Development of A Nanostructured Lipid Carrier-Based Drug Delivery Strategy for Apigenin: Experimental Design Based on CCD-RSM and Evaluation against NSCLC In Vitro
Abstract
:1. Introduction
2. Results and Discussion
2.1. Determination of AP Content
2.1.1. Choice of Maximum Absorption Wavelength
2.1.2. Drawing of Working Curve
2.2. Single-Factor Experiment
2.3. Optimization of AP-NLC
2.3.1. ANOVA of The Model
2.3.2. 3D Response Surface and Contour
2.3.3. Determination and Validation of The Optimal Prescription
2.4. Transmission Electron Microscopy
2.5. DSC Analysis
2.6. X-ray Diffractometry
2.7. FT-IR Analysis
2.8. Drug Release Study In Vitro
2.9. Stability of Preparations
2.10. Freeze Drying Protection
2.11. Safety Evaluation of Preparations
2.12. Cell Proliferation Assay
2.13. Cell Morphology
2.14. Wound Healing Assay
2.15. Migration and Invasion Assay
2.16. Plate Cloning formation Assay
3. Materials and Methods
3.1. Materials
3.2. Preparation of AP-NLC
3.3. Determination of AP content
3.3.1. Choice of Maximum Absorption Wavelength
3.3.2. Drawing of Working Curve
3.3.3. Encapsulation Efficiency and Drug Loading of Preparations
3.4. Single-Factor Experiment
3.4.1. Ultrasonic Power
3.4.2. Emulsifier Dosage
3.4.3. Emulsification Time
3.4.4. Lipid–Drug Ratio
3.4.5. Solid–Liquid Lipid Ratio
3.5. Optimization of AP-NLC Based on CCD-RSM
3.6. Characterization of NLC
3.6.1. Transmission Electron Microscopy
3.6.2. DSC Analysis
3.6.3. X-ray Diffraction Study
3.6.4. FT-IR Analysis
3.7. Drug Release Study In Vitro
3.8. Stability of Preparations
3.9. Freeze Drying Protection
3.10. Cell Culture
3.11. Safety Evaluation of Preparations In Vitro
3.11.1. Cell Viability of Blank NLC
3.11.2. Hemolysis Assay
3.12. Cell Viability Assay
3.13. Cell Morphology
3.14. Wound Healing Assay
3.15. Transwell Assays
3.16. Plate Cloning Formation Assay
3.17. Statistical Analysis
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Sample Availability
References
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No. | Coded Value | Actual Value | Value of Response | |||||
---|---|---|---|---|---|---|---|---|
A | B | C | A | B | C | Y1 | Y2 | |
1 | 1 | 1 | −1 | 2 | 30 | 3 | 64.11 ± 0.33 | 2.06 ± 0.03 |
2 | 0 | 0 | 0 | 1.5 | 25 | 5.5 | 85.59 ± 1.43 | 3.27 ± 0.03 |
3 | 0 | 0 | 1.682 | 1.5 | 25 | 9.70 | 90.10 ± 0.97 | 3.48 ± 0.04 |
4 | 1 | −1 | −1 | 2 | 20 | 3 | 67.18 ± 2.40 | 3.28 ± 0.10 |
5 | −1 | 1 | 1 | 1 | 30 | 8 | 89.27 ± 1.07 | 2.87 ± 0.14 |
6 | −1.682 | 0 | 0 | 0.66 | 25 | 5.5 | 74.74 ± 1.74 | 2.89 ± 0.05 |
7 | −1 | −1 | 1 | 1 | 20 | 8 | 81.82 ± 1.74 | 3.94 ± 0.07 |
8 | 0 | −1.682 | 0 | 1.5 | 16.59 | 5.5 | 75.75 ± 1.77 | 4.40 ± 0.13 |
9 | 0 | 0 | 0 | 1.5 | 25 | 5.5 | 81.57 ± 0.75 | 3.28 ± 0.08 |
10 | 0 | 0 | 0 | 1.5 | 25 | 5.5 | 83.79 ± 0.64 | 3.16 ± 0.07 |
11 | 0 | 0 | 0 | 1.5 | 25 | 5.5 | 83.14 ± 1.80 | 3.21 ± 0.06 |
12 | 0 | 0 | 0 | 1.5 | 25 | 5.5 | 82.55 ± 1.63 | 3.19 ± 0.04 |
13 | 1.682 | 0 | 0 | 2.34 | 25 | 5.5 | 67.43 ± 2.27 | 2.63 ± 0.16 |
14 | 0 | 1.682 | 0 | 1.5 | 33.41 | 5.5 | 67.41 ± 1.98 | 2.03 ± 0.12 |
15 | −1 | 1 | −1 | 1 | 30 | 3 | 74.95 ± 3.17 | 2.43 ± 0.07 |
16 | −1 | −1 | −1 | 1 | 20 | 3 | 63.83 ± 0.96 | 2.87 ± 0.41 |
17 | 1 | −1 | 1 | 2 | 20 | 8 | 83.68 ± 1.36 | 3.97 ± 0.10 |
18 | 0 | 0 | −1.682 | 1.5 | 25 | 1.30 | 66.69 ± 0.54 | 2.60 ± 0.04 |
19 | 0 | 0 | 0 | 1.5 | 25 | 5.5 | 83.13 ± 2.16 | 3.25 ± 0.03 |
20 | 1 | 1 | 1 | 2 | 30 | 8 | 69.63 ± 2.25 | 1.92 ± 0.66 |
Source | Sum of Squares | df | Mean Square | F-Value | p-Value | |
---|---|---|---|---|---|---|
Model | 1380.10 | 9 | 153.34 | 32.50 | <0.0001 | significant |
