metadata
title: README
emoji: 🚀
colorFrom: green
colorTo: gray
sdk: static
pinned: false
license: mit
Nature Chemical Biology Paper | NeurIPS Paper | GitHub | Leaderboards | Datasets
Artificial intelligence is poised to enable breakthroughs and discoveries in therapeutic science. Therapeutics Data Commons is a global initiative to access and evaluate artificial intelligence capability across therapeutic modalities and stages of discovery. The Commons is a resource with AI-solvable tasks, AI-ready datasets, and curated benchmarks, providing an ecosystem of tools, libraries, leaderboards, and community resources, including data functions, strategies for systematic model evaluation, meaningful data splits, data processors, and molecule generation oracles.
Therapeutics Commons website
from tdc.single_pred import ADME
data = ADME(name = 'HIA_Hou')
# split into train/val/test with scaffold split methods
split = data.get_split(method = 'scaffold')
# get the entire data in the various formats
data.get_data(format = 'df')
Retrieve AI tasks, data functions, model evaluators and benchmarks
Find all Therapeutics Commons models in the Hub
More information: Therapeutics Commons Slack Workspace, Release News