This technique was used to investigate
the morphology of the particles. The SLNs sample was observed in the form of aqueous dispersion using Quanta 200 ESEM (FEI, USA) (magnification: 24000×; accelerating voltage: 10 kV) at 25 ± 2 °C.7 On the bases of results obtained in the preliminary screening find more studies, two levels of each independent variable were decided. For three factors, the Box–Behnken design offers some advantage in requiring a fewer number of runs over the composite central, three-level full factorial designs. In full factorial designs, as number of factors increase there is increase in number of trial runs exponentially, such as 33 = 27, but with Box–Behnken design optimization HIF inhibitor can be completed with 17 experiments with five centre point. As it is shown in Table 2 and Table 3, Y1, Y2, and Y3 were fitted with a quadratic model and insignificant lack of fit (P > 0.05). The positive sign of the factors represent a synergistic effect on the response, while a negative sign means an antagonist relationship. Phrases composed of two factors indicate the interaction terms and phrases with second-order factors stand for the nonlinear relationship between the response and the variable. The second-order polynomial equation relating the response of particle size (Y1) is given below: equation(1) Y1=+194.83+12.95A−28.36B−25.48C+2.25AB+17.73AC−3.86BC−10.47A2+37.77B2+18.20C2Y1=+194.83+12.95A−28.36B−25.48C+2.25AB+17.73AC−3.86BC−10.47A2+37.77B2+18.20C2
The model F-value of 7288.58 implied that the model is significant (p < 0.0001). The ‘Lack of Fit F-value’ of 0.24 implied that the Lack of Fit is not significant (p = 0.8618). As Table 3 shows, the ANOVA test indicates that A, B, C, AB, BC, AC, A2, B2and C2 are significant model terms. Positive coefficients of A, AB, AC, B2& C2 in equation (1) indicate the synergistic
effect on particle size while negative coefficients Idoxuridine of B, C, BC & A2 indicate the antagonistic effect on particle size. The “Pred R Squared” of 0.9996 is in reasonable agreement with the “Adj R-Squared” of 0.9998, indicating the adequacy of the model to predict the response of particle size. The ‘Adeq Precision’ of 345.975 indicated an adequate signal. Therefore, this model is used to navigate the design space. The 3-D surface plots for particle size are shown in Fig. 1. An increase in particle size from 239.76 nm (H1) to 260.65 nm (H2) was observed on increasing the drug to lipid ratio from 1:2 to 1:4 (Table 2). This was probably caused by the aggregation of particles because of the concentration of surfactant was constant and not enough to form a protective layer on each particle10. A decrease in particle size from 193.98 nm (H13) to172.9 nm (H12) was observed on increasing surfactant concentration (up to certain limit) and stirring speed.