Oja, M.; Sild, S.; Piir, G.; Maran, U. Intrinsic aqueous solubility: mechanistically transparent data-driven modeling of drug substances. Pharmaceutics 2022, 14, 2248.
Compound
| ID: | t23 | |
|---|---|---|
| Name: | Gliclazide | |
| Description: | ||
| Labels: | ||
| CAS: | 21187-98-4 | |
| InChi Code: | InChI=1/C15H21N3O3S/c1-11-5-7-14(8-6-11)22(20,21)17-15(19)16-18-9-12-3-2-4-13(12)10-18/h5-8,12-13H,2-4,9-10H2,1H3,(H2,16,17,19) |
Properties
logS0: Intrinsic aqueous solubility from single source [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -4.2 |
Avdeef, A. Multi-lab intrinsic solubility measurement reproducibility in CheqSol and shake-flask methods. ADMET DMPK 2019, 7, 210–219. https://doi.org/http://doi.org/10.5599/admet.698 |
| -3.559 |
M1: Model with Dragon descriptors from training set 1 (Training set) |
logS0a: Intrinsic aqueous solubility from multiple sources [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -4.235 |
experimental value |
| -3.048 |
M2: Model with RDKit descriptors from training set 2 (Training set) |
| -3.874 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Training set) |
| -3.494 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Training set) |