Formulation optimization using Box-Behnken design

In this study, we explored the effects of cholesterol concentration, hydrophilic-lipophilic balance (HLB) of the surfactant, and drug content on various characteristics of niosomes, including vesicle size, polydispersity index, zeta potential values, and entrapment efficiency. By employing a Box-Behnken design with three factors and three levels, we generated 15 primary predicted formulations and conducted a comprehensive analysis. Through statistical analysis, we assessed the individual and combined impacts of these parameters on niosome properties, gaining insights into their relationships. The design allowed us to identify optimal values for each parameter, facilitating the creation of niosomes with desired attributes.

The results obtained through this approach provide valuable information for the development of optimized niosome formulations with desired properties, enhancing their potential for various pharmaceutical and biomedical applications.

Analysis of niosome characteristics

According to ANOVA test and Box-Behnken design the quadratic model was the best fitted model for all responses. Consequent equations were as follows:

$$\mathrm\;\mathrm\;\mathrm=165.567\;-\;24.6488\mathrm A\;+\;26.0275\mathrm B\;-\;0.77125\mathrm C\;-\;24.8683\mathrm A^2\;-\;0.4925\mathrm\;+\;7.59\mathrm\;+\;12.6092\mathrm B^2\;-\;10.6175\mathrm\;+\;0.776667\mathrm C^2$$

$$\mathrm=+\;0.0025\;\mathrm A\;+\;0.025\mathrm B\;+\;0.005\;\mathrm C\;+\;0.0170833\mathrm^2\;-\;0.0325\mathrm\;-\;0.0125\mathrm\;+\;0.0220833\mathrm B^2\;+\;0.0275\mathrm\;+\;0.0270833\mathrm C^22$$

$$\mathrm=40.8467\;-\;2.74625\mathrm A\;-\;2.01\mathrm B\;-\;7.01875\mathrm C\;-\;5.91583\mathrm A^2\;-\;0.2425\mathrm+2.9\mathrm\;-\;2.62333\mathrm B^2+0.9925\mathrm\;-\;0.0808333\mathrm C^$$

$$\mathrm E\;\mathrm=55.95\;-\;0.2555\mathrm A\;-\;1.6245\mathrm B\;+\;21.311\mathrm C\;-\;1.98125\mathrm A^2\;-\;1.1565\mathrm\;-\;3.2665\mathrm+1.10175\mathrm B^2\;-\;1.7345\mathrm\;-\;7.21475\mathrm C^2$$

According to Table 1, DLS method showed that, mean vesicle sizes were in the range of 93 to 214 nm and the optimum formulation mean vesicle size was 165.1 ± 8.07 nm; increasing cholesterol percent caused an increase in the average size of the niosomes from 131.70 nm for F7 to 214.33 nm for F14. This result is supported by the results of ANOVA analysis; briefly, a significant synergistic effect was seen between the mean vesicle size of the niosomes and amount/percent of cholesterol, according to Pareto chart and estimated response surface 3D plot (Figs. 1 and 2). Square root of the cholesterol showed similar results; but, it wasn’t statistically significant. PDI values had significant reverse effect on HLB values (Table 1; Figs. 1 and 2). This significant reverse effect was also seen by the square root of the HLB. Another critical parameter was entrapment efficacy, as shown in Table 1, mean entrapment efficiencies were in the range from 21.39 ± 4.95% to 74.83 ± 1.88%. ANOVA analyses showed, this parameter had a significant direct relation with the amount of drug. In fact, rosuvastatin entrapment efficiency was increased by increasing the amount of the drug. This might be due to the excess amount of the drug that would be present in the lipophilic phase to be entrapped in the bilayers of the niosomes. Reverse relation between entrapment efficiency and HLB value was seen but this effect was not statistically significant. This phenomenon was also seen in the amount of cholesterol (Figs. 1 and 2). Moreover, according to Table 3, rosuvastatin entrapment efficiency of optimum formulation containing hyaluronan was more than optimum formulation without hyaluronan that showed the positive effect of hyaluronan in the entrapment efficiency as previously published [4, 5, 24]. Briefly, incorporating rosuvastatin in the hyaluronan gel and using this gel as a hydration medium might lead to the higher entrapment of rosuvastatin as it can be entrapped in the hydrophilic core; in addition, entrapping in the hydrophobic bilayers. Moreover, hyaluronan might act as a membrane stabilizer and increase bilayers stiffness which leads to less rosuvastatin leaking.

