Multiobjective optimization of fluphenazine nanocomposite formulation using NSGA-II method

The primary chemical materials used in this research were fluphenazine deaconate (FZN) (a gift from Hikma Pharmaceutical Inc., lot No. RAC163USP0FC, purity of 99%), CS (low molecular weight 10–120 kDa, 90% deacetylation, lot No. STBH7664) by Sigma-Aldrich (Taufkirchen, Germany), and sodium TPP by AZ Chemical Inc. (lot No. 1161/1162). All other chemical materials, including acetic acid, acetone, sodium hydroxide (NaOH), acetonitrile, methanol, and ammonium acetate, were purchased from Sigma-Aldrich.

The nanocomposite was fabricated using a well-known process called ionotropic gelation (IG). This IG procedure was first developed by Calve [34]. Through ionic interaction between CS with a positive charge of the amino acid group and TPP with a negative charge of a phosphate group, it forms gels [35]. The NPs are formed accordingly by mixing the mixture in a specific range of proportions for each starting material.

In this study, the first step in fabricating (FZNCSNPs) was to separately prepare the three solutions (i.e., CS, TPP, and FZN). The CS was dissolved in 2% w/v acetic acid solution to form CS solutions of 0.5–1.6% w/v. The TPP was dissolved in 50 mL water to form solutions of 1.0–3.2% w/v, whereas FZN was dissolved in 20 mL acetone to form solutions of 0.6–1.7% w/v. The second step was adding the FZN solution over the CS solution gradually using a burette. The last step was adding the TPP solution over the mixture of CS-FZN gradually, using a burette in a dropwise manner to form FZN-CSNPs nanocomposite while mixing the solution under vigorous mixing by a magnetic stirrer for 3 h. Finally, the solution’s pH should be adjusted using 10% NaOH to either 4.0 or 6.0. The proportions of materials were determined by the mixture design generated by Minitab software. All solutions were collected and evaluated in terms of size, ZP, and drug loading percentage.

Blank samples (CSNPs) were also prepared in this study as controlled samples in the characterization phase. The same procedure as mentioned above was performed with no additional step of the FZN solution. All solutions were prepared at room temperature and centrifuged (at 5,000 rpm for 15 min) to remove the supernatant. Finally, the obtained solutions were lyophilized using freeze dryer (by Martin Christ, Osterode-Germany) with a total cycle of 48 h for further characterization studies. The final samples were kept at room temperature. NPs fabrication process are summarized in Figure 2.

Fig. 2

It is essential to control NPs properties in the fabricating process to indicate and monitor the stability and effectiveness of NPs drug delivery systems. A small NPs size (<200 nm) improves drug permeability and diffusion in the body [36].

On the other hand, ZP is also one of the essential NPs characteristics. ZP indicates the surface electrostatic charge of the NPs. However, a high degree of ZP reflects high resistance to agglomeration, which provides high stability of NPs. The magnitude of ZP (positive or negative) is referred to as the degree of repulsion between particles [37]. ZP values >30 mV indicate good stability and those >60 mV excellent stability. A value of about 20 mV provides only short-term stability; values in the range of −5 mV to +5 mV provide insufficient stability and fast precipitation as a result [38].

LE is another essential characteristic for NPs drug delivery systems. A higher drug LE is desired. LE refers to the percentage of drug that is successfully entrapped into NPs carriers.

NPs size and ZP for the nanocomposite were measured by dynamic light scattering (DLS) technique using Zetasizer Nano (by Malvern, Worcestershire-UK) at Hikma Pharmaceutical Inc. The ultra-centrifuge technique was used to determine FZN drug-free percentage in the prepared nanocomposite. The analysis method was as follows: 5 mL of solution was centrifuged at 5,000 rpm for 30 min, and then the supernatant solution was measured using high-performance liquid chromatography (HPLC) at 260 nm wavelength. Intersil® ODS-3V (5 μm, 4.6 mm × 250 mm) HPLC column was used to analyze the samples. The mobile phase was prepared by mixing 400 mL of methanol, 400 mL acetonitrile, and 200 mL of 0.05 M ammonium acetate. Finally, the mobile phase mixture was filtrated through a 0.45 μm PTFE syringe filter. The column temperature was kept at 25°C temperature, and the flow rate was 2 mL/min.

