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: | t47 | |
|---|---|---|
| Name: | Chlorpromazine | |
| Description: | ||
| Labels: | ||
| CAS: | 50-53-3 | |
| InChi Code: | InChI=1S/C17H19ClN2S/c1-19(2)10-5-11-20-14-6-3-4-7-16(14)21-17-9-8-13(18)12-15(17)20/h3-4,6-9,12H,5,10-11H2,1-2H3 |
Properties
logS0: Intrinsic aqueous solubility from single source [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -5.55 |
Avdeef, A. Multi-lab intrinsic solubility measurement reproducibility in CheqSol and shake-flask methods. ADMET DMPK 2019, 7, 210–219. http://dx.doi.org/http://doi.org/10.5599/admet.698 |
| -4.935 |
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 |
|---|---|
| -5.335 |
experimental value |
| -4.623 |
M2: Model with RDKit descriptors from training set 2 (Training set) |
| -4.834 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Training set) |
| -4.797 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Training set) |