Box Behnken Design Based Development of Curcumin Loaded Eudragit S100 Nanoparticles for Site-Specific Delivery in Colon Cancer

 

Apeksha Saraf ¹*, Nidhi Dubey¹, Nitin Dubey², Mayank Sharma³

¹School of Pharmacy, Devi Ahilya Vishwavidyalaya, Takshashila Campus, Khandwa Road, Indore-452001, Madhya Pradesh, India

²College of Pharmacy, IPS Academy, AB Road, Indore-452012, Madhya Pradesh, India

³School of Pharmacy and Technology Management, NMIMS University (Deemed), Shirpur,

Dist. Dhule – 425405, Maharashtra, India

 

ABSTRACT:

The aim of the present study was to  prepare and optimize polymeric nanoparticles for site specific delivery of curcumin in colon cancer. The nanoparticles were formulated by nanoprecipitation method employing eudragit S100, a pH sensitive polymer for site specific delivery. The Box-Behnken experimental design (BBD) was applied for optimization and validation of formulation. The optimized formulation was characterized for surface morphology, particle size, zeta potential, encapsulation efficiency, in vitro release of drug and stability. The results of characterization revealed smooth surface of nanoparticles and particle size was obtained to be 122.38±0.75nm. The value of polydispersity index, zeta potential and encapsulation efficiency were found to be 0.298 and -38.79±0.05mV and 61.73±0.06, respectively. The in vitro drug release profile showed minimal drug release at pH 1.2 and pH 6.8 whereas higher and sustained drug release was found at pH 7.4, corresponding to pH of colon. The nanoparticles were found to be stable at refrigerated conditions. The results of the study suggested that hydrophobic herbal molecule like curcumin, with evident anti-cancer activity in colon cancer, can be successfully encapsulated in nanoparticluate system for improving therapeutic efficiency and site specific delivery to colon.

 

 

 

INTRODUCTION:

Colon cancer is the second leading cause for death world-wide. The treatment of colon cancer provides a limitation that the drug should reach colon in concentration required to achieve therapeutic efficacy. Most of the conventional therapies fail to achieve high concentration of drug in colon¹. Therefore, to overcome this problem and to improve therapeutic efficacy of drug, it is advantageous to formulate a site specific nanoparticulate drug delivery system. Site specific drug delivery provides a promising strategy to target the malignancies associated with colon.

 

These delivery systems offer advantages of   enhancing efficacy and site specificity^2-5.

 

Further, herbal anti-cancer agents are gaining attention for their efficacy to prevent and treat cancer. Number of herbal agents are investigated for anti-cancer activity but they show low aqueous solubility, low bioavailability and therefore insignificant therapeutic efficacy^6-7. Reports of literature revealed that several researchers have demonstrated successful improvement of therapeutic efficacy of herbal drugs upon encapsulation in a nanocarrier system^8-12. Curcumin is one of herbal agent with well proven anti-cancer activity for treatment of colon cancer. Curcumin exhibit poor water solubility, low bioavailability and lack of site specificity for cancerous cells^13-19. Thus, curcumin was selected as a model bioactive agent for development of site-specific polymeric nanoparticles for colon cancer. The present study is aimed to develop site-specific polymeric nanoparticles containing curcumin using eudragit S100, a pH sensitive polymer. Eudragit S100 facilitates drug delivery to distal part of gastrointestinal tract as it is insoluble in acidic environment of stomach, thereby increasing the therapeutic efficacy of the herbal anti-cancer agent²⁰.

 

Design of experiments (DOE) provides a systemic analytical tool to determine effect of response variables and interaction between the independent factors. Box-Behnken, D-optimal and central composite are frequently used response surface methodology design of experiments^21-23. Box Behnken design  was employed to optimize the polymer nanoparticulate formulation in the current study. The nanoparticles so prepared were further subjected to characterization of physicochemical properties, in vitro drug release profile study and stability studies.