A calibration curve was constructed by measuring known concentrations of FZN solutions using HPLC and then plotting the peak area vs. the FZN drug amount. However, the FZN drug-free amount was determined using Eq. (1), and then the percentage of drug loaded in nanocomposite (LE%) was calculated using Eq. (2). (1) FZN drug free (mg)=0.1541 (peak area from HLC)+0.0266 \matrix{{{\rm{FZN}}\,{\rm{drug}}\,{\rm{free}}\,({\rm{mg}}) =} \hfill\cr{0.1541\,({\rm{peak}}\,{\rm{area}}\,{\rm{from}}\,{\rm{HLC}}) + 0.0266} \hfill\cr} (2) % (LE)=FZN added in mixture (mg)−FZN drug free (mg)Mass of (FZN_CSNPs) (mg)×100% \matrix{{\% \,({\rm{LE}}) =} \hfill\cr{{{{\rm{FZN}}\,{\rm{added}}\,{\rm{in}}\,{\rm{mixture}}\,({\rm{mg}}) - {\rm{FZN}}\,{\rm{drug}}\,{\rm{free}}\,({\rm{mg}})} \over {{\rm{Mass}}\,{\rm{of}}\,({\rm{FZN}}\_{\rm{CSNPs}})\,({\rm{mg}})}}} \hfill\cr{\times 100\%} \hfill\cr}

Multivariate regression analysis was carried out on the data collected from the experimental design discussed above, and P-values with a 95% confidence interval (CI) were calculated to determine each model term’s significance using Minitab. The predictors that explain the correlation with the responses were included in the regression model equations accordingly.

