Optimization and characterization of hyper cross-linked cyclodextrins for improved efinaconazole delivery: A comprehensive study

Materials

β-cyclodextrin (β-CD), Carbonyldiimidazole (CDI), and dialysis membranes (Sartorius cut off 12,000 Da) were obtained from Sigma-Aldrich Chemicals Private Limited (Bangalore, India). Efinaconazole was supplied by MSN Labs Ltd. (Hyderabad, India). Carbopol 934, N-methyl-2-pyrrolidone, Triethanolamine, and Propylene glycol, were sourced from S.D. Fine Chem. Pvt. Ltd. (Mumbai, India). Throughout the study, exclusively Milli-Q water from Millipore was utilized. The investigation employed analytical-grade chemicals and reagents.

Preparation and characterization of HCDs

Optimization of variables

The synthesis variable settings for achieving the desired response were determined using the desirability approach of numerical optimization. The approach was fine-tuned by setting limits on both dependent and independent variables. To validate the statistical experimental procedures, three additional confirmation experiments were conducted, each involving different molar quantities of the components [21].

Table 1. The theoretical and observed values of different trials of taguchi design. [Click here to view]

Preparation of hyper cross-linked cyclodextrins (HCDs)

HCDs were synthesized using CDI as the crosslinking agent, following a previously detailed method [22]. The synthesis process began with the dissolution of β-CD in DMSO. Subsequently, CDI was added to the solution. Under continuous stirring, the reaction mixture was refluxed at optimum conditions. Following the completion of the reaction, the product was subjected to purification by washing with excess water and soxhlet extraction using ethanol. The white powder obtained was then dried and finely ground into a powder. The finely pulverized powder was mixed in water, and the resultant colloidal fraction was collected. Subsequently, the colloidal fraction was subjected to lyophilization to yield the powdered (NS) using a Lyodel Laboratory Scale Freeze Dryer (FD-01, Delvac Pumps Pvt. Ltd.). Ten different iterations of HCDs were generated by modifying the molar ratio between β-CD and CDI.

Efinaconazole loading into HCDs

To load efinaconazole into HCDs, the freeze-drying method was employed, following a previously outlined protocol [23,24]. Initially, the HCDs were dispersed in 50 ml of Milli-Q water while being stirred. Subsequently, an excess amount of the drug was introduced into the HCDs suspension. The mixture underwent 10 minutes of sonication, followed by continuous stirring for 24 hours. Following this, the suspensions underwent centrifugation at 2,000 rpm for 10 minutes, leading to the sedimentation of the uncomplexed drug, which settled as a residue beneath the colloidal supernatant. The colloidal supernatant was carefully collected and underwent freeze-drying under controlled conditions, specifically at a temperature of −20°C and a reduced operating pressure of 13.33 mbar. The obtained freeze-dried powder was thoroughly dried and then stored in a desiccator. The percentage of drug association was calculated using the formula 1.

$\mathit{Percent}\mathit{drug}\mathit{association}=\frac{\mathit{Weight}\mathit{of}\mathit{drug}\mathit{in}\mathit{HCDs}}{\mathit{Total}\mathit{weight}\mathit{of}\mathit{drug}\mathit{added}}\times 100(1)$

Characterization of efinaconazole loaded HCDs (EFNS)

The evaluation of EFNS characteristics encompassed parameters such as particle size, PDI, and zeta potential. Particle size analysis was executed using dynamic light scattering, employing the 90 Plus particle sizer by Brookhaven Instruments Corporation, USA. Additionally, the same instrument, augmented with an extra electrode, facilitated the measurement of zeta potential. The FTIR spectra of NS16, efinaconazole, and EFNS were recorded to identify any changes or modifications in the chemical structure of EFNS compared to the plain efinaconazole. XRD analysis was conducted on NS16, efinaconazole, and EFNS to investigate any changes in their crystalline or amorphous nature, which could provide valuable insights into the structural characteristics. DSC analysis of NS16, efinaconazole, and EFNS was conducted to study the thermal behavior and properties of the samples. To assess the morphology of NS, TEM images of EFNS were obtained to assess the morphology of drug-loaded NS.

