# Design and Optimization of Solid Lipid Nanoparticles Loaded with Triamcinolone Acetonide

^{1}

^{2}

^{3}

^{*}

## Abstract

**:**

## 1. Introduction

#### Experimental Design Approaches on Lipid Nanocarriers

^{n}or 3

^{n}, and, for this reason, full factorial designs are usually implied for screening a minor number of variables. Other experimental designs, with reduced amounts of experimental runs, were created to overcome the exponential growth of samples to be analyzed. Plackett–Burman designs are considered effective screening designs of experiments when a large number of factors is involved, as they require only a number of experiments [8] that correspond to the first multiple of four higher than the factors to be screened. For this reason, these kinds of designs are also used as preliminary screening for more complete, full factorial designs. In the study performed by Shah et al., a Plackett–Burman design was implemented to study the influence of six parameters on the synthesis of Levofloxacin-loaded solid lipid nanoparticles (SLN), and then a three-level, full factorial design was used to monitor the most relevant factors selected and their influence on the responses with a higher degree of resolution [9]. Optimization designs, also known as surface response methodologies, are implemented on already consolidated processes or when previous screening on the relevant variables was performed. Each factor to be optimized is studied at least in three levels, allowing the study of quadratic and cubic terms to be included in the polynomial equation used to predict the behavior of a selected response, where a combination of independent factors could contribute in a synergistic (positive sign) or antagonistic way (negative sign) to the response [10]. The most-used kind of optimization design is the Central Composite Design (CCD), based on a classical full factorial design, with the addition of center points and the so-called star points, which are intermediate points located at a precise distance, called alpha, from the design center (Figure 1 [11]). The alpha value determines the kind of Central Composite Design obtained [5,12]. With the use of CCDs, the simultaneous optimization of parameters can be achieved through the use of desirability functions. In this way, a set of possible solutions is proposed in function of the established goal for each response, with an assigned desirability index (DI) from 0 to 1 that provides an overall measure of how well the combination of factors satisfies the desired goals.

## 2. Results and Discussion

#### 2.1. Central Composite Design

^{2}, non-significance for the Lack of Fits, and ANOVA adequate precision, which ensures the signal-to-noise ratio of each model and guarantees its ability to distinguish significant measurements from statistical noise.

#### 2.1.1. Model Determination for Zeta Average

#### 2.1.2. Model Determination for Zeta Potential

#### 2.2. Optimized Formulation

#### 2.3. Encapsulation Efficiency of the Optimized Formulation

^{2}= 0.9992 and equation y = 145122x) (LOD 0.1 ppm, LOQ 1 ppm). Using Size Exclusion Chromatography as a purification method, the resulting encapsulation efficiency of the TA-loaded solid lipid nanoparticles is equal to 94 ± 4%.

## 3. Materials and Methods

#### 3.1. Materials

^{®}G-50 were purchased by Sigma Aldrich (Milano, Italy).

#### 3.2. Preparation of TA-SLN

#### 3.3. Particle Size and Zeta Potential Measurements

#### 3.4. Experimental Design

#### 3.5. Purification from Unentrapped Triamcinolone Acetonide

^{®}G-50, (Cytiva, Marlborough, MA, USA). Fractions corresponding to 3 column volumes were collected, and the ones containing Triamcinolone Acetonide were combined and concentrated to determine the overall encapsulation efficiency (EE%) of TA-SLN.

#### 3.6. HPLC-DAD Method for Detection and Quantitation of Triamcinolone Acetonide

_{2}O 0.1% v/v formic acid and B: Acetonitrile 0.1% v/v formic acid at the ratio of A:B = 60:40 (% v/v). Chromatograms were recorded at 240 nm. The sample injection volume was fixed at 3.00 µL. For the quantitation of Triamcinolone Acetonide from purified SLN samples, a linear calibration curve was obtained between the concentration ranges of 0.5 and 25 ppm. The encapsulation efficiency of the optimized formulation of TA-SLN was obtained using Equation (5):

## 4. Conclusions

## Supplementary Materials

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## Sample Availability

## References

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**Figure 2.**Contour (

**a**) and perturbation plots (

**b**) for the particle Zeta average model. Graphs are reported in the transformed scale. The red dot represents experimental design points.

