The Toxicology in the 21st Century (Tox21) dataset measures the toxicity of 8,000 compounds across 12 different toxicity targets including nuclear receptors and stress response pathways. Structures in this dataset are provided as SMILES structures with RDKit 30 embedding their geometries prior to optimization. GFN2-xTB further optimized these structures prior to DFT and QTAIM. We constructed a random train-test split of 90/10 and the validation set was constructed from the training set with a split of 80/20 for model selection and hyperparameter tuning. Algorithms were trained in a multi-task fashion to predict all 12 properties (toxicity toward 12 targets). QTAIM properties for this dataset were computed at TPSS 33 /def2-SVP with D3BJ dispersion following geometry optimization. The dataset consists of various missing values across the 12 labels so we imputed mode values for training but at testing no imputation was performed.