A simple correlation to predict drug solubility in supercritical carbon dioxide

• This work proposes a correlation to predict drugs solubility in CO2.
• The main advantages are its simplicity and minimal input data, namely temperature and density.
• The proposed drug solubility correlation in CO2 has better performance (lower AARE%) respect to seven other empirical equations.

The availability of easy correlation of drug solubility in supercritical fluids without time-consuming calculations and difficult is crucially important for improvement of supercritical technology in pharmaceutical industries. This work proposes a new correlation to predict drugs solubility in CO2. The main advantages are its simplicity and minimal input data, namely temperature and density. The proposed drug solubility correlation in CO2 has better performance (lower AARE%) respect to eight other empirical equations. Due to data sets, the mean AARE for the proposed model was 6.88%.