The dataset containing active substances was extracted from research articles and was available at . The final goal of filtering the dataset was to obtain substances which showed their in vitro toxicity or inhibitory activity toward the human VEGFR-2 strains. The activity types were chosen to be IC 50 or pIC 50 , then being standardized to the pIC 50 values. Molecular SMILES strings were canonicalized and filtered using the RDKit library according to the MOSES data preparation criteria, including uncharged atoms, constraints on certain allowed elements, number of atoms in cycles and medicinal chemistry filters, as well as containing no information about stereochemistry. Then, molecules also went through the JTVAE vocabulary check to ensure their encoding and decoding availability. Lastly, outlier removal was performed on the dataset using zscore to obtain the final training dataset for the QSAR model.