Preparation of hydrogel formulation of efinaconazole NS

In the formulation of the efinaconazole NS gel base, Carbopol 934 was employed as described in reference [25]. To prepare a uniform 1% w/w gel base, the polymer was initially soaked in water for 2 hours. It was then dispersed in distilled water using a magnetic stirrer to ensure a homogeneous mixture. Subsequently, 1% Triethanolamine, 2% N-methyl-2-pyrrolidone, and 2% w/w Propylene glycol were introduced and stirred into the gel base. Following this, the gel base was enriched with NS loaded with efinaconazole, aiming for a concentration of 10% w/w efinaconazole in the gel base, maintaining a drug-to-carrier ratio of 10:90. As a control, a formulation was prepared by simply adding free efinaconazole to the gel base.

Characterization of the hydrogel formulation

Determination of pH

The pH of the hydrogel formulations was assessed utilizing a digital pH meter. To begin, 0.25 g of the NS-based gel was precisely weighed and dispersed in 25 ml of filtered water [26]. Before conducting the pH measurements, the pH meter was calibrated using buffer solutions with pH values of 4.0, 7.0, and 9.0. The pH of the formulation was assessed in triplicate, and the mean values were calculated for further analysis.

Preparation of HCDs

HCDs have been synthesized using different techniques, including convective heating, ultrasound, and microwave-aided synthesis. Among these methods, convective heating has been the most popular for synthesizing HCDs. However, this technique can sometimes result in the formation of reticulate complexes with multiple organic molecules [31].

Optimizing factors in the synthesis process, such as temperature, pH, concentration, solvent, catalyst, time, and pressure, can be challenging and time-consuming due to complex parameter connections. To address this, a statistical experimental design approach was employed in this investigation and optimization focused on synthesis. The design of experiments allows for exploring factor effects efficiently and accurately with fewer trials, providing relevant information on how individual and interactive factors affect the process [32].

The Taguchi statistical design is particularly useful in screening numerous parameters with fewer tests and employs OAs and ANOVA for analysis. This method helps estimate factor effects on feature attributes and structure while considering variability to determine optimal settings. Statistical assessment and experimental design are more effective in identifying relevant factors and their interactions with fewer runs compared to one-factor-at-a-time research. Taguchi experimental designs are fractional factorial designs that estimate main effects, disregarding higher-order interactions in screening research [33].

During the preliminary screening, it was determined that reaction time, reaction temperature, stirring speed, and solvent volume were the key process parameters influencing the synthesis of HCDs. The variable ranges for these parameters were defined by varying the reaction temperature, duration, stirring speed, and solvent volume. Temperatures exceeding 130°C led to the creation of reticulates, whereas temperatures below 80°C were insufficient to generate NS. An experimental approach was used to create a model for optimizing the preparation of cyclodextrin NS based on early findings.

A Taguchi OA was employed to identify the parameters affecting the particle size and percent practical yield of HCDs. Fractional factorial Taguchi OAs reduced the number of trials required to obtain maximum data. A matrix with four variables and three levels each was established to predict practical yield and particle size. Utilizing the Taguchi array consisting of nine experiments, the optimal combination of variables was identified. Preliminary point estimates from thorough pre-optimization tests were used as input functions in the statistical model for greater precision in statistical inference. All trials were duplicated three times to improve reliability.

The variance of the practical yield and particle size distribution was estimated and reported through ANOVA. ANOVA tests helped identify the variables that had the most significant impact on the response parameters. F-values in the F-distribution indicated the significance of a variable’s influence on response characteristics. By pooling control variables to error terms and increasing error freedom, ANOVA analyses provided valuable insights into the effects of factors on response parameters.

