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EUDRAGIT RSPO PDF

Drug Dev Ind Pharm. Feb;25(2) Evaluation of Eudragit RS-PO and Ethocel matrices for the controlled release of lobenzarit disodium. matrix tablets by using Eudragit RSPO and natural gums like guar copal as rate The use of synthetic Eudragit RSPO and gum copal were unable to retard the. Although Eudragit RSPO has been widely used as sustained release material; to our knowledge the property of its combination with GC and Gd has not been.

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To receive news and publication updates for Journal of Nanomaterials, enter your email address in the box below. This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The objective of present study was to develop an optimized polymeric nanoparticle system for the antiretroviral drug tenofovir.

The effect of amount of polymer, surfactant concentration, and sonication time on particle size, particle distribution, encapsulation efficiency EEand zeta potential were assessed and optimized utilizing a three-factor, three-level Eudragot Design BBD of experiment. The optimized formulation was characterized for in vitro drug release and structural characterization.

The FTIR showed some noncovalent interactions between the drug and polymer but a sustained release was observed in vitro for up to 80 hours.

Tenofovir is one of the first-line drugs used in the treatment of the human immunodeficiency virus HIV infected adults. It is a potent inhibitor of the virus nucleotide reverse transcriptase and was approved for clinical dudragit in [ 1 ]. It is also an important component of the fixed dose antiretroviral combinations Truvada, Atripla, and Complera [ 3 ].

Eudragit RSPO | Gum Copal | Gum Damar | Matrix Tablets | Release Kinetics

Therefore, to maintain the oral delivery route, formulating the drug into polymeric nanoparticles is essential for improving the bioavailability. Nanoparticles present significant advantages over conventional free drug dosing [ 56 ]. There is minimal drug loss during transit through the gastrointestinal tract while the particles evade degradation in the acidic environment of the stomach.

The lymphoid tissue associated with these patches facilitates distribution of the nanoparticles through the systemic circulations. While in the systemic circulation the nanoparticles extend the half-life of the drug and release it in a sustained manner.

The resultant benefit is a reduction of therapeutic dose, increased bioavailability, and limitation of toxic side-effects. The selection of a polymer for encapsulation is informed by several factors including the desired nanoparticle design and its biocompatibility [ 8 ]. Eudragit polymers are commercially available synthetic polymers used in drug delivery. They are copolymers of acrylic and methacrylic esters compatible with oral drug administration [ 9 eudragut.

Journal of Nanomaterials

Eudragit RS PO is a derivative with quaternary ammonium functional group [ 10 ]. It is insoluble at the physiological pH but the cationic charge facilitates rapid permeation through the intestinal mucosa [ 10 ].

This means that the drug payload can eudgagit transported by diffusion. Eudragit RS PO is used in the pharmaceutical industry as a eudragkt agent for tablets and capsule [ 11 ]. It has also been used in the preparations of time-controlled drug delivery formulations [ 12 ]. Tenofovir was encapsulated in Eudragit RS PO in this study intended for oral administration since most studies are based on the prevention of HIV transmission [ 13 ].

The most important characteristics of drug-bearing nanoparticles are size, encapsulation efficiency EEzeta potential, and drug release [ 14 ]. Various formulation and process variables such as amount of polymer, concentration of surfactant, amount of drug, stirring speed, stirring time, and temperature play a key role in determining the final physical and mechanical characteristics of nanoparticles.

These parameters are often screened and optimized using highly automated statistical tools and design of experiment. It is one of eudragti most popular experimental designs which is used for the development and optimization of drug delivery eufragit [ 8 ] and it offers the advantage of exploring more than three formulation variables rxpo minimize the number of wet experiments to be carried out [ 15 ].

Apart from this, BBD was chosen in this study because it is a more cost-effective technique than other similar experimental designs like central composite design, D-optimal design, and Latin square design which require 20 runs and 5 levels of the factor [ 13 eudtagit. It also does not contain any points at the corners, which helps to avoid unreasonable results [ 16 ]. It is also known as solvent displacement or interfacial deposition method and was developed about 40 years ago [ 18 ].

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Compared to other methods like emulsion [ 19 ], desolvation [ 20 ], salting out, and supercritical fluid technology it involves an economy of energy and steps and does not require specialized equipment. In this project we used a modified nanoprecipitation method to encapsulate tenofovir. All other chemicals used were of analytical grade and purchased from Sigma-Aldrich South Africa.

The solution was filtered through a 0. The BBD three factors, Quantum XL, Sigma was used to study the influence of formulation parameters in optimizing the preparation of nanoparticles. Effects of three independent parameters, namely, ratio of a polymer to a drugconcentration of surfactantand sonication time on average particles sizeparticle size distribution expressed as polydispersity index, PDIencapsulation efficiency EEand zeta potential were studied.

They were selected at their low, medium, and high levels with replicated centre points as shown in Table 1. The completed design consisted of 15 experimental runs, which were done in triplicate.

Analysis of variation ANOVA helps to identify the significant independent factors that affect the responses [ 22 ] and the fitness of the model. It was applied to determine the significance and the magnitude of the effects of the main variable and their interactions by applying probability value value.

The fitness of the model was checked by coefficient of determination and signal to noise -test. A nonlinear quadratic model correlating the relationship between the independent and dependent variables were generated and shown in where is the dependent variable, is the intercept, to are the regression coefficients, and, and are the independent variables.