ANOVA indicates that all NPs input fabrication parameters are statistically significant. Besides, the predictors’ interactions showed high statistical significance (P-values are less than the significance level of 0.05). Three regression models have been generated accordingly. Eqs (5)–(7) represent the regression equations for the three objectives generated after performing mixture regression analysis using Minitab. (5) NPs Size=8860.6768(FZN)+0.2326(CS)−12.0924(TPP)−148.0605(FZN)×(CS)−144.0752(FZN)×(TPP)+1.2233(FZN)×(CS)×(TPP)−0.6309(FZN)×(CS)×(FZN−CS)−0.5744(FZN)×(TPP)×(FZN−TPP)−0.0065(CS)×(TPP)×(CS−TPP)−1.5431(TPP)×(pH)(TPP−pH)+0.8092(FZN)×(CS)×(pH)−0.1900(FZN)×(TPP)×(pH)−0.0207(FZN)×(CS)×(TPP)×(pH)+0.0061(FZN)×(CS)×(FZN−CS)×(pH)−0.0108(FZN)×(TPP)×(FZN−TPP)×(pH)+0.0012(CS)×(TPP)×(CS−TPP)×(pH) \matrix{{{\bf{NPs}}\,{\bf{Size}}} \hfill & {= 8860.6768(FZN) + 0.2326(CS)} \hfill\cr{} \hfill & {- 12.0924(TPP) - 148.0605(FZN)} \hfill\cr{} \hfill & {\times (CS) - 144.0752(FZN) \times (TPP)} \hfill\cr{} \hfill & {+ 1.2233(FZN) \times (CS) \times (TPP)} \hfill\cr{} \hfill & {- 0.6309(FZN) \times (CS) \times (FZN - CS)} \hfill\cr{} \hfill & {- 0.5744(FZN) \times (TPP) \times (FZN - TPP)} \hfill\cr{} \hfill & {- 0.0065(CS) \times (TPP) \times (CS - TPP)} \hfill\cr{} \hfill & {- 1.5431(TPP) \times (pH)(TPP - pH)} \hfill\cr{} \hfill & {+ 0.8092(FZN) \times (CS) \times (pH)} \hfill\cr{} \hfill & {- 0.1900(FZN) \times (TPP) \times (pH)} \hfill\cr{} \hfill & {- 0.0207(FZN) \times (CS) \times (TPP) \times (pH)} \hfill\cr{} \hfill & {+ 0.0061(FZN) \times (CS) \times (FZN - CS)} \hfill\cr{} \hfill & {\times (pH) - 0.0108(FZN) \times (TPP)} \hfill\cr{} \hfill & {\times (FZN - TPP) \times (pH) + 0.0012(CS)} \hfill\cr{} \hfill & {\times (TPP) \times (CS - TPP) \times (pH)} \hfill\cr} (6) ZP=5612.9998(FZN)+0.6278(CS)+1.3833(TPP)−103.0432(FZN)×(CS)−104.3974(FZN)×(TPP)−0.0102(CS)×(TPP)−0.6714(FZN)×(CS)×(FZN−CS)−0.7087(FZN)×(TPP)×(FZN−TPP)+0.0224(FZN)×(FZN)×(CS)×(TPP)+0.0074(FZN)×(CS)×(CS)×(TPP)+0.0072(FZN)×(CS)×(TPP)×(TPP)−0.0020(FZN)×(CS)×(FZN−CS)^2−0.0023(FZN)×(TPP)×(FZN−TPP)^2+0.0270(TPP)×(pH)−0.0021(CS)×(TPP)×(pH)−0.000002(FZN)×(CS)×(FZN−CS)^2×(pH) \matrix{{{\bf{ZP}}} \hfill & {= 5612.9998(FZN) + 0.6278(CS)} \hfill\cr{} \hfill & {+ 1.3833(TPP) - 103.0432(FZN) \times (CS)} \hfill\cr{} \hfill & {- 104.3974(FZN) \times (TPP) - 0.0102(CS)} \hfill\cr{} \hfill & {\times (TPP) - 0.6714(FZN) \times (CS) \times (FZN - CS)} \hfill\cr{} \hfill & {- 0.7087(FZN) \times (TPP) \times (FZN - TPP)} \hfill\cr{} \hfill & {+ 0.0224(FZN) \times (FZN) \times (CS) \times (TPP)} \hfill\cr{} \hfill & {+ 0.0074(FZN) \times (CS) \times (CS) \times (TPP)} \hfill\cr{} \hfill & {+ 0.0072(FZN) \times (CS) \times (TPP) \times (TPP)} \hfill\cr{} \hfill & {- 0.0020(FZN) \times (CS) \times (FZN - CS)\^2} \hfill\cr{} \hfill & {- 0.0023(FZN) \times (TPP) \times (FZN - TPP)\^2} \hfill\cr{} \hfill & {+ 0.0270(TPP) \times (pH) - 0.0021(CS) \times (TPP)} \hfill\cr{} \hfill & {\times (pH) - 0.000002(FZN) \times (CS)} \hfill\cr{} \hfill & {\times (FZN - CS)\^2 \times (pH)} \hfill\cr} (7) LE%=−54.5475(FZN)+0.2568(CS)+0.3063(TPP)+0.7362(FZN)×(CS)+0.6385(FZN)×(TPP)+0.0268(CS)×(TPP)+0.0003(FZN)×(FZN)×(CS)×(TPP)+0.0001(FZN)×(CS)×(CS)×(TPP)+0.00004(FZN)×(CS)×(TPP)×(TPP)+24.8426(FZN)×(pH)+0.1000(CS)×(pH)+0.1301(TPP)×(pH)−0.3433(FZN)×(CS)×(pH)−0.2450(FZN)×(TPP)×(pH)−0.0071(CS)×(TPP)×(pH)−0.0001(FZN)×(FZN)×(CS)×(TPP)×(pH)+0.0001(FZN)×(CS)×(CS)×(TPP)×(pH) \matrix{{{\bf{LE}}\%} \hfill & {=- 54.5475(FZN) + 0.2568(CS)} \hfill\cr{} \hfill & {+ 0.3063(TPP) + 0.7362(FZN) \times (CS)} \hfill\cr{} \hfill & {+ 0.6385(FZN) \times (TPP) + 0.0268(CS)} \hfill\cr{} \hfill & {\times (TPP) + 0.0003(FZN) \times (FZN) \times (CS)} \hfill\cr{} \hfill & {\times (TPP) + 0.0001(FZN) \times (CS) \times (CS)} \hfill\cr{} \hfill & {\times (TPP) + 0.00004(FZN) \times (CS) \times (TPP)} \hfill\cr{} \hfill & {\times (TPP) + 24.8426(FZN) \times (pH)} \hfill\cr{} \hfill & {+ 0.1000(CS) \times (pH) + 0.1301(TPP)} \hfill\cr{} \hfill & {\times (pH) - 0.3433(FZN) \times (CS) \times (pH)} \hfill\cr{} \hfill & {- 0.2450(FZN) \times (TPP) \times (pH)} \hfill\cr{} \hfill & {- 0.0071(CS) \times (TPP) \times (pH)} \hfill\cr{} \hfill & {- 0.0001(FZN) \times (FZN) \times (CS) \times (TPP)} \hfill\cr{} \hfill & {\times (pH) + 0.0001(FZN) \times (CS) \times (CS)} \hfill\cr{} \hfill & {\times (TPP) \times (pH)} \hfill\cr}