Table 2 summarizes the primary parameters influencing both the NS’ yield and particle size. The practical yield represents the actual amount of the desired product obtained after accounting for losses during the synthesis process. The practical yield directly impacts the economic efficiency of the synthesis process. A high practical yield means less wastage of raw materials, reducing production costs. It allows researchers and manufacturers to adjust reaction conditions, reagent quantities, or purification methods to improve the overall efficiency of the synthesis. When transitioning from laboratory-scale to industrial-scale production, understanding the practical yield is essential. Consistent and reproducible synthesis processes are critical in pharmaceutical manufacturing. Monitoring and optimizing the practical yield contribute to the reproducibility of the nanosponge synthesis, ensuring consistent product quality. Understanding the relationship between reaction conditions and practical yield allows for the optimization of the synthesis process [34]. For nanosponge yield, the Model F-value of 4328.14 signifies its significance, with noise accounting for only 0.01% of the “Model F-Values.” Factors A and B play crucial roles, as they have F values greater than the identification value F, indicating their substantial influence on practical yield. Factors C and D, with higher “Prob > F” values, are considered insignificant and have been removed from the model to enhance its performance. The model’s Predicted R² value of 0.9988 closely aligns with the Adjusted R² value of 0.9995, indicating a good fit. The “Adeq Precision” value of 162.589 confirms the model’s effectiveness in navigating the design space. The influence of Factor A, representing reaction temperature, on practical yield is rooted in its impact on the cross-linking process. Elevated temperatures expedite cross-linking, fostering the creation of a stable network. This acceleration enhances the overall yield by facilitating the formation of a robust structure. Likewise, Factor B, corresponding to reaction time, significantly contributes to practical yield. The extended reaction time enables thorough cross-linking, optimizing the utilization of reactants and, consequently, resulting in a higher practical yield. The equation in terms of coded factors can be used to make predictions about the response for given levels of each factor. The model equation for the response practical yield is presented in equation 2.

Table 2. Statistical analysis of regression models – ANOVA. [Click here to view]

Practical yield = 82.07 – 16.13 A[1]+12.17A[2] – 2.67 B [1] + 0.3333 B[2] (2)

A[1] and A[2] represents minimum and maximum values of A

B[1] and B[2] represents minimum and maximum values of B

This equation represents the relationship between the practical yield and the levels of factors A and B in the experimental design, allowing for prediction and optimization of the practical yield based on the chosen levels of factors A and B.

For nanosponge particle size, the Model F-value of 302.943 indicates significance, with noise accounting for only 0.01% of the “Model F-Values.” Factors C and D are particularly important, as they have F values greater than the identification value F, signifying their substantial influence on particle size. Factors A and B, with higher “Prob > F” values, are considered insignificant and were removed from the model. The predicted R² value of 0.9833 closely matches the Adjusted R² value of 0.9934, indicating a good fit. The “Adeq Precision” value of 47.748 indicates a favorable signal, demonstrating effective navigation of the design space by the model. Factor C, pertaining to stirring speed, plays a pivotal role in determining the particle size of cyclodextrin NS. The speed at which the reaction mixture is stirred significantly affects the distribution of reactants, impacting the size of the formed NS. Higher stirring speeds facilitate more efficient mixing, reducing the chances of agglomeration and leading to smaller particle sizes. Conversely, lower stirring speeds might result in inadequate mixing, potentially causing larger particle formation. Factor D, representing the volume of solvent, influences particle size through its impact on the overall reaction environment. A larger volume of solvent provides a more spacious medium for the reaction to occur. This can lead to better dispersion of reactants, potentially yielding smaller-sized NS. Conversely, a smaller volume might lead to a more concentrated environment, impacting particle size. The model equation for the response particle size is presented in equation 3.