To graphically demonstrate the influence of each factor on the response, the surface plots for each response were generated results using BBD [ 23 ]. Tenofovir nanoparticles were prepared using modified nanoprecipitation method [ 24 ] in accordance with BBD Table 2. Subsequently, nanoparticles were formed which turned the aqueous phase slightly milky with bluish opalescence. However, the mixtures were continued to be sonicated at different time frames and were left to stir overnight to aid size reduction and to evaporate solvent present.

Each sample was measured in triplicate. The results are expressed as mean standard deviation SD. The encapsulated drug was calculated using. The samples were prepared using a double adhesive tape stuck to an aluminium stub.

Drops of nanoparticles dispersion were applied on the stub and dried overnight. They were then coated with gold under an argon atmosphere using a gold sputter in a high vacuum evaporator.

The in vitro drug release studies were carried out using dialysis bag method [ 25 ]. Concentration of drug released was determined using UV spectrophotometer.

The percent drug release was determined by. Nanoprecipitation of hydrophobic drugs is more facile than the hydrophilic ones. Hydrophilic drugs tend to rapidly equilibrate from the organic to the outer aqueous phase leaving very little drug in the precipitating nanoparticles [ 26 ].

Modification of the traditional method with the use of surfactants improves the EE. Thus the purpose of solubility study was to identify suitable surfactant that possesses good solubilizing capacity for tenofovir to increase entrapment of the drug. It was also found that SDS was able to increase the drug solubility by threefold when compared to the solubility of tenofovir in water. Their results indicated that the drug had a solubility of Three-level, three-factor BBD was used to study the effect of variables in the preparation steps of nanoparticles.

Modified nanoprecipitation method was used to prepare 15 formulations as per BBD. On the basis of the results obtained from solubility study, SDS was chosen as surfactant to stabilize nanoparticles and acetone was chosen as an organic phase.

ANOVA was performed to test the significance and adequacy of the model. Normally the ratio greater than 4 is desirable for the model to be used effectively [ 28 ]. Factors with values that are less than 0. Any terms in the models with high -value and small value indicate more significant effect on the respective response variables. Moreover, coefficient of determination indicates the proportion of variation in the data that is explained by the model.

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An closer to 1 or 0. The significant effects of the independents variables were graphically demonstrated by 3D surface plots.

These kinds of plots are useful in studying the effects of two independent factors on the response at one time [ 30 ]. Since the model has more than two factors, one factor was held constant for each diagram [ 31 ]. The 3D surface plots illustrating the effects of independent variables on mean particle size, EE, average zeta potential, and PDI are shown in Figures 2 — 5respectively. Mathematical models were developed to understand the nature of the true relationship between the input variables and the output variables of the system [ 32 ].

The equation is composed of linear and interaction terms. The negative sign for the coefficients in the equation indicates a negative effect on responses, while the positive sign indicates a positive effect [ 8 ].

The reduced mathematical models for mean particle size, EE, average zeta potential, and PDI are presented by 4 to 7respectively. The coefficient of determination of the model for mean particle size was 0. The equation derived for mean particle size is given in where, and are ratio of a polymer to a drug, concentration of a surfactant, and sonication time, respectively, and and are interaction effects between ratio of a polymer to a drug and sonication time, concentration of a surfactant, and sonication time while and are quadratic effect on mean particle size.

From equation, it was observed that ratio of a polymer and concentration of a surfactant had positive effect on mean particle size whereas sonication time had negative effect. Figure 2 provides the 3D response surface plots showing the change of particles size corresponding to the change of independent variables.

Time-controlled release

Figure 2 a shows the effect of ratio of a polymer to a drug and concentration of a surfactant at a constant sonication time. It can be seen from the plot that an increase in ratio of a polymer and concentration of a surfactant resulted in an increased mean particle size.

It was explained that an increase in polymer concentration leads to an increase in viscous force resisting droplet breakdown by sonication [ 35 ]. Small mean particle size was obtained by low polymer to a drug having ratio of 1: These results are in good agreement with the results reported by Gannu et al.

Small mean particle size was observed in Figure 2 b when sonication time was increased. This may be due to the increase erosion effect on the surface of large particle and particle agglomerates resulting in small particles [ 37 ]. It was observed that ratio of a polymer to a drug has significant effect whereas other factors do not have an effect on EE. The interactions between ratio of a polymer to a drug and concentration of a surfactant and ratio of a polymer to a drug and sonication time were also statistically significant on EE.

The reduced model for EE is presented in where, and are ratio of a polymer to a drug, concentration of a surfactant, and sonication time, respectively, and and are interaction effects between ratio of a polymer to a drug and sonication time while is quadratic effect on EE.

The direction of the magnitude of significance as shown in 5 was negative for ratio of a polymer to a drug indicating an inverse relationship between ratio of a polymer to a drug and EE. This can further be seen from 3D surface plots in Figure 3.

From Figure 3 aa higher EE was attained with decrease in ratio of polymer to a drug and a maximum concentration of a surfactant at a constant sonication time.

Similarly in Figure 3 ba higher EE was obtained with a decrease in ratio of a polymer to a drug and a maximum sonication time at a constant concentration of a surfactant. This can be due to the fact that an increase in polymer concentration led to an enhancement of the concentration gradient between emulsion droplets and the continuous phase, as a result increasing the amount of drug partitioning into the continuous phase [ 38 ].

Table 6 shows that zeta potential is significantly influenced by ratio of a polymer to a drug and sonication time.