Anti-Cancer Drug Solubility Development within a Green Solvent: Design of Novel and Robust Mathematical Models Based on Artificial Intelligence
Abstract
:1. Introduction
2. Dataset
3. Methodology
3.1. Base Models
- Inputs: training samples : input features, : real-valued output, testing point x to predict
- Algorithm:
- Calculate distance to every training example
- Select closet examples and their outputs
- Output:
3.2. AdaBoost
4. Results
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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No. | X1 = P (bar) | X2 = T (K) | Y (Solubility/Mole Fraction) |
---|---|---|---|
1 | 120 | 308 | 4 × 10−6 |
2 | 160 | 308 | 4.94 × 10−6 |
3 | 200 | 308 | 5.49 × 10−6 |
4 | 240 | 308 | 5.96 × 10−6 |
5 | 280 | 308 | 3.99 × 10−6 |
6 | 320 | 308 | 3.88 × 10−6 |
7 | 360 | 308 | 8.38 × 10−6 |
8 | 400 | 308 | 1.24 × 10−5 |
9 | 120 | 318 | 2.15 × 10−6 |
10 | 160 | 318 | 5.79 × 10−6 |
11 | 200 | 318 | 8.95 × 10−6 |
12 | 240 | 318 | 7.27 × 10−6 |
13 | 280 | 318 | 3.40 × 10−6 |
14 | 320 | 318 | 7.03 × 10−5 |
15 | 360 | 318 | 4.01 × 10−6 |
16 | 400 | 318 | 1.39 × 10−5 |
17 | 120 | 328 | 1.79 × 10−6 |
18 | 160 | 328 | 5.13 × 10−6 |
19 | 200 | 328 | 1.05 × 10−6 |
20 | 240 | 328 | 5.48 × 10−5 |
21 | 280 | 328 | 2.31 × 10−5 |
22 | 320 | 328 | 2.04 × 10−5 |
23 | 360 | 328 | 2.50 × 10−5 |
24 | 400 | 328 | 4.41 × 10−5 |
25 | 120 | 338 | 1.52 × 10−5 |
26 | 160 | 338 | 3.84 × 10−6 |
27 | 200 | 338 | 1.05 × 10−5 |
28 | 240 | 338 | 2.08 × 10−5 |
29 | 280 | 338 | 3.13 × 10−5 |
30 | 320 | 338 | 1.95 × 10−5 |
31 | 360 | 338 | 5.47 × 10−5 |
32 | 400 | 338 | 6.0 × 10−5 |
Models | MAE | R2 |
---|---|---|
ADA-KNN | 1.98 × 10−6 | 0.996 |
ADA-GPR | 1.33 × 10−6 | 0.967 |
ADA-TSR | 2.33 × 10−6 | 0.883 |
X1 = P (bar) | X2 = T (K) | Y (Solubility) |
---|---|---|
329 | 318.0 | 7.03 × 10−5 |
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Huwaimel, B.; Alobaida, A. Anti-Cancer Drug Solubility Development within a Green Solvent: Design of Novel and Robust Mathematical Models Based on Artificial Intelligence. Molecules 2022, 27, 5140. https://doi.org/10.3390/molecules27165140
Huwaimel B, Alobaida A. Anti-Cancer Drug Solubility Development within a Green Solvent: Design of Novel and Robust Mathematical Models Based on Artificial Intelligence. Molecules. 2022; 27(16):5140. https://doi.org/10.3390/molecules27165140
Chicago/Turabian StyleHuwaimel, Bader, and Ahmed Alobaida. 2022. "Anti-Cancer Drug Solubility Development within a Green Solvent: Design of Novel and Robust Mathematical Models Based on Artificial Intelligence" Molecules 27, no. 16: 5140. https://doi.org/10.3390/molecules27165140