Table 3 Physicochemical characteristics of optimum formulation (mean ± SD, n=3) Fig. 1

Standardized Pareto chart achieved from anova analysis for 4 responses including Size response, PDI response, Entrapment Efficiency response and Zeta Potential response

Fig. 2

Estimated response surface 3D plots achieved from anova analysis for 4 responses including Size response, PDI response, Entrapment Efficiency response and Zeta Potential response

Polydispersity indexes (PDI) are used to assess dispersion homogeneity. Briefly, low PDI value indicate a homogeny dispersion; while, a high PDI value indicate a heterogenic dispersion with a high range of niosome vesicle size. So, According to the prior publications and results shown in Table 3, niosomes had acceptable homogeneity [25, 26]. According to Table 3; Figs. 1 and 2, PDI values were ranged from 0.21 to 0.34 (mean value 0.26). PDI of the niosomes were increased by increasing the amount of cholesterol from 0.28 to 0.32 for F7 and F14, respectively. According to pareto charts in Fig. 1, HLB value and the amount of the drug also had direct effect on PDI, but this effect was not statistically significant.

Zeta potential is a surface charge of the niosomes and can be used as a parameter to predict niosomes stability. Almost all of the previously published papers agreed with the fact that stable niosome dispersion should have a high amount of zeta potential. Many published papers suggest the range from 20 mv to 30 mv for zeta potential values in a stable system [24, 27]. In this study, the value of zeta potential was in the range from − 26.23 ± 2.32 mv to -48.53 ± 2.5 mv that showed all the prepared formulations had enough value of zeta potential and was stable. That was supported by the stability test results too. Rosuvastatin niosomes were stable after 90 days and there weren’t significant changes in the physicochemical properties of the niosomes. Size, PDI and zeta potential value were 170.21 nm, 0.28 and − 39.43 mv respectively. According to the Figs. 1 and 2, the amounts of zeta potential were increased by decreasing the amounts of drug. A significant reveres effect was also seen between zeta potential and second root of HLB value.

TEM & SEM analysis

Figure 3-A1 and 3-A2 shows TEM images of Nio-RSV and HA-Nio-RSV, respectively. And Figs. 3-B1 and 3-B2 shows SEM images of Nio-RSV and HA-Nio-RSV, respectively. According to Fig. 3 both Nio-RSV and HA-Nio-RSV were spherical. The size of the Nio-RSV in Fig. 3-A1 and 3-B1 was compatible with the mean vesicle size obtained by DLS method. Similarly, HA-Nio-RSV mean vesicle size obtained by DLS method (Table 3) and SEM analysis in Fig. 3-A2 and 3-B2 were compatible too.

Fig. 3

Morphorogical properties of rosuvastatin niosomes and rosuvastatin niosomes containing hyaluronan are showed in TEM and SEM images including TEM images of rosuvastatin niosomes (A1) and rosuvastatin niosomes containing hyaluronan (A2). SEM images of rosuvastatin niosomes (B1) and rosuvastatin niosomes containing hyaluronan (B2)

Stability analyses

Stability analyses were conducted to assess the physicochemical characteristics of the niosomes over a period of 90 days, and the results demonstrated their long-term stability. The initial sizes of the niosomes were 165.1 ± 8.07 nm, and after 90 days, they maintained a similar size of 170.21 ± 6.1 nm, indicating negligible changes in size over the stability period. The polydispersity index (PDI) value, a measure of particle size distribution, showed a slight increase from 0.25 ± 0.02 to 0.28 ± 0.04, suggesting a minimal change in the uniformity of the niosomes. The zeta potential, which indicates the surface charge of the particles, remained consistent throughout the stability period. The initial value of -42.13 ± 1.64 mV was comparable to the value after 90 days of -39.43 ± 3.82 mV, indicating that the niosomes maintained their surface charge stability. Similarly, the entrapment efficiency, representing the percentage of drug encapsulated within the niosomes, exhibited a stable value of 62.49 ± 1.42% initially and 59.22 ± 3.08% after 90 days, suggesting no significant loss of drug during the stability period. These results demonstrate the robust stability of the niosomes over the 90-day duration, as evidenced by minimal changes in size, uniformity, surface charge, and drug encapsulation efficiency. The consistent values obtained after the stability period indicate that the niosomes maintained their physicochemical characteristics without significant deviations from the initial values. Overall, the stability analyses confirm the long-term stability of the niosomes, supporting their potential as a reliable and durable drug delivery system. The maintained physicochemical properties over the 90-day period highlight the suitability of these niosomes for extended storage and potential applications in pharmaceutical formulations.

