alterlab-pytdc

# PyTDC (Therapeutics Data Commons) ## Overview PyTDC is an open-science platform providing AI-ready datasets and benchmarks for drug discovery and development. Access curated datasets spanning the entire therapeutics pipeline with standardized evaluation metrics and meaningful data splits, organized into three categories: single-instance prediction (molecular/protein properties), multi-instance prediction (drug-target interactions, DDI), and generation (molecule generation, retrosynthesis). ## When to Use This Skill This skill should be used when: - Working with drug discovery or therapeutic ML datasets - Benchmarking machine learning models on standardized pharmaceutical tasks - Predicting molecular properties (ADME, toxicity, bioactivity) - Predicting drug-target or drug-drug interactions - Generating novel molecules with desired properties - Accessing curated datasets with proper train/test splits (scaffold, cold-split) - Using molecular oracles for property optimization ### Does NOT Trigger | Scenario | Use Instead | |----------|-------------| | Featurizing the loaded molecules and training/evaluating models | `alterlab-deepchem` (models) or `alterlab-molfeat` (features) | | Pulling raw bioactivity records (IC50/Ki) for a target beyond TDC's curated sets | `alterlab-chembl` | | Measured binding affinities for a protein target | `alterlab-bindingdb` | | Querying the PrimeKG knowledge graph itself (drug–disease paths) | `alterlab-primekg` | ## Installation & Setup ...