Particle size = 253.89 + 98.78 C[1] – 11.56 C[2] – 30.22 D[1] + 0.4444D[2] (3)

C[1] and C[2] represents minimum and maximum values of C

D[1] and D[2] represents minimum and maximum values of D

This equation represents the relationship between the particle size and the levels of factors C and D in the experimental design, allowing for prediction and optimization of the particle size based on the chosen levels of factors C and D.

In Figure 1A, the residual versus projected response (practical yield) from the final model is presented, with a consistent response range variance. Figure 1B displays a comparison between predictions and actual data, showing a good match between the model and experimental results. Similarly, Figure 1C exhibits the residual vs. predicted particle size from the final model, with a constant response range variance. Figure 1D illustrates a comparison between predictions and reactions, revealing a robust agreement between the model and the experimental data.

In the context of Taguchi methodology, the signal-to-noise (S/N) ratio serves as a metric to gauge both the quality and deviation from the desired target value. In this context, “signal” refers to the mean value, while “noise” pertains to the standard deviation from the mean for the specific response parameter [35]. Equation 2 reveals the S/N ratio.

$\frac{\mathit{S}}{\mathit{N}}=-10\log (\mathit{MSD})(2)$

—Mean square deviation (MSD) of the response variable

MSD should be modest since S/N is big. Thus, MSD is defined differently for each parameter [36]. Equation 3 is used to calculate the mean squared deviation.

$\mathit{MSD}=\frac{1}{\mathit{n}}\sum _{\mathit{i}=1}^{\mathit{n}}{\mathit{y}}_{\mathit{i}}^2(3)$

‘n’ represents the number of experiments in the OA and “y_i” refers to the mean shrinkage percentage for the ith experiment.

This study employed an L9 (3^4) OA, characterized by 4 columns and 9 rows. The smaller the practical yield and particle size, the better the conditions. Table 1 demonstrates realistic yield and particle size S/N ratios. The orthogonal experimental design allows for parameter-level separation. The average S/N ratio and range (D = delta = S/Nmax S/Nmin) of each control factor at each level are computed.

In Table 3, the mean S/N ratio for each parameter level represents the practical yield. Notably, the highest values for reaction temperature and reaction time observed in Table 3 indicate their crucial role in determining the realistic yield. Similarly, Table 3 also presents the mean S/N ratio for each parameter level, which reflects the particle size. Here, the highest values for stirring speed and solvent volume highlight their significant influence on the particle size, indicating that the particle size is dependent on the solvent volume and stirring speed.

Figure 1. (A) Y1- Residuals versus predicted practical yield (B) Y1-Predicted versus actual practical yield (C) Y2- Residuals versus predicted particle size (D) Y2-Predicted versus actual particle size. [Click here to view]

By employing numerical optimization with desirability, the NS was successfully formulated to achieve the desired responses. The main objective was to identify the optimal settings for independent variables, aiming to increase practical yield and decrease particle size. The outcomes of this optimization process are presented in Table 4, displaying the optimized and expected values for Y1 (practical yield) and Y2 (particle size).

To validate the obtained results, 10 batches of NS were prepared with varying molar concentrations of β-CD and CDI, ranging from 1:1 to 1:10. The comparison between the predicted values and the actual observations for Y1 and Y2 is presented in Table 4, indicating a close match between the two sets of data. This validation process has confirmed the reliability of the model used for optimization. Ultimately, through the comparison of predicted and experimental results, the optimal conditions for nanosponge synthesis were determined, leading to the achievement of the desired responses.