Differential scanning calorimetry (DSC)

In Fig. 4, DSC thermograms of pure Rosuvastatin (A), Cholesterol (B), Hyaluronan (C), Rosuvastatin niosomes (D), and Rosuvastatin niosomes containing Hyaluronan (E) are presented. The DSC thermogram of pure Rosuvastatin (Fig. 4-A) exhibits a sharp endothermic peak at 240 °C, which can be attributed to the melting point of Rosuvastatin. This sharp peak is indicative of the crystalline nature of the drug. The thermogram for Cholesterol (Fig. 4-B) shows characteristic endothermic peaks at 41.24 and 149.1 °C. The latter peak is closely aligned with the melting point of Cholesterol. In the thermogram of Hyaluronan (Fig. 4-C), a broad endothermic peak at 106.52 °C is observed, which may represent the polymer’s melting behavior. The presence of a narrow, sharp exothermic peak at 239.9 °C suggests the thermal degradation or destruction of the polymer, corroborating findings reported in the literature. For the Rosuvastatin niosomes (Fig. 4-D) and the formulation containing Hyaluronan (Fig. 4-E), a similar peak around 50 °C is noted in both thermograms. This peak’s consistency across the formulations indicates a reliable attribute of the niosomal preparation, potentially related to the Tg or a phase transition of the niosomal components. Notably, the characteristic sharp endothermic peak of pure Rosuvastatin at 240 °C is absent in the thermograms of the niosome formulations (Fig. 4-D and 4-E), suggesting that the encapsulation within niosomes and the presence of Hyaluronan might alter the crystalline structure of Rosuvastatin, leading to an amorphous form. This alteration could be conducive to the drug’s stability and suggests an interaction between the drug and the niosomal components. Similarly, the characteristic peaks of Cholesterol and Hyaluronan are not distinctly present in the niosome thermograms, implying interactions between these components within the niosome structure. These interactions may influence the stability and encapsulation efficiency of the niosomes, as supported by analogous results in previously published papers [4, 13]. Overall, the DSC thermograms indicate that the niosome formulations, both with and without Hyaluronan, may enhance Rosuvastatin’s stability by altering its physical state.

Fig. 4

Thermal behavior of different samples are showed in DSC thermograms of each sample including DSC thermograms of pure Rosuvastatin (A), Cholestrol (B), Hyaluronan (C), Rosuvastatin entrapped niosomes (D), Rosuvastatin entrapped niosomes containing hyaluronan (E)

FT-IR analysis

According to Fig. 5, Characteristics peaks and identical spectra of rosuvastatin calcium including N-H stretching characteristics peak (2968.55 cm-1), C = O stretching characteristics peak (1732.13 cm − 1), C = C stretching characteristics peak (1546.96 cm-1), =C-H stretching characteristics peak (2922.25 cm-1), N-H bending characteristics peak (3387.11 cm-1), and symmetric bending vibration of CH3 group characteristics peak (1383.01 cm-1) were seen from pure powder (Fig. 5-A) and rosuvastatin entrapped niosomes and hyaluronan containing rosuvastatin entrapped niosomes (Figs. 5-C, D). hyaluronan was also analyzed in this study to detect the possible incompatibilities. Characteristics peaks of hyaluronan were seen in Fig. 5-B. Results showed that no incompatibilities were seen and no new bands appeared [28, 29].

Fig. 5

The FT-IR spectra of pure Rosuvastatin (A), The FT-IR spectra of hyaluronan (B), The FT-IR spectra of Rosuvastatin niosomes (C), The FT-IR spectra of Rosuvastatin niosomes containing hyaluronan (D) were analyzed to detect possible compatibilities or incompatibilities