The main effect plots are considered a visualization method to examine how the pH influences the responses to the question of whether the variables interact. Figure 5 indicates that the pH significantly affects the three responses with differing patterns because the main effect line is not drawn horizontally in any of the predictors. As pH increases, NPs size and ZP decrease, as indicated in Figure 5A, 5B. In contrast, LE% increases as the pH value increases, as indicated in Figure 5C.

Fig. 5

Figure 6A–6C shows the contour plots for the three responses. The plots at the left side represent the mixture formulation when prepared at the low pH level (i.e., pH = 4.0), whereas the plots at the right side represent the high level of pH (i.e., pH = 6.0). The region that is within the solid gray lines represents the design space of the study.

Fig. 6

Figure 6A represents the contour plots for size and illustrates how proportions of the component’s mixture affect the size of NPs. If the mixture’s component proportions are chosen from the lower-left corner of the study design space, NPs size would be the smallest. On the other hand, NPs size would increase if the mixture’s component proportions are chosen from the design space’s right corner (regardless of the solution’s pH). In both plots (right and left), the light gray area represents the best for size. Since the NPs size would be reduced at a low pH level, the effect of the process variable (i.e., pH of solution) on size is perceptible in the case of both plots. The left corner area represents the best blend of the components within the constrained design space. Preparing FZN-CSNPs nanocomposite with reference to the design space study region and using the following NPs input fabrication parameters, i.e., FZN = 15%, CS = 62.5%, TPP = 22.5%, and pH = 4.0, similar to the F24 parameters shown in Table 1, would produce NPs with small sizes.

Figure 6B represents the contour plots for ZP. The light gray area represents the worst for ZP (lowest values). On the other hand, the dark gray area (at the lower-left corner) represents the best for ZP (highest values), especially at a lower pH level. Preparing FZN-CSNPs nanocomposite with reference to the design space study region and using the following NPs input fabrication parameters, i.e., FZN = 15%, CS = 62.5%, TPP = 22.5%, and pH = 4.0, similar to the F24 parameters shown in Table 1, would produce NPs with best ZP values. The contour plots for LE are demonstrated in Figure 6C. The light gray areas in the entire design space represent the lowest LE values (especially at the upper corner). In comparison, the dark gray area represents the best for LE (highest values) that are located at the middle borderline. Preparing FZN-CSNPs nanocomposite with reference to the design space study region and using the following NPs input fabrication parameters, i.e., FZN = 15%, CS = 22.5%, TPP = 62.5%, and pH = 6.0, similar to the F24 parameters shown in Table 1, would produce NPs with best LE values.

In summary, one mixture with a high percentage of CS, low percentage of TPP, and low pH value is required to achieve the first two objectives (NPs size maximization and ZP minimization). In contrast, a mixture with a low percentage of CS, a high percentage of TPP, and high pH is required to achieve the third objective (LE maximization). Nevertheless, in all cases, a high percentage of FZN is required to achieve the three objectives. Thus, there was a need for the use of NSGA-II to deal with these conflicting objectives.

PdI values were in the range of 0.20–0.25. Results show that the proposed mixture system has nearly uniform NPs in terms of size.

The thermograms of FZN, CSNPs, and FZNCSNPs nanocomposite are illustrated in Figure 8A–C, respectively. The DSC curve of pure FZN at Figure 8A exhibits a strong peak temperature of 29.3°C, corresponding to its melting point. Polymer CSNPs in Figure 8B has shown peak at a temperature of 58.6°C. The FZN-CSNPs nanocomposite in Figure 8C has shown a minor peak at 41.9°C, and the peak position at FZN was found to have disappeared, which can be attributed to the fact that FZN can be molecularly dispersed into the CS polymer matrix.