Characterization of HCDs

The laser light scattering analysis of NS demonstrated an average particle size ranging from 141 to 160 nm, characterized by a low PDI. The NS exhibited a high zeta potential, indicating the stability of the complexes and making them less prone to agglomeration. Figure 2A displays the FTIR spectra of β-CD and HCDs (NS1:1-NS1:10). Under optimal experimental conditions, HCDs exhibit a carbonate bond peak within the range of 1720–1750 cm⁻¹. In contrast, the FTIR spectra of β-CD, which acts as the precursor material for the NS, do not exhibit this peak between 1720 and 1750 cm⁻¹. Importantly, the NS presents distinctive peaks at 1026 cm⁻¹ arising from the C-O stretching vibration of primary alcohol, at 2,918 cm⁻¹ arising from the C-H stretching vibration, and at 1418 cm⁻¹ arising from the C-H bending vibration. These distinctive peaks distinguish the NS (NS) from β-cyclodextrin. X-ray analysis was performed to elucidate the solid structure of the NS. Figure 2B shows the X-ray powder diffraction (XRPD) study, displaying the crystalline structure of uncross-linked plain β-cyclodextrin. In comparison to the NS, the XRPD pattern of β-CD exhibits broad reflections as small peaks. The NS, on the other hand, displays few broad reflections, suggesting a paracrystalline structure. It is noteworthy that each batch of NS created with a specific cross-linking ratio exhibits identical diffraction patterns. Differential scanning analysis was carried out to provide a comprehensive characterization of the NS. In Figure 2C, the thermogram of β-CD is shown, displaying a distinct endothermic peak at 290°C, indicative of its melting temperature. In contrast, the NS exhibited no discernible DSC peak before reaching 350°C, indicating a remarkable level of thermal stability.

Table 3. S/N values of both responses at different levels. [Click here to view]

Table 4. Validation of design. [Click here to view]

Figure 2. Results of FTIR, XRD, and DSC analysis. [Click here to view]

Preparation of efinaconazole loaded NS

NS pre-treated for drug loading resulted in nanoparticles with sizes below 150 nm. The freeze-drying method was used to load efinaconazole into distinct kinds of NS. Based on the specific type of NS utilized, the resulting drug-loaded NS formulations were designated as EFNS1 to EFNS10.

Characterization of efinaconazole-loaded NS

The analysis of particle size for efinaconazole-loaded nanosponges (EFNSs) indicated an average particle size ranging from approximately 69–84 nm, as detailed in Table 5. The PDI was notably low, denoting a tightly focused particle size distribution with minimal variability. This low PDI underscores the uniformity and consistency of the colloidal particles. Furthermore, the prominent zeta potential values suggest the potential for strong stability and a diminished tendency for particle aggregation. Notably, all formulated compositions exhibited a fine, free-flowing powder texture. This characterization was confirmed through TEM studies, illustrating that the basic spherical form and size of the plain NS were preserved even after drug encapsulation, as depicted in Figure 3. The particle size observed under TEM closely aligned with the measurements obtained through dynamic light scattering. Finally, the calculated percentages for drug loading and encapsulation efficiency for the developed efinaconazole NS are provided in Table 5.

The observed reduction in the size of the NS after loading with efinaconazole can be attributed to the intricate process of inclusion complex formation. Cyclodextrin NS, due to their unique structure and functional groups, are adept at forming inclusion complexes with guest molecules like efinaconazole. This process involves the accommodation of efinaconazole molecules within the cavities of the nanosponge network. Upon loading, the drug molecules interact with the cyclodextrin moieties through various forces such as Van der Waals, hydrogen bonding, and hydrophobic interactions. These interactions induce a structural rearrangement within the nanosponge matrix, causing it to contract or condense. The result is a more compact structure where the efinaconazole molecules are not merely adsorbed onto the surface but are intricately encapsulated within the three-dimensional network of the NS. This encapsulation serves several purposes. First, it enhances the stability of efinaconazole, shielding it from environmental factors that might degrade the drug. Second, it contributes to a more controlled release profile, as the drug is not exposed directly to the external environment but released gradually from the nanosponge matrix. Finally, the compact structure may also influence the overall physicochemical properties of the NS, such as their solubility and dispersibility [37]. Figure 2D presents a comparison of FTIR spectra between NS1:6 (NS), efinaconazole, and the efinaconazole-loaded nanosponges complex (EFNS). The FTIR analyses unveiled indications of modest interactions between NS and efinaconazole, manifesting through the broadening and vanishing of drug peaks within the complex formations. A notable change was observed in the fingerprint region (900–1,400 cm⁻¹) of the FTIR spectra when comparing efinaconazole with the complex. The main characteristic peaks of efinaconazole were identified at approximately 3193.98, 3118.76, 3022.33, 2995.32, 2688.66, 1739.72, 1587.35, 1498.62, 1452.33, 1404.12, 1272.96, 1234.39, 1213.17, 958.58, 858.22, and 665.41 cm⁻¹. The characteristic peaks of efinaconazole displayed notable broadening or shifts within the formulations, underscoring evident interactions between efinaconazole and the NS.