 

MATERIALS AND METHODS:

Materials:

Eudragit S100 was procured from Evonik, India. Curcumin was procured from Sigma-Aldrich (St. Louis, MO, USA). Polyvinylalcohol (PVA) was obtained from Sigma Aldrich (St. Louis, MO, USA). The other chemicals and reagents were of extra pure grade.

 

Preparation of Curcumin Loaded ES100 Nanoparticles (CU-ES-NPs):

The curcumin loaded nanoparticles were prepared by nanoprecipitation method. The drug and ES100 were dissolved in acetone²⁴. This solution was injected into aqueous PVA solution under continuous magnetic stirring for 3 hrs to allow complete evaporation of organic solvent. The nanoparticles were obtained by centrifugation at 10,000 rpm for 20 minutes at 4°C (ELTEK, Refrigerated Centrifuge RC800 S) followed by freeze drying after repeated washing(Labcono, Model: FreeZone 4.5L).

 

Optimization of Curcumin Loaded ES100 Nanoparticles:

Curcumin loaded nanoparticles formulation was optimized by using Box-Behnken experimental design (BBD) by Design-Expert^® Software 11 (State-ease Inc., Trial Version) of 3-factor, 3-level wherein 17 formulations were developed. The selected variables and responses are as summarized in Table 1. The interaction between the variables was analysed by polynomial equations and three dimensional response surface plots generated by Design-Expert^® Software 11. The polynomial equation generated by Box-Behnken design is represented by following equation:

 

Y= A₀ + A₁*X₁ + A₂*X₂ + A₃*X₃ + A₄*X₄ + A₅*X₁*X₂ + A₆*X₁*X₃ + A₇*X₁*X₄ + A₈ *X₂ *X₃ + A₉*X₂*X₄ + A₁₀*X₃*X₄ + A₁₁ *X₁² + A₁₂ *X₂² + A₁₃*X₃² + A₁₄*X₄²

 

Where, Y = Response value of dependent variables, A₀ = intercept, A₁ to A₁₄ = regression coefficients, X₁ to X₄ = coded values of independent variables, X_a X_b (where a and b are 1,2,3,4) = interaction terms and X_i²(where ‘i’ is 1, 2, 3, 4) = interaction terms. The positive sign and negative signs to the magnitude of coefficients in polynomial equation showed synergistic effect or antagonistic effect of the independent variable on particle size and entrapment effficiency. The criteria for selection of optimized batch were to obtain minimum particle size and maximum encapsulation efficiency.

 

Table 1: Variables and Their Levels Used In Box-Behnken Design

Variables	Levels
			Units	-1 (Low)	0 (Medium)	+1 (High)
Independent Variables	X1	Volume of organic phase	ml	2.5	5	7.5
	X2	Drug Loading	%	10	20	30
	X3	Concentration of Surfactant	%	0.5	1	1.5
Constraints
Dependent Variables	Y1	Particle Size	nm	Minimize
	Y2	Entrapment Efficiency	%	Maximize

 

Physicochemical Characterization of Curcumin Loaded ES100 Nanoparticles:

Field Emission Scanning Electron Microscopy (FE-SEM): The optimized CU-ES-NPs formulation was subjected for determination of shape and surface morphology using FE-SEM (Zeiss, Germany, Model: Supra

55). The CU-ES-NPs were coated with gold and resolution was set at 2 nm with secondary electron image display and voltage of 2.2 Kv, 20 mV was applied.

 

Zeta potential, particle size and particle size distribution: Dynamic light scattering technique was used to determine zeta potential, particle size and size distribution of CU-ES-NPs at 25 °C in triplicate.

