{"library":"pyTDC","title":"Therapeutics Data Commons (TDC)","description":"Therapeutics Data Commons (TDC) is a unified, open-source framework for machine learning in therapeutics. It provides standardized datasets, benchmarks, and tools for tasks like drug-target interaction, ADMET prediction, and clinical trial outcome prediction. Current version 1.1.15, with frequent updates.","language":"python","status":"active","last_verified":"Fri May 01","install":{"commands":["pip install PyTDC"],"cli":null},"imports":["from tdc import TDC","from tdc.single_pred import SinglePredDataset","from tdc.utils import DataLoader"],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"from tdc.single_pred import ADME\ndata = ADME(name = 'Caco2_Wang')\nsplit = data.get_split(method = 'random', seed = 42)\ntrain, valid, test = split['train'], split['valid'], split['test']\nprint(train.head())","lang":"python","description":"Load Caco2 permeability dataset and split into train/valid/test.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":null}