Table 5. Characteristics of drug-loaded NS formulation. [Click here to view]

Figure 3. TEM images (A) NS1:5 (B) NS1:6 (C) EFNS5 (D) EFNS6. [Click here to view]

To investigate the physical nature of efinaconazole within the cyclodextrin NS, XRD analysis was performed on pure efinaconazole, plain NNS6, and EFNS6. The results, as shown in Figure 2E, revealed distinctive characteristic peaks associated with efinaconazole, indicative of its prominent crystalline structure. Intriguingly, these characteristic peaks were notably absent in the EFNS6. The conspicuous absence of these crystalline peaks in EFNS6 strongly supports the inference that the drug is effectively encapsulated within the NS.

In Figure 2F, the DSC curves of three samples: free efinaconazole, plain NS6, and the efinaconazole nanosponges complex (EFNS6) were observed. The DSC spectra of efinaconazole display a distinct and sharp endothermic peak at 191.1°C, signifying its melting point. However, the DSC spectra of the NS exhibit exothermic peaks at approximately 350°C. Intriguingly, the efinaconazole complex also displays a broad exothermic peak around the same temperature of 350°C. Notably, for the formulations obtained through the freeze-drying process, the drug’s endothermal peak is absent. This phenomenon strongly suggests interactions among the formulation components, indicating potential drug amorphization and/or the formation of inclusion complexes. The collective results from FTIR, DSC, and XRD studies definitively confirmed the presence of an inclusion complex between efinaconazole and the NS.

Figure 4A presents the dissolution profiles of both pure efinaconazole and the efinaconazole nanosponge complexes (EFNS1-EFNS10) in a simulated gastric medium. The results from in-vitro release studies showcase a substantial enhancement in the release rate of the complex when compared to the pure drug. The dissolution rate of pure efinaconazole remains relatively low, staying below 14% within 12 hours. In contrast, the nanosponge-encapsulated efinaconazole demonstrates a significantly faster and improved dissolution profile. The percentage of efinaconazole released from the nanosponge formulations after 12 hours shows a range between 64.54 and 99.68 %.

The diffusion of pure efinaconazole exhibited a mere 7% release within 120 minutes, while the drug encapsulated in NS demonstrated a notably swifter release. Within the first 60 minutes, an average of 19.96%—37.89% efinaconazole was released, showcasing a rapid burst release phenomenon. This initial rapid release is commonly ascribed to the portion of efinaconazole that is either adsorbed or encapsulated as a non-inclusion complex on the surface of the NS. When the formulation is introduced into the release medium, this portion of efinaconazole swiftly diffuses into the surrounding liquid.

Figure 4. (A) Efinaconazole release from NS in vitro (B) Stability study results (C) In-vitro skin permeation of efinaconazole in gel and control in SC (D) In-vitro skin permeation of efinaconazole in gel and control in Epidermis and dermis. [Click here to view]

The maximum release of efinaconazole after 6 hours was observed in EFNS1 and EFNS2, reaching 98.89%–94.53%, respectively. In contrast, other NS exhibited a gradual reduction in release rate after this initial burst. This sustained and gradual release of efinaconazole can be ascribed to the diffusion of efinaconazole entrapped within the NS in the form of an inclusion complex, contributing to extended drug release over time.