 

Encapsulation Efficiency of Curcumin Loaded ES100 Nanoparticles:

The encapsulation efficiency of CU-ES-NPs was determined in triplicate by ultraviolet-visible (UV) spectrophotometric analysis. Nanoparticles (10mg) were dissolved in methanol (10ml) and centrifuged at 8000 rpm for 5 minutes. After filtration, drug concentration in supernatant was determined at ambient temperature at wavelength of 420nm. The percentage drug encapsulated was determined by following formula:

 

                                    Weight of drug in nanoparticles

Encapsulation efficiency (%) = ––––––––––––––––––––––––––× 100

                              Total weight of drug

 

In Vitro Drug Release Study of Curcumin Loaded ES100 Nanoparticles:

The in-vitro drug release of CU-ES-NPs was determined in hydrochloric acid pH 1.2, phosphate buffer pH 6.8 and phosphate buffer pH 7.4²⁵. The NPs (10mg) were placed in the dissolution medium at 37 ± 1˚C, under magnetic stirring to maintain perfect sink condition. Samples were withdrawn at specific time interval and replaced with same volume of fresh medium. The samples were centrifuged at 8000 rpm for 5 min and amount of drug in supernatant was measured by UV-spectrophotometric analysis.

Stability Study:

The samples CU-ES-NPs formulation was evaluated for stability at refrigerated conditions for 90 days and evaluated for particles size, zeta potential and encapsulation efficiency.

 

RESULTS AND DISCUSSION:

Optimization of Curcumin Loaded ES100 Nanoparticles by Experimental Design:

The observations of total seventeen formulations of nanoparticles generated by using the Design Expert® soft-ware 11 and their corresponding response variables obtained are summarized in Table 2. The data observed from 17 formulations was fitted to mathematical models like linear, first order, cubic and quadratic models using Design Expert^® Software 11 to investigate interaction between the variables. The experimental design revealed the quadratic model to be the best fitted model for CU-ES-NPs analysis. Three dimensional graphs were plotted to study the influence of each of the responses.

 

 

Table 2: Observation of experimental runs and observed responses (n=3)

Formulation Code	Independent Variables			Dependent Variables
	Volume of Organic Phase: X1 (ml)	Drug Loading: X2 (%)	Concentration of Surfactant: X3 (%)	Particle Size (Y1) (nm ± SD)*	Entrapment Efficiency (Y2) (% ± SD)*
CUE1	1	1	0	166.14±0.57	59.78±1.45
CUE 2	1	0	-1	188.92±1.23	60.87±2.17
CUE 3	0	0	0	122.46±0.87	64.52±0.15
CUE 4	0	1	-1	136.85±0.42	56.77±1.72
CUE 5	0	0	0	120.68±0.22	62.56±0.14
CUE 6	0	0	0	118.67±0.65	58.91±1.66
CUE 7	-1	-1	0	116.17±0.9	40.84±0.90
CUE 8	-1	0	-1	144.34±0.28	54.92±0.75
CUE 9	0	0	0	128.68±0.31	66.85±1.52
CUE 10	-1	0	1	146.39±0.67	54.21±0.25
CUE 11	-1	1	0	140.56±0.77	56.82±1.62
CUE 12	1	0	1	175.28±0.94	60.35±0.49
CUE 13	0	0	0	122.46±1.21	62.46±0.09
CUE 14	1	-1	0	175.42±1.51	47.76±0.36
CUE 15	0	-1	1	135.16±0.16	38.62±0.06
CUE 16	0	1	1	154.97±0.40	54.72±0.24
CUE 17	0	-1	-1	162.44±1.33	43.25±0.15

 

Particle Size (Y₁)

The quadratic equation generated for the Y₁ response for CU-ES-NPs is as follows:

Y₁ = +122.59+19.789X₁ +1.166X₂ -2.594X₃ -8.42X₁X₂ -3.923 X₁ X₃ +11.35X₂X₃ +21.68 X₁²+5.303X₂²+ 19.463X₃²

 

 

 

The ANOVA analysis shows that the independent variables and their interaction effects provides significant model terms in respect to response Y₁. P-value was found to be less than 0.0001 for response Y₁ (Table 3). The values of lack of fit, model F value, p-value, adjusted R² and predicted R² for particle size (response Y₁) and encapsulation efficiency (response Y₂) are as shown in Table 4.