**Figure 3.**3D surface plots for AB (

**a**), BC (

**b**), and AC (

**c**) terms. Each missing factor is fixed at its mean level. The red dot represents experimental design points.

**Table 1.**Zeta average, polydispersity index, and Zeta potential values obtained for each experimental run.

Run | Z-Average (nm) | PDI | Zeta Potential (mV) |
---|---|---|---|

1 | 733 ± 44 | 0.16 ±0.14 | −39.5 ± 0.7 |

2 | 628 ± 4 | 0.43 ± 0.05 | −43.3 ± 1.3 |

3 | 843 ± 60 | 0.18 ± 0.09 | −43.6 ± 0.6 |

4 | 2418 ± 232 | 0.21 ± 0.12 | −38.9 ± 2.3 |

5 | 869 ± 62 | 0.26 ± 0.30 | −39.8 ± 0.1 |

6 | 917 ± 64 | 0.22 ± 0.07 | −39.7 ± 0.1 |

7 | 735 ± 10 | 0.16 ± 0.15 | −41.3 ± 0.5 |

8 | 933 ± 63 | 0.30 ± 0.11 | −39.9± 0.2 |

9 | 833 ± 60 | 0.27 ± 0.05 | −39.8 ± 0.2 |

10 | 656 ± 71 | 0.34 ± 0.30 | −31.1 ± 0.7 |

11 | 2986 ± 712 | 0.44 ± 0.15 | −32.1 ± 1.7 |

12 | 867 ± 61 | 0.25 ± 0.15 | −39.7 ± 0.1 |

13 | 1824 ± 60 | 0.59 ± 0.11 | −35.5 ± 1.8 |

14 | 550 ± 3 | 0.35 ± 0.08 | −45.0 ± 1.9 |

15 | 711 ± 40 | 0.24 ± 0.09 | −29.5 ± 0.9 |

16 | 693 ± 13 | 0.27 ± 0.01 | −33.7 ± 0.9 |

17 | 590 ± 8 | 0.26 ± 0.05 | −35.6 ± 1.3 |

18 | 751 ± 16 | 0.17 ± 0.05 | −37 ± 1 |

19 | 637 ± 26 | 0.19 ± 0.09 | −36.8 ± 0.4 |

20 | 2274 ± 188 | 0.31 ± 0.20 | −41.8 ± 1.3 |

Model | p-Value | Lack of Fit p-Value | F-Value | Adj R^{2} | Predicted R^{2} |
---|---|---|---|---|---|

Linear | 0.0002 | 0.6447 | 15.61 | 0.7451 | 0.6239 |

Two-Factor Interaction | 0.2889 | 0.6646 | 1.46 | 0.7715 | 0.5280 |

Quadratic | 0.4568 | 0.6479 | 0.99 | 0.7711 | 0.3553 |

Model | p-Value | Lack of Fit p-Value | F-Value | Adj R^{2} | Predicted R^{2} |
---|---|---|---|---|---|

Linear | 0.0990 | 0.4731 | 2.62 | 0.2445 | −0.1097 |

Two-Factor Interaction | 0.5917 | 0.4468 | 0.66 | 0.1765 | 0.0385 |

Quadratic | 0.0007 | 0.9710 | 26.35 | 0.9129 | 0.8068 |

Factor | F-Value | p-Value |
---|---|---|

A: Lipid | 2.63 | 0.15 |

B: Tween 80 | 71.56 | <0.0001 |

C: Power | 0.02 | 0.87 |

AB | 0.03 | 0.85 |

AC | 20.34 | 0.002 |

BC | 0.31 | 0.59 |

A^{2} | 2.46 | 0.16 |

B^{2} | 64.04 | <0.0001 |

Independent Variables | Solution Value | |

A: Lipid (% w/v) | 5 | |

B: Tween 80 (% w/v) | 2.45 | |

C: Power (%) | 35 | |

Predicted Variables | Goal | Value |

Zeta average (nm) | Minimize | 663.2 |

Zeta potential (mV) | Maximize | −33.8 |

Desirability index | 0.81 |

Independent Variables | Levels | |
---|---|---|

−1 | +1 | |

A: Lipid (% w/v) | 1.5 | 5.0 |

B: Tween 80 (% w/v) | −1.5 | 5.0 |

C: Sonication Power (%) | 35 | 70 |

Run | A: Lipid (% w/v) | B: Tween 80 (% w/v) | C: Power (%) |
---|---|---|---|

1 | 5.00 | 1.5 | 35 |

2 | 5.00 | 1.5 | 70 |

3 | 1.50 | 1.5 | 35 |

4 | 1.50 | 5.00 | 35 |

5 | 3.25 | 3.25 | 52 |

6 | 3.25 | 3.25 | 52 |

7 | 1.50 | 1.50 | 70 |

8 | 3.25 | 3.25 | 52 |

9 | 3.25 | 3.25 | 52 |

10 | 6.20 | 3.25 | 52 |

11 | 1.50 | 5.00 | 70 |

12 | 3.25 | 3.25 | 52 |

13 | 0.30 | 3.25 | 52 |

14 | 3.25 | 0.30 | 52 |

15 | 5.00 | 5.00 | 35 |

16 | 3.25 | 3.25 | 52 |

17 | 3.25 | 3.25 | 82 |

18 | 3.25 | 3.25 | 23 |

19 | 5.00 | 5.00 | 70 |

20 | 3.25 | 6.20 | 52 |

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## Share and Cite

**MDPI and ACS Style**

Talarico, L.; Pepi, S.; Susino, S.; Leone, G.; Bonechi, C.; Consumi, M.; Clemente, I.; Magnani, A.
Design and Optimization of Solid Lipid Nanoparticles Loaded with Triamcinolone Acetonide. *Molecules* **2023**, *28*, 5747.
https://doi.org/10.3390/molecules28155747

**AMA Style**

Talarico L, Pepi S, Susino S, Leone G, Bonechi C, Consumi M, Clemente I, Magnani A.
Design and Optimization of Solid Lipid Nanoparticles Loaded with Triamcinolone Acetonide. *Molecules*. 2023; 28(15):5747.
https://doi.org/10.3390/molecules28155747

**Chicago/Turabian Style**

Talarico, Luigi, Simone Pepi, Surama Susino, Gemma Leone, Claudia Bonechi, Marco Consumi, Ilaria Clemente, and Agnese Magnani.
2023. "Design and Optimization of Solid Lipid Nanoparticles Loaded with Triamcinolone Acetonide" *Molecules* 28, no. 15: 5747.
https://doi.org/10.3390/molecules28155747