In vitro release

According to the data presented in Fig. 6, the in vitro release study revealed distinct release profiles for rosuvastatin from the different formulations. Rosuvastatin entrapped in hyaluronan-containing niosomes exhibited a sustained release pattern, while rosuvastatin entrapped in regular niosomes demonstrated a faster release rate, with complete release occurring within 25 h. The initial burst release observed in the niosomes without hyaluronan could be attributed to the immediate availability of rosuvastatin at the niosome’s interface, it is a common feature for many drug delivery systems intended for immediate therapeutic action. The subsequent sustained release phase, although less pronounced in this formulation, is still beneficial for maintaining drug levels above the minimum effective concentration for a prolonged period. In contrast, the hyaluronan-containing niosomes provided a more moderated release, likely due to the encapsulation of rosuvastatin within the hyaluronan matrix, which creates a barrier to rapid diffusion. This discrepancy in release rates can be attributed to the presence of hyaluronan, which is entrapped within the inner core of the niosomes. The release of rosuvastatin from a gel-like matrix (hyaluronan) within the niosomes is expected to be slower compared to a release from a solution within the niosomes, as observed in previous studies [4, 30]. The release behavior of rosuvastatin from niosomes was analyzed using different mathematical models, and the best fit was achieved with the Higuchi model, yielding an R2 value of 0.965 (as shown in Table 4). The Higuchi model is commonly used to describe the release of a dispersed drug from a homogeneous matrix, where release is controlled by the diffusion of the solvent into the matrix, following Fickian diffusion principles. Moreover, the release behavior of rosuvastatin from hyaluronan-containing niosomes conformed to the Pepas model, which further supports the controlled release mechanism observed in this study. In summary, the in vitro release study demonstrated sustained release characteristics for rosuvastatin from hyaluronan-containing niosomes and faster release kinetics from regular niosomes. The Higuchi model provided the best fit for the release behavior of rosuvastatin from niosomes, indicating diffusion-controlled release from a homogeneous matrix. The observed release profile aligns with previous research and validates the potential of hyaluronan-containing niosomes as a controlled release [5].

Fig. 6

Comparative release profiles of rosuvastatin from optimum formulations with and without hyaluronan over 25 h

Table 4 Different kinetic models fitting the release dataEffect of rosuvastatin on cell viability of DPSCs

The viability of DPSCs upon treatment with various agents is central to ensuring that any therapeutic or investigative substance does not inadvertently compromise cell health. The MTT assay, a widely recognized method for gauging cell viability, was employed to shed light on how DPSCs responded to treatments from control, blank niosome, rosuvastatin, and rosuvastatin-niosome groups.

From the data illustrated in Fig. 7, it is evident that following a 5 day treatment window, the cell viability percentages across the different groups presented some striking insights. Most notably, the viability values for cells treated with rosuvastatin and rosuvastatin-niosome closely paralleled those from the control and blank niosome groups. This congruence in viability metrics serves as a robust testament to the biocompatibility of rosuvastatin and its niosomal form. Essentially, neither rosuvastatin nor its niosome-combined form demonstrated any discernible cytotoxic effects on DPSCs.

Fig. 7

Effect of rosuvastatin and rosuvastatin- niosome on cell viability of DPSCs

Such findings, besides reinforcing the safety profile of rosuvastatin in the context of DPSCs, also underline the potential of its niosomal delivery system. The fact that rosuvastatin-niosome maintains similar viability percentages as the control and blank niosome groups points to the non-toxic nature of the niosomal system itself. The implication here is profound it suggests that the niosomal delivery doesn’t compromise the inherent safety of the drug, while possibly offering other therapeutic advantages, as alluded to in previous experiments.

Evaluation of the alkaline phosphatase activity

In the context of assessing early markers of osteogenesis, alkaline phosphatase (ALP) activity assumes paramount significance. It is customarily regarded as an initial indicator of the transition into osteoblast differentiation and, consequently, the commencement of bone matrix mineralization. Guided by this understanding, the present study ventured to elucidate the effect of both rosuvastatin and its niosomal combination on the initiation of the differentiation program in DPSCs.

Figure 8A sheds light on the ALP activity across all DPSC groups post their respective treatments. Following a span of 21 days of treatment with either rosuvastatin or the rosuvastatin-niosome, discernible variations were noted in the ALP activity. While an upsurge in ALP activity was observed in the group treated with rosuvastatin, the rosuvastatin-niosome group exhibited a notably elevated activity. This heightened activity was not only significantly above the control group but also markedly outperformed the blank niosome groups after the 21-day period.