EFNS3, EFNS4, EFNS5, and EFNS6 displayed a relatively modest burst effect and demonstrated more favorable sustained release properties upon drug loading. This behavior could be attributed to a higher proportion of efinaconazole forming an inclusion complex within the NS. Conversely, the relatively higher occurrence of non-inclusion complexation in EFNS1 and EFNS2 might be due to efinaconazole’s limited access to the larger network of channels and pores within the structure. Additionally, the incomplete release of the drug from NS7 to NS10 could be attributed to the higher cross-linking density, which likely hindered the dissolution of the drug. Given the controlled release nature of EFNS6, it was selected for further investigation to formulate a topical hydrogel. The decision was based on its potential to regulate the release of efinaconazole effectively.

Efinaconazole gel formulation

Following literature guidance, the gel base formulation was developed by incorporating EFNS and utilizing Carbopol 934 polymer. Carbopol is a widely used base for topical preparations and is a hydrogel-forming polymer of acrylic acid. When in contact with water or alkaline solutions, the carboxyl groups in Carbopol hydrate, resulting in the formation of a hydrogel [16]. The formulation of EFNSincorporated Carbopol 934 hydrogel along with 2% w/w of Propylene glycol and 2% w/w of N-methyl-2-pyrrolidone as permeation enhancers. For gel neutralization, 1% w/w of Triethanolamine was employed. This approach mirrors a prior study that utilized a similar Carbopol hydrogel composition, leading to improved stability and permeation of Econazole nitrate [17]. Both formulations exhibited a pH ranging from 4.98–5.65, aligning with the skin’s typical pH range of 3.0–9.0. This observation underscores the non-irritating nature of the preparation.

The photodegradation studies encompassed three variants: free efinaconazole, a Carbopol gel formulation incorporating free efinaconazole (EFgel), and l formulation embedding efinaconazole-loaded nanosponges (EFNSgel). These formulations were subjected to exposure under a UVA lamp possessing a wavelength range of 320–400 nm. This experiment aimed to quantify the extent of degradation that occurred due to the UVA irradiation. Upon exposure to the UVA lamp, the gel formulation containing pure efinaconazole experienced degradation of approximately 17.82% ± 1.26% of the drug. However, a significant reduction in the extent of efinaconazole. Photodegradation was observed in the formulations incorporating the NS-encapsulated efinaconazole. This outcome underscores the protective influence of the NS against Photodegradation. To assess whether the enhancement of efinaconazole Photostability was a result of the gel formulation, dedicated Photostability experiments were conducted using free efinaconazole. The outcomes revealed that when the drug was exposed directly to the UVA lamp, approximately 21.73% ± 2.08% of the drug experienced degradation. This finding suggests that the Carbopol gel formulation contributes to a degree of protection against photodegradation.

To further evaluate whether the NS contributed to the enhanced Photostability of efinaconazole and if this effect varied with time, additional photolysis experiments were conducted after the same formulations had been stored for 3 months at room temperature in the absence of light. This aspect aimed to mimic storage conditions that the formulations could undergo during practical use. The observed percentage loss of efinaconazole upon irradiation of the studied formulations is presented in Table 6. These results provide insights into the potential benefits of NS encapsulation in enhancing the Photostability of efinaconazole formulations.

To investigate the potential impact of NS on the chemical stability of efinaconazole, an extended aging study was conducted using the same formulations as those utilized in the photodegradation experiments. The formulations were subjected to analysis for 6 months, under controlled conditions of room temperature and darkness. The outcomes of this aging study are depicted in Figure 4B. During the 6 months, a degradation of approximately 14.68% was observed for free efinaconazole, while the gel formulation containing non-encapsulated efinaconazole experienced a degradation of approximately 9.6%. Strikingly, the formulations containing efinaconazole encapsulated within NS exhibited no significant decline in the efinaconazole content after the same duration of time. These findings underscore the protective capabilities offered by cyclodextrin NS, as they effectively prevent the chemical degradation of efinaconazole even under conditions that could potentially induce degradation. This observation further supports the potential advantages of utilizing NS encapsulation for enhancing the stability of pharmaceutical formulations.