Table 3: ANOVA for Quadratic Model for Particle Size (Response Y₁)

Source	Sum of Squares	df	Mean Square	F-value	p-value
Model	8072.59	9	896.95	49.22	< 0.0001	significant
A-Volume of organic phase	3132.36	1	3132.36	171.90	< 0.0001
B-drug loading	10.88	1	10.88	0.5971	0.4650
C-Concentration of surfactant	53.82	1	53.82	2.95	0.1294
AB	283.42	1	283.42	15.55	0.0056
AC	61.54	1	61.54	3.38	0.1087
BC	515.29	1	515.29	28.28	0.0011
A²	1979.04	1	1979.04	108.61	< 0.0001
B²	118.39	1	118.39	6.50	0.0382
C²	1594.90	1	1594.90	87.53	< 0.0001
Residual	127.55	7	18.22
Lack of Fit	71.42	3	23.81	1.70	0.3045	not significant
Pure Error	56.14	4	14.03
Cor Total	8200.14	16

 

Table 4: Summary of Various Quadratic Parameters

Response	Adjusted R2	Predicted R2	Lack of fit F-value	Model F-value
Particle size(Y1)	0.9644	0.8500	1.70	49.22
Encapsulation efficiency (Y2)	0.9195	0.8843	0.18	21.30

 

The quadratic equation shows that volume of organic phase (X₁) and drug loading (X₂) has positive effect on particle size. The increase in the volume of acetone causes increase in the particle size which may be attributed to presence of high volume of medium. The particle size gradually increased with increasing amount of drug loading in the CU-ES-NPs. However, surfactant (X₃) showed decrease in the particle size of NPs upon increasing the concentration due to formation of small droplets. The three dimensional response graphs are as shown in Fig. 1a, 1b and 1c.

 

Entrapment Efficiency (Y₂):

The quadratic equation generated for the Y₂ response for CU-ES-NPs is as follows:

Y₂ = +63.06+2.75X₁+7.203X₂ -0.9888 X₃-0.99 X₁X₂ +0.0475 X₁X₃ +0.645X₂X₃ -1.256X₁²-10.504X₂²-4.216X₃²

 

The ANOVA analysis showed that the independent variables and their interaction effects provide significant model terms in respect to response Y₂. P-value was found to be 0.0003 for response Y₂ (Table 5).

 

 

Fig. 1a

 

Fig. 1b

 

Fig. 1c

Fig. 1: Three Dimensional Response Surface Plots for CU-ES-Nps Showing Effect of (A) Drug Loading and Volume of Organic Phase, (B) Concentration of Surfactant and Volume of Organic Phase, and (C) Concentration of Surfactant and Drug Loading on Particle Size

 

 

 

Table 5: ANOVA for Quadratic model for Encapsulation Efficiency (Response Y₂)

Source	Sum of Squares	df	Mean Square	F-value	p-value
Model	1067.55	9	118.62	21.30	0.0003	significant
A-Volume of organic phase	60.34	1	60.34	10.84	0.0133
B-drug loading	415.01	1	415.01	74.53	< 0.0001
C-Concentration of surfactant	7.82	1	7.82	1.40	0.2746
AB	3.92	1	3.92	0.7040	0.4292
AC	0.0090	1	0.0090	0.0016	0.9690
BC	1.66	1	1.66	0.2988	0.6016
A²	6.64	1	6.64	1.19	0.3108
B²	464.54	1	464.54	83.42	< 0.0001
C²	74.85	1	74.85	13.44	0.0080
Residual	38.98	7	5.57
Lack of Fit	4.65	3	1.55	0.1807	0.9043	not significant
Pure Error	34.33	4	8.58
Cor Total	1106.53	16

 

The above quadratic equation shows volume of organic phase (X₁) and drug loading (X₂) has synergistic effect on response Y₂. However, the higher amount of surfactant at showed decrease in the encapsulation efficiency. The three dimensional response graphs Y₂ are as shown in Fig. 2a, 2b and 2c.