Fig. 8

Alkaline phosphatase and Alizarin Red staining assays. ALP activity of DPSCs cultured with, rosuvastatin, rosuvastatin- niosomes and blank niosomes at day 21(8A). The effect of rosuvastatin and rosuvastatin- niosomes treatment on osteogenic differentiation of DPSCs by alizan red staining at day 21. Quantitative Alizarin red staining (8B). Accumulation of calcium deposits in rosuvastatin and rosuvastatin- niosomes groups was shown using Alizarin Red staining. DPSCs (C) Control group staining with alizan red (D) rosuvastatin group staining with alizan red (E) rosuvastatin- niosomes group staining with alizan red (F). n = 4 (*p < 0.05, **p < 0.01, and ***p < 0.001)

Drawing from these observations, it becomes apparent that the niosomal form of rosuvastatin exhibits a pronounced effect in instigating the osteogenic differentiation of DPSCs. The amplified ALP activity in the rosuvastatin-niosome group underscores the potential of niosomes in enhancing the osteogenic capability of the drug. It might be inferred that the niosome, acting as a drug delivery system, could be offering a more controlled and sustained release, leading to increased cellular uptake and, consequently, superior osteogenic outcomes.

Evaluation of the alizarin red activity

The potential osteogenic effects of rosuvastatin, both alone and in a rosuvastatin-niosome combination, were scrutinized through Alizarin red staining [31]. The purpose was to understand the impact of these treatments on bone differentiation in DPSCs.

The obtained results from Fig. 8B-F vividly depict the influence of both treatment modalities on osteoblast function in different DPSC groups. Here, the integral role of osteoblasts in bone formation and their function was marked by the intensity and extent of alizarin red staining. Post a 21-day treatment, distinct variations were observed in the staining patterns between the groups.

Analyzing calcium content, which serves as a fundamental osteogenic marker, offered intriguing insights. While there was a perceptible augmentation in the calcium content in the rosuvastatin group, it was the rosuvastatin-niosome combination that truly stood out. The alizarin red activity in this group was not only significantly higher than the control but also surpassed the results from the blank niosome group after the stipulated 21-day period. This differential staining activity, which is indicative of calcium deposition and osteoblastic activity, underscores the enhanced osteogenic potential of the rosuvastatin-niosome combination.

These outcomes present compelling evidence to suggest that niosomal encapsulation or delivery of rosuvastatin augments its osteogenic efficacy. This enhancement might be attributed to improved drug delivery, sustained release, or increased cellular uptake provided by the niosome. In essence, the rosuvastatin-niosomes do not merely promote osteogenesis but appear to also steer the programming fate of DPSCs. The underlying mechanisms warrant further exploration, but these findings pave the way for innovative therapeutic strategies in bone tissue engineering and regeneration.

Osteogenic mRNA expressions in DPSCs

The potential of rosuvastatin and rosuvastatin-niosomes in influencing osteogenic differentiation in DPSCs was investigated by examining the expression of vital osteogenic markers. Figure 9 presents the data from quantitative RT-PCR analyses which provide a detailed perspective on the behavior of these compounds when exposed to DPSCs.

Fig. 9

Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis of expression of various osteogenic related markers. Runx2, BMP-2, ALP and OCN were analyzed after exposure of DPSCs to rosuvastatin, rosuvastatin- noisome and blank niosomes at day 1,7,14 and 21. n = 4 (*p < 0.05, **p < 0.01, and ***p < 0.001)

Upon analysis, both rosuvastatin and rosuvastatin-niosomes revealed an impressive ability to upregulate the expression of crucial osteogenic-related genes, namely BMP-2, Runx2, ALP, and OCN. Here, OCN characteristically marks the late stages of osteogenesis. In contrast, BMP and ALP emerge as early to intermediate markers, playing pivotal roles during the mineralization phase. Crucially, RUNX2 has a renowned significance in osteoblast development.

Interestingly, the study showcased that the rosuvastatin-niosome setup had a clear edge, with its gene expression levels shooting up considerably higher than its counterparts: rosuvastatin, blank niosomes, and even the control group.

The garnered results shed light on the noteworthy osteogenic potential of both rosuvastatin and its niosome-incorporated variant. While rosuvastatin alone does a commendable job, encapsulating it within niosomes gives it an extra punch. This amplified osteogenic potential, as witnessed by the pronounced upregulation of osteogenic markers, is indicative of the synergy between rosuvastatin and the niosomal delivery system.

The noticeable distinction in gene expression between the rosuvastatin-niosome group and the others accentuates the potential of the niosomal system in enhancing drug delivery and efficacy. This approach seems to foster a more conducive environment for the osteogenic differentiation of DPSCs.