Fig. 8

Figure 9 shows the FZN drug release profile from FZN-CSNPs nanocomposite into a solution of phosphate buffer saline (PBS) with pH 7.4. The drug release pattern out over 72 h (4,320 min) is divided into two stages; of these the first is an initial fast release, where 35% of the drug was released through 60 min. The initial burst release (i.e., at a rapid rate) from the CS NPs may be caused by the polymer’s swelling, creation of pores, or diffusion of the drug from the polymer’s surface [58].

Fig. 9

In the second stage, the drug release becomes gradual in a slow pattern over the 3 days of the study. Forty-eight percent of the drug was released at the end of day 1, 62% at the end of day 2, and 74% at the end of day 3. The daily drug release rate indicated that it was relatively constant at the end of day 2, with around 12%. Thus, the drug needs at least 5 days to be completely released (100%). This sustained-release pattern improves patient compliance and adherence to the dosing by reducing the administration frequency and doses [59].

The XRD instrument was used to determine the crystal structures of powder materials. Figure 10A–D shows the XRD patterns of FZN, CSNPs, FZN-CSNPs nanocomposite, and physical mixture of FZN with CSNPs, respectively. Three strong diffraction peaks were observed in the FZN (powder) at the following 2θ of 17.3, 19.3, and 22.5 (Figure 10A).

Fig. 10

The diffractogram of CSNPs NPs at Figure 10B displayed two amorphous peaks at 2θ of 19.1 and 24.9 with a characteristic broad hump for the second peak [60]. The ionic interaction between TPP and protonated CS () leads to the formation of these CSNPs. The absence of any other diffraction peaks corresponding to impurities (such as TPP) were indicative of their purity. In FZN-CSNPs nanocomposite, however, no such crystalline peak of FZN was observed (Figure 10C). This result indicates that the FZN encapsulated in CSNPs is in the polymeric matrix’s amorphous form. This form of FZN inside the CS polymeric matrix produces benefits by ensuring sustained release of the FZN from the CSNPs NPs [61]. For the physical mixture of FZN and CSNPs at Figure 10D, all characteristic crystalline peaks of FZN were observed with less intensity (labeled as *), this result again confirming the amorphous properties of FZN in the nanocomposites [62].

Figure 11 demonstrates the chemical interactions between the three components (i.e., FZN, CS, and TPP) to form the FZN-CSNPs nanocomposites. The Fourier-transform infrared spectra of pristine FZN, CSNPs, and FZN-CSNPs nanocomposite are shown in Figure 12A–12C, respectively. The spectrum of FZN (Figure 9A) shows different absorption peaks; for example, the band at 3,200 cm⁻¹ is related to the O-H stretching vibrations, while the band at 3,053 cm⁻¹ is related to the C-H stretching vibrations of rings 1 and 2 (Figure 11). The band at 1,602 cm⁻¹ was related to the stretching vibrations of C-S-C and C-C at rings 1 and 2. The bands at 1,240 cm⁻¹ are related to the stretching vibration of C-H at rings I and II and also the stretching vibration of CF_–3–[63].

Fig. 11

Fig. 12

The FTIR spectra of CSNPs is shown in Figure 12B. A peak at 3,418 cm⁻¹ was observed for the main functional group of CS and is due to the O-H group of stretching vibrations. The presence of absorption peaks at 1,639 cm⁻¹ and 1.573 cm⁻¹ are due to the N-H bending vibration of the protonated amino (NH_–2–) group and the C-H bending vibration of the alkyl group [64, 65, 66]. The absorption peaks at 1,039 cm⁻¹ and 896 cm⁻¹ are recognized due to the anti-symmetric stretching vibration of C–O–C bridges and assigned to glucopyra-nose ring in CS matrix.

FTIR spectrum of the FZN-CSNPs nanocomposite (in Figure 12C) shows the characteristic peaks for FZN, confirming that the drug was loading in the final formulation. For instance, the peaks at 1,243 cm⁻¹ were due to C–H’s stretching vibration at rings I and II and stretching vibration of CF3. From Figure 11, it can be seen that FZN has protonated the nitrogen atom due to the pH condition of preparation. Therefore, the positive charge of FZN can interact with a negative charge of phosphate ions.