 

 

Fig. 2a

 

 

Fig. 2b

 

Fig. 2c

Fig. 2: Three Dimensional Response Surface for CU-ES-Nps Showing Effect of (A) Drug Loading and Volume of Organic Phase, (B) Concentration of Surfactant and Volume of Organic Phase, (C) Concentration of Surfactant and Drug Loading on Encapsulation Efficiency

 

Optimization and Validation:

The optimized formulation of CU-ES-NPs was selected on the criteria to attain minimum particle size and maximum encapsulation efficiency by using numerical point prediction method of the Design Expert software®. The selected optimized formulation for CU-ES-NPs contained 4.8 ml volume of acetone, 20.2% of drug loading and 0.94% w/v surfactant concentration with value of desirability of 0.956. The experimentally obtained values of particle size (122.38nm) and entrapment efficiency (61.73%) of CU-ES-NPs were found in agreement with the predicted value of particle size (120.43 nm) and entrapment efficiency (63.65%) generated by Design Expert software® 11.

 

Physicochemical Characterization of Curcumin Loaded Nanoparticles:

The optimized nanoparticles showed the spherical shape by FE-SEM (Fig. 3). The average particle size of nanoparticles was found to be 122.38±0.75nm. The particle size distribution for optimized CU-ES-NPs is as shown in Fig. 4. The polydispersity index and zeta potential were obtained to be 0.298 and -38.79±0.05mV, respectively. The low value of polydispersity index and negative value of zeta potential confirms the uniform dispersity of particles and good physical stability of the delivery system. The encapsulation efficiency was obtained to be 61.73±0.06.

 

In-vitro Drug Release Study of Curcumin Loaded Nanoparticles:

The in vitro drug release from CU-ES-NPs was studied in pH ranging from pH 1.2, 6.8 and 7.4 (Fig. 5). NPs showed comparatively less drug release at pH 1.2 and 6.8, respectively, whereas at pH 7.4 the drug released was obtained to be higher and sustained, indicating the significant prevention of drug loss from nanoparticles before they reaches to colon.

 

Fig. 3: Scanning Electron Microscopic Image of CU-ES-NPs

 

 

Fig. 4: Particle Size Distribution of CU-ES-NPs (n=3)

 

Fig. 5: In Vitro Drug Release Profile of CU-ES-NPs (n = 3)

 

Stability Studies:

The physicochemical properties of CU-ES-NPs evaluated for 90 days at refrigerated conditions are summarized in Table 6. No significant change was observed in the particle size, zeta potential and encapsulation efficiency. The results revealed that refrigerated condition is the suitable storage condition for CU-ES-NPs.

 

Table 6: Summary of Results of Stability Study at Various Storage Conditions (n = 3)

Temperature	Parameters		Days
Refrigerated Temperature		0	30	60	90
	Particle Size (nm)	122.38±0.75	123.18±0.05	123.34±0.15	123.79±0.26
	Zeta Potential (mV)	-38.79±0.05	-38.32±0.27	-37.91±0.03	-37.89±0.84
	Encapsulation Efficiency (%)	61.73 ±0.06	61.41 ±0.40	60.86 ±0.53	60.12 ±0.90

 

CONCLUSION:

The curcumin loaded eudragit S100 nanoparticles prepared by nanoprecipitation method showed significant interaction between the dependent and independent variables. The particle size, zeta potential and encapsulation efficiency were found to be in desirable range. The refrigerated condition was appeared to be a suitable condition for storage of the formulation. The in vitro drug release profile has shown maximum and sustained drug release at pH 7.4 revealing prevention of drug loss in gastrointestinal tract. Therefore, it can be concluded that the curcumin loaded nanoparticles formulation can prove to be an effective site-specific delivery system for treatment of colon cancer.

 

ACKNOWLEDGEMENT:

The authors are thankful to Dr. Rajesh Sharma, Professor & Head, School of Pharmacy, Devi Ahilya Vishwavidyalaya, Indore, for his kind support and guidance throughout the research work. We extend our thanks to UGC-DAE Consortium for Scientific Research, Indore and Sophisticated Instrumentation Centre (SIC), Indian Institute of Technology Indore (IITI), for providing facility at their respective organizations.

 

CONFLICTS OF INTEREST:

The authors declare no conflict of interest.

 

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Accepted on 18.05.2019           © RJPT All right reserved

Research J. Pharm. and Tech 2019; 12(8):3672-3678.