Table 6. Photodegradation values for free and nanosponge encapsulated efinaconazole in gel formulations, immediately after preparation and after 3-month storage. [Click here to view]

The investigation into in-vitro skin permeation involved the assessment of NS-encapsulated efinaconazole gel formulations, with a Carbopol gel formulation containing free efinaconazole as the control counterpart. This experimental setup aimed to ascertain whether the observed enhancement in skin permeation was solely attributed to the gel formulation. As part of this exploration, skin permeation studies were also conducted using free efinaconazole dissolved in propylene glycol. In the context of our study, samples were extracted from the receptor media at specific time intervals (0.5, 1, 2, 4, 6, 8, 10, and 12 hours) to monitor potential transdermal delivery of efinaconazole. It is noteworthy that no trace of efinaconazole was detected in the receptor phase after the 12-hour application duration of both the control and the test formulations. This outcome indicates a lack of significant transdermal delivery of efinaconazole in the context of this study. Therefore, it can be inferred that the formulations, despite their variations, did not facilitate substantial penetration of efinaconazole through the skin over the given time frame.

Upon completion of the 12-hour permeation study, an assessment was made regarding the quantity of efinaconazole that had permeated and been deposited within the SC as well as the epidermis and dermis layers of the rat skin. Comparative analysis revealed that, in contrast to the efinaconazole solution in propylene glycol, both the Carbopol gel formulations containing encapsulated and non-encapsulated efinaconazole exhibited a significant enhancement in efinaconazole penetration into the skin 12 hours post-application. Specifically, the cumulative quantities of efinaconazole observed from the propylene glycol solution and the Carbopol gel formulation EFgel after the 12-hour dosing period were 6.74 ± 0.53 μg/cm² and 10.25 ± 0.92 μg/cm², respectively. In simpler terms, the cumulative quantity of efinaconazole that permeated the skin from the free efinaconazole gel formulation was approximately 1.52 times greater than that achieved through the propylene glycol solution within the same 12-hour timeframe. This difference highlights the significant impact of the gel formulation on the enhancement of efinaconazole skin penetration capabilities.

When comparing the Carbopol gel formulations of free efinaconazole, gel formulation containing encapsulated efinaconazole exhibited a substantial increase in efinaconazole skin penetration capabilities 12 hours after application. Specifically, the cumulative amounts of efinaconazole from the Carbopol gel formulations (EFgel, EFNSgel) at the 12-hour mark after dosing were measured at 10.25 ± 0.92 μg/cm² and 32.18 ± 1.43 μg/cm², respectively. This indicates that the cumulative amount of efinaconazole penetrating through the skin from the gel formulation containing encapsulated efinaconazole was over 3.14 times greater than that from the gel formulation containing free efinaconazole within the same 12-hour timeframe. Notably, the gel formulation with NS-encapsulated efinaconazole demonstrated a fivefold increase in permeation through the skin compared to efinaconazole in propylene glycol.

In Figures 4C and 4D, we present the distribution pattern of efinaconazole within the excised rat skin. The time-course analysis of in-vitro efinaconazole skin penetration revealed a significant enhancement in its concentration within the SC at 3 hours, 6 hours, 9 hours, and 12 hours post-application when efinaconazole was incorporated within the NS. Similarly, the concentration of efinaconazole within the epidermis/dermis [(E + D)] also experienced significant enhancement at these time intervals (p < 0.05). This heightened permeation and deposition of efinaconazole can be attributed to the combined effects of NS encapsulation and the penetration-enhancing attributes of the Carbopol gel formulation. This underscores the potential synergy between NS and the gel base in enhancing efinaconazole skin penetration capabilities.