Back to Nature: Development and Optimization of Bioinspired Nanocarriers for Potential Breast Cancer Treatment
Abstract
:1. Introduction
2. Materials and Methods
2.1. Materials
2.2. Methodology
2.2.1. Preparation of CA-Loaded CS NPs
2.2.2. Computational Optimization and Modeling of CA-Loaded CS NPs
2.2.3. Characterization of CA-Loaded CS NPs
PS, PDI and ZP Analysis
2.2.4. Determination of CA Entrapment Efficiency Percentage (EE %)
2.2.5. Molecular Docking Experiments
2.2.6. Transmission Electron Microscope Imaging
2.2.7. Differential Scanning Calorimetry
2.2.8. In Vitro Release Study of CA from Optimized CS NPs
2.2.9. IC50 Determination by Cell Culture Studies
Human Breast Carcinoma Cell Line
2.2.10. Evaluation of In Vitro Antitumor Activity of Optimized CA-Loaded CS NPs
2.2.11. Statistical Analysis
3. Results and Discussion
3.1. Preparation and Optimization of CA-Loaded CS NPs
3.2. Model Analysis
3.3. Model Diagnostics
3.4. The Interpretation of the Models’ Results
3.4.1. The PS Response
3.4.2. The PDI Response
3.4.3. The ZP Response
3.5. Model Validation
3.6. Optimization of Prepared CA-Loaded CS NPs Using Desirability Function (D)
3.7. Imaging Using High-Resolution Transmission Electron Microscopy (HR-TEM)
3.8. DSC
3.9. Results of the in Vitro Release Study of CA from Optimized CS NPs
3.10. Cell Culture Studies
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Formula Code | A: CS Concentration (g%) | B: CaCl2Volume (μL) | C: CA Amount (mg) |
---|---|---|---|
F1 | 1 | 75 | 20 |
F2 | 1 | 50 | 30 |
F3 | 1 | 50 | 10 |
F4 | 1 | 25 | 20 |
F5 | 2 | 50 | 20 |
F6 | 2 | 50 | 20 |
F7 | 2 | 25 | 30 |
F8 | 2 | 75 | 30 |
F9 | 2 | 50 | 20 |
F10 | 2 | 50 | 20 |
F11 | 2 | 50 | 20 |
F12 | 2 | 25 | 10 |
F13 | 2 | 75 | 10 |
F14 | 3 | 75 | 20 |
F15 | 3 | 25 | 20 |
F16 | 3 | 50 | 30 |
F17 | 3 | 50 | 10 |
Formula Code | A: CS Concentration (g%) | B: CaCl2 Volume (µL) | C: CA Amount (mg) | Data * ± SD | |||
---|---|---|---|---|---|---|---|
Y1:PS (nm) | Y2: PDI | Y3: ZP (mV) | Y4:EE% | ||||
F1 | 1 | 75 | 20 | 189.74 ± 0.95 | 0.326 ± 0.031 | −11.01 ± 1.45 | 96.01 ± 1.23 |
F2 | 1 | 50 | 30 | 136.81 ± 0.33 | 0.323 ± 0.041 | −19.93 ± 0.92 | 95.42 ± 2.98 |
F3 | 1 | 50 | 10 | 122.11 ± 3.52 | 0.326 ± 0.092 | −10.45 ± 0.37 | 96.32 ± 4.52 |
F4 | 1 | 25 | 20 | 114.52 ± 5.13 | 0.333 ± 0.128 | −15.22 ± 0.75 | 96.81 ± 3.98 |
F5 | 2 | 50 | 20 | 110.94 ± 4.42 | 0.345 ± 0.156 | −21.23 ± 0.65 | 95.04 ± 5.09 |
F6 | 2 | 50 | 20 | 108.93 ± 2.25 | 0.309 ± 0.015 | −22.54 ± 0.26 | 96.52 ± 3.29 |
F7 | 2 | 25 | 30 | 144.34 ± 2.81 | 0.331 ± 0.066 | −24.11 ± 2.46 | 95.12 ± 4.02 |
F8 | 2 | 75 | 30 | 236.83 ± 1.34 | 0.302 ± 0.096 | −18.74 ± 2.52 | 94.74 ± 2.78 |
F9 | 2 | 50 | 20 | 109.22 ± 1.79 | 0.301 ± 0.133 | −19.94 ± 2.32 | 97.26 ± 1.98 |
F10 | 2 | 50 | 20 | 111.34 ± 2.61 | 0.308 ± 0.016 | −23.50 ±1.54 | 95.63 ± 0.96 |
F11 | 2 | 50 | 20 | 109.73 ± 1.45 | 0.339 ± 0.018 | −22.92 ± 1.99 | 96.83 ± 3.04 |
F12 | 2 | 25 | 10 | 125.44 ± 0.96 | 0.334 ± 0.012 | −23.43 ± 0.23 | 95.58 ± 3.27 |
F13 | 2 | 75 | 10 | 156.53 ± 0.28 | 0.327 ± 0.004 | −14.42 ± 0.43 | 94.40 ± 2.98 |
F14 | 3 | 75 | 20 | 268.63 ± 3.88 | 0.381 ± 0.012 | −17.42 ± 0.23 | 95.34 ± 1.88 |
F15 | 3 | 25 | 20 | 223.34 ± 5.76 | 0.493 ± 0.004 | −23.53 ± 1.24 | 93.72 ± 4.56 |
F16 | 3 | 50 | 30 | 257.81 ± 3.14 | 0.455 ± 0.076 | −27.44 ± 0.17 | 94.23 ± 5.09 |
