Solubilization data of drug-polymer mixtures from several previous publications were combined together with in-house data to create a formulation database of 3700 experimental data points. These are listed in Table which also includes polymer and monomer names used throughout this manuscript. Solubilization data were collected from these publications either by extracting or calculating the mean values of solubilized drug from given tabulated data or graphically from plots using WebPlotDigitizer 4.6 . The data include a large variation of structures and concentrations of polymers and drugs, as well as of the time point for measuring solubilization. The latter allowed for significantly increasing the size of the dataset by also including long-term stability information. Furthermore, co-formulations of polymers with two drugs were included. Differentiating the chemical structure of monomers and lengths of individual blocks, the dataset included 82 different polymer block compositions, with 34 different B block monomer types, 2 A block monomer types (98 % pMeOx and 2 % pEtOx) and 84 drugs. Figure provides a brief overview of selected properties. As expected, a high correlation between LC and LE values (0.76) is detected, with high values of the former only present for the case of high values of the latter. These properties were calculated based on the amount of solubilized drug (eq. 1 and 2). They describe the relation between the drug feed (m added drug , in g/L), the measured solubilization (m solubilized drug , in g/L) and the polymer feed (m solubilized drug , in g/L), assuming complete solubilization of the polymer. In addition, a negative correlation (-0.34) between the drug feed and LE values can be observed, as higher LE values are more likely for the case of low drug loadings. Drugs of the dataset cover a large proportion of the relevant chemical space in which most drugs with low solubility are located (Figure ).