A | 103.32 | 1 | 103.32 | 21.90 | 0.0009 | |
B | 11.58 | 1 | 11.58 | 2.45 | 0.1483 | |
C | 642.89 | 1 | 642.89 | 136.26 | <0.0001 | |
AB | 159.22 | 1 | 159.22 | 33.75 | 0.0002 | |
AC | 13.24 | 1 | 13.24 | 2.81 | 0.1249 | |
BC | 26.83 | 1 | 26.83 | 5.69 | 0.0383 | |
A2 | 237.86 | 1 | 237.86 | 50.41 | <0.0001 | |
B2 | 217.81 | 1 | 217.81 | 46.16 | <0.0001 | |
C2 | 31.49 | 1 | 31.49 | 6.67 | 0.0273 | |
Residual | 47.18 | 10 | 4.72 | |||
Lack of Fit | 38.09 | 5 | 7.62 | 4.19 | 0.0710 | not significant |
Pure Error | 9.09 | 5 | 1.82 | |||
Cor Total | 1427.28 | 19 | ||||
R2 | 0.9669 | |||||
Adjusted R2 | 0.9372 | |||||
Predicted R2 | 0.7809 |
Source | Sum of Squares | df | Mean Square | F-Value | p-Value | |
---|---|---|---|---|---|---|
Model | 8.01 | 10 | 0.8007 | 192.45 | <0.0001 | significant |
A | 0.1271 | 1 | 0.1271 | 30.54 | 0.0004 | |
B | 2.81 | 1 | 2.81 | 674.97 | <0.0001 | |
C | 0.9176 | 1 | 0.9176 | 220.53 | <0.0001 | |
AB | 0.3872 | 1 | 0.3872 | 93.06 | <0.0001 | |
AC | 0.1152 | 1 | 0.1152 | 27.69 | 0.0005 | |
BC | 0.2664 | 1 | 0.2664 | 64.04 | <0.0001 | |
A2 | 0.4701 | 1 | 0.4701 | 112.99 | <0.0001 | |
B2 | 0.0056 | 1 | 0.0056 | 1.35 | 0.2750 | |
C2 | 0.0960 | 1 | 0.0960 | 23.08 | 0.0010 | |
A2B | 0.0380 | 1 | 0.0380 | 9.14 | 0.0144 | |
Residual | 0.0374 | 9 | 0.0042 | |||
Lack of Fit | 0.0261 | 4 | 0.0065 | 2.88 | 0.1382 | not significant |
Pure Error | 0.0113 | 5 | 0.0023 | |||
Cor Total | 8.04 | 19 | ||||
R2 | 0.9953 | |||||
Adjusted R2 | 0.9902 | |||||
Predicted R2 | 0.9254 |
Indicators | Measured | Predicted | Predicted Error (%) |
---|---|---|---|
EE% | 88.22 ± 1.61 | 90.13 | 2.12 |
DL% | 4.22 ± 0.13 | 4.40 | 4.09 |
Release Kinetic Models | Equation | R2 |
---|---|---|
Zero Order | Mt = 1.27 × t + 21.75 | R2 = 0.87972 |
First Order | Mt = 41.95 × (1-e−0.37t) | R2 = 0.74094 |
Higuchi | Mt = 7.53 × t1/2 + 12.88 | R2 = 0.98057 |
Ritger–Peppas | Mt = 19.59 × t0.28 | R2 = 0.99101 |
Factor | Name | Level | ||||
---|---|---|---|---|---|---|
−1.682 | −1 | 0 | +1 | +1.682 | ||
A | emulsifier dosage | 0.6591 | 1 | 1.5 | 2 | 2.34 |
B | Lipid–drug ratio | 16.59 | 20 | 25 | 30 | 33.41 |
C | Solid–liquid lipid ratio | 1.30 | 3 | 5.5 | 8 | 9.70 |
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Wang, X.; Liu, J.; Ma, Y.; Cui, X.; Chen, C.; Zhu, G.; Sun, Y.; Tong, L. Development of A Nanostructured Lipid Carrier-Based Drug Delivery Strategy for Apigenin: Experimental Design Based on CCD-RSM and Evaluation against NSCLC In Vitro. Molecules 2023, 28, 6668. https://doi.org/10.3390/molecules28186668
Wang X, Liu J, Ma Y, Cui X, Chen C, Zhu G, Sun Y, Tong L. Development of A Nanostructured Lipid Carrier-Based Drug Delivery Strategy for Apigenin: Experimental Design Based on CCD-RSM and Evaluation against NSCLC In Vitro. Molecules. 2023; 28(18):6668. https://doi.org/10.3390/molecules28186668
Chicago/Turabian StyleWang, Xiaoxue, Jinli Liu, Yufei Ma, Xinyu Cui, Cong Chen, Guowei Zhu, Yue Sun, and Lei Tong. 2023. "Development of A Nanostructured Lipid Carrier-Based Drug Delivery Strategy for Apigenin: Experimental Design Based on CCD-RSM and Evaluation against NSCLC In Vitro" Molecules 28, no. 18: 6668. https://doi.org/10.3390/molecules28186668
APA StyleWang, X., Liu, J., Ma, Y., Cui, X., Chen, C., Zhu, G., Sun, Y., & Tong, L. (2023). Development of A Nanostructured Lipid Carrier-Based Drug Delivery Strategy for Apigenin: Experimental Design Based on CCD-RSM and Evaluation against NSCLC In Vitro. Molecules, 28(18), 6668. https://doi.org/10.3390/molecules28186668