F17 | 3 | 50 | 10 | 180.83 ± 2.89 | 0.499 ± 0.018 | −25.12 ±1.99 | 93.52 ± 4.98 |
Response | PS | PDI | ZP |
---|---|---|---|
Suggested Model | Quadratic | Reduced Quadratic | Reduced Quadratic |
Equation | |||
P-value | <0.0001 | <0.0001 | <0.0001 |
R2 | 0.9996 | 0.8760 | 0.8835 |
Adjusted R2 | 0.9991 | 0.8474 | 0.8306 |
Predicted R2 | 0.9947 | 0.7454 | 0.6775 |
Adequate precision | 119.867 | 14.311 | 14.366 |
C.V.% | 1.08 | 7.06 | 10.12 |
PRESS | 266.66 | 0.017 | 125.06 |
Terms | Responses | |||||
---|---|---|---|---|---|---|
PS | PDI | ZP | ||||
F-Value | p-Value | F-Value | p-Value | F-Value | p-Value | |
Model | 1901.98 * | <0.0001 | 30.62 * | <0.0001 | 16.68 * | <0.0001 |
A | 5713.38 * | <0.0001 | 53.82 * | <0.0001 | 41.90 * | <0.0001 |
B | 2522.03 * | <0.0001 | 4.78 * | 0.0476 | 18.27 * | 0.0013 |
C | 1542.51 * | <0.0001 | 1.39 NS | 0.2762 NS | 8.59 * | 0.0137 |
AB | 75.68 * | <0.0001 | 5.47 NS | 0.0520 NS | 0.33 NS | 0.5815 NS |
AC | 328.56 * | <0.0001 | 0.83 NS | 0.3917 NS | 3.93 NS | 0.0880 NS |
BC | 319.14 * | <0.0001 | 0.24 NS | 0.6392 NS | 0.98 NS | 0.3549 NS |
A2 | 3398.80 * | <0.0001 | 33.25 * | <0.0001 | 5.47 * | 0.0392 |
B2 | 2304.06 * | <0.0001 | 0.43 NS | 0.5316 NS | 8.39 * | 0.0145 |
C2 | 344.75 * | <0.0001 | 0.89 NS | 0.3780 NS | 1.44 NS | 0.2692 NS |
Lack of fit | 4.87 NS | 0.0800 | 1.81 NS | 0.2979 | 2.52 NS | 0.1950 |
Different Parameters | Formulation 1 | Formulation 2 | Formulation 3 | |
---|---|---|---|---|
A: CS concentration (g%) | 1.25 | 2.25 | 2.5 | |
B: CaCl2 volume (μL) | 35 | 60 | 70 | |
C: CA amount (mg) | 15 | 25 | 22.5 | |
PS (nm)± SD | Actual | 98.70 ± 3.85 | 169.10 ± 2.01 | 209.70 ± 3.35 |
Predicted | 98.22 | 163.26 | 204.27 | |
% Bias | 0.49 | 3.46 | 1.16 | |
Mean Percentage Bias = 1.7% | ||||
PDI ± SD | Actual | 0.315 ± 0.015 | 0.341 ± 0.028 | 0.349 ± 0.007 |
Predicted | 0.324 | 0.334 | 0.356 | |
%Bias | 2.86 | 2.05 | 2.01 | |
Mean Percentage Bias = 2.3% | ||||
ZP (mV)± SD | Actual | −17.10 ± 1.15 | −23.20 ± 1.70 | −22.00 ± 1.31 |
Predicted | −17.43 | −22.83 | −20.44 | |
%Bias | 1.93 | 1.60 | 7.10 | |
Mean Percentage Bias = 3.5% |
Formulations | IC50 (µg/mL) * ± SD |
---|---|
CA solution | 173.30 ± 3.00 |
Unloaded CA-CS NPs | 537.50 ± 6.10 |
Optimized CA-CS NPs (O1) | 78.45 ± 1.70 |
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Safwat, S.; Hathout, R.M.; Ishak, R.A.H.; Mortada, N.D. Back to Nature: Development and Optimization of Bioinspired Nanocarriers for Potential Breast Cancer Treatment. Sci. Pharm. 2024, 92, 50. https://doi.org/10.3390/scipharm92030050
Safwat S, Hathout RM, Ishak RAH, Mortada ND. Back to Nature: Development and Optimization of Bioinspired Nanocarriers for Potential Breast Cancer Treatment. Scientia Pharmaceutica. 2024; 92(3):50. https://doi.org/10.3390/scipharm92030050
Chicago/Turabian StyleSafwat, Sally, Rania M. Hathout, Rania A. H. Ishak, and Nahed D. Mortada. 2024. "Back to Nature: Development and Optimization of Bioinspired Nanocarriers for Potential Breast Cancer Treatment" Scientia Pharmaceutica 92, no. 3: 50. https://doi.org/10.3390/scipharm92030050
APA StyleSafwat, S., Hathout, R. M., Ishak, R. A. H., & Mortada, N. D. (2024). Back to Nature: Development and Optimization of Bioinspired Nanocarriers for Potential Breast Cancer Treatment. Scientia Pharmaceutica, 92(3), 50. https://doi.org/10.3390/scipharm92030050