water). Two variables remain unchanged (PKOE and glycerol). Abbreviation: PKOE, palm kernel oil ester.

The increase in the viscosity of the dispersed phase (oil phase) leads to an increase in flow resistance, which may cause problems in the process of droplet rupture. Therefore, the split rate is limited, resulting in the formation of large droplets. When the amount of lecithin used decreases, the droplet size of the nanoemulsion increases. This may be due to the fixed amount of emulsifier (lecithin), which caused the emulsifier molecules to not completely cover the newly formed droplets. This coverage limitation may result in an increase in emulsion droplet size. 24 The pharmaceutical industry needs to produce nanoemulsions with very small droplet sizes because it provides the entire system with extremely low surface tension and interfacial tension oil-in-water droplets 25

Figures 3 and 4 show that the higher the content of glycerin and Tween 80, the lower the droplet size value, where the minimum droplet size (dark green area) can be seen. The observed droplet diameter decreases with the increase of emulsifier concentration, which can be attributed to a variety of factors: the emulsifier adsorbs to the surface of the oil droplet faster during the homogenization process, resulting in lower interfacial tension, which promotes droplet fragmentation ; More emulsifiers can be used to cover the surface of the droplets formed during the homogenization process. 26 Increasing the amount of emulsifier will reduce the interfacial tension, thereby reducing the Laplace pressure and stress required for droplet deformation. These results indicate that Tween 80 and lecithin are the components that have the greatest effect on the droplet size reduction of nanoemulsions containing aripiprazole.

Complete the verification of the final model to check the adequacy of the predicted response values ​​in the verification set. Five random recipes with different component percentages are provided to validate the model. Compare the actual value of the response droplet size with the corresponding predicted value to evaluate the effectiveness of the model, as shown in Table 5. Determine the residual standard error percentage of the formula result value. The results confirmed the adequacy of the model, and found that the actual value is very close to the predicted value, indicating that the generated model has good fitness.

Table 5 Validation set abbreviations of five different formulations containing aripiprazole nanoemulsion: PKOE, palm kernel oil ester; RSE, residual standard error.

The best and stable formulation has the smallest droplet size, absolute value of zeta potential> 30 and PDI <0.25. The best formula is obtained based on the smallest droplet size of the nanoemulsion and the best Tween 80 volume. Using this method, a set of components was found. According to the MED analysis, the droplet size, zeta potential and PDI of the nanoemulsion composed of 3.0% PKOE, 2.0% lecithin, 1.0% Tween 80, 2.25% glycerin and 91.75% water are predicted to be 62.23 nm, -31.6 mV and 0.18 ,respectively. The formula and prediction results are shown in Table 6. The desirability of the best formula is 0.963. When the desirability value is between 0.8 and 1, the formulation quality is considered acceptable and excellent. When the value is less than 0.63, the quality of the preparation is considered poor. When the desirability value is <0.37.27, the formula is considered unacceptable

Table 6 The abbreviation of the best formula derived from the D-best mixture experimental design: PKOE, palm kernel oil ester.

Nano-sized and larger surface area drugs have some very interesting physical properties that can be used to overcome anatomical and physiological barriers related to drug delivery in complex diseases such as schizophrenia. The study showed that through the D-optimized experimental design, the nanoemulsion encapsulating aripiprazole was prepared through the emulsification process. The initial size of the droplets depends on the oil level, emulsifier type and emulsifier level, which are the main factors affecting the formation and stability of the nanoemulsion. In the titration process, using 1% non-ionic emulsifier (Tween 80), lecithin (2%), glycerol (2.25%) and 3% PKOE can form nanometers containing small droplets (d<65 nm) Emulsion. Therefore, in this study, we systematically studied some of the main factors that affect the efficiency and stability of nanoemulsion encapsulation. The nanoemulsion containing aripiprazole remained physically stable during storage at a temperature of ±5°C for 9 months, and no precipitation or aggregation was observed. From this, it can be concluded that the final nanoemulsion formulation has high encapsulation efficiency.

Thank you very much for the financial assistance provided by Putra University Malaysia under the Research University Grants Scheme (RUGS).

The authors report no conflicts of interest in this work.

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