A Dataset of Solubility of Various Anticancer Drugs in Supercritical Carbon Dioxide

The solubility of anticancer drugs (ACDs) in supercritical carbon dioxide (SC-CO2) has a pivotal role in the extraction and purification processes of drugs by this powerful and environmentally-friendly methodology. In this study, the ability of gene expression programming (GEP) and adaptive neuro-fuzzy inference system (ANFIS) techniques comprising experimental models were investigated to estimate the solubility of ACDs in SC-CO2. An extensive database comprising 744 datasets in the wide range of operational conditions (308-348.2 K and 80-400 bar), ACD's molecular weight (MWACDs), and melting point (MPACDs)were established after a comprehensive literature search. The findings of this article are consistent with previous research and show the high accuracy of artificial intelligence techniques in predicting the solubility of ACDs in SC-CO2.