In order to assist other researchers experiencing solubility issues for drugs or potential novel drug candidates, models are integrated into a web application called POxload (). In the current version, users can predict LC and LE values for single molecules or co-formulations by providing corresponding SMILES strings (Figure ). Different polymers can be selected for which drug loading is predicted, with the most common variants (A-nPrOx-A, A-nPrOzi-A, A-nBuOx-A and A-nBuOzi-A) listed as default. Predictions can be made either by the final models (Table ) or the best subset/model type combination (RDK7-RF) that showed good Acc values as well (Table ). From the thresholds passed, the maximum of solubilized drug is computed (e.g. LE = 39% when passing LE20 but not LE40), given a polymer feed of 10 g/L and drug feeds from 2 to 10 g/L. Predictions are listed for both parameters individually and in a combined way, listing the average amount of solubilized drug predicted by both LC and LE models (Figure ). For calculation of these values, the application determines the last threshold passed before two consecutive thresholds result in negative predictions. However, in general, we recommend users to evaluate the predictions of all LC and LE models for deciding whether to investigate the selected drug experimentally; as discussed above, LC models are more likely to result in positive predictions at higher drug feeds, whereas high LE values are more common at lower DF values. For predictions outside of the AD, values for a negative prediction are assumed for calculation of solubilized drug. In the end of each formulation report, predictions for all individual models are also shown as barplot and listed in tabulated format. The tool also includes a batch mode and the option to evaluate longterm storage for single polymers. The software is currently hosted and downloadable as a command-line tool at our github page ().