How does PyTDC handle data splitting for ML training?

PyTDC supports advanced splitting strategies such as scaffold splits for chemical diversity and cold-start splits for unseen drugs or targets in interaction tasks.

Is PyTDC suitable for benchmarking new models?

Absolutely. It features Benchmark Groups with curated datasets and specific evaluation protocols (like the 5-seed requirement) for systematic model comparison.

What kind of datasets does the PyTDC skill provide?

It provides AI-ready datasets for ADME, toxicity, drug-target interactions (DTI), drug-drug interactions (DDI), molecular generation, and retrosynthesis.

Can I use this skill to evaluate molecular properties?

Yes, it includes molecular oracles that can score SMILES strings for properties like bioactivity, synthetic accessibility, and drug-likeness.

PyTDC (Therapeutics Data Commons)

Name: PyTDC (Therapeutics Data Commons)
Author: Sologa

bySologa

0•

Data Science & ML

Accesses AI-ready drug discovery datasets and benchmarks for therapeutic machine learning and pharmacological prediction.

PyTDC is a specialized skill for the Therapeutics Data Commons platform, designed to provide researchers and developers with high-quality, AI-ready datasets for the entire drug discovery pipeline. It offers curated data for single-instance prediction (ADME, toxicity), multi-instance interactions (DTI, DDI), and molecular generation tasks. By integrating standardized evaluation metrics, sophisticated data splits like scaffold-based partitioning, and molecular oracles, this skill enables efficient benchmarking and development of machine learning models within the pharmaceutical and therapeutic domains.

Key Features

01Integrated chemical utilities for format conversion and molecule filtering

02Molecular oracles for property scoring and goal-directed generation

03Advanced data splitting strategies including scaffold and cold-start splits

04Curated access to ADMET, toxicity, and drug-target interaction datasets

050 GitHub stars

06Standardized evaluation metrics for classification and regression tasks

Use Cases

01Optimizing novel molecule generation using therapeutic oracles

02Benchmarking ML models on standardized pharmaceutical datasets

03Predicting molecular pharmacokinetic and toxicity properties

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add sologa/codex-pipeline pytdc

For use in Claude.ai and ChatGPT

Download Skill