What kind of data splits does PyTDC offer?

PyTDC offers specialized splitting strategies including scaffold splits for chemical diversity, cold-drug/cold-target splits for interaction tasks, and temporal splits for time-sensitive data.

How do I evaluate my models using this skill?

The skill provides a standardized Evaluator class with metrics like ROC-AUC, PR-AUC, RMSE, and MAE tailored to specific therapeutic discovery tasks.

What is the PyTDC Claude Code skill used for?

It is used to access curated, AI-ready datasets and benchmarks for drug discovery tasks such as molecular property prediction, interaction forecasting, and molecule generation.

Can I use PyTDC for clinical trial outcome prediction?

Yes, PyTDC includes datasets for multi-instance prediction tasks like TrialOutcome and drug resistance prediction.

Does this skill support molecular property optimization?

Yes, it provides access to over 17 molecular oracles that can be used to score and optimize molecules for specific biological targets or chemical properties.

Therapeutics Data Commons (PyTDC)

Name: Therapeutics Data Commons (PyTDC)
Author: ovachiever

byovachiever

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データサイエンスとML

Provides AI-ready drug discovery datasets, standardized benchmarks, and molecular oracles for therapeutic machine learning.

PyTDC (Therapeutics Data Commons) is a specialized skill for drug discovery researchers and ML engineers, offering streamlined access to curated biomedical datasets across the entire therapeutics pipeline. It facilitates the development and benchmarking of models for molecular property prediction, drug-target interactions, and molecule generation by providing standardized evaluation metrics, diverse data split strategies like scaffold and cold-start, and automated molecule processing utilities. This skill is essential for anyone working on ADME/Tox prediction, retrosynthesis, or optimizing molecular properties using validated oracles within the Claude Code environment.

主な機能

01Integrated molecular oracles for goal-directed generation and property optimization

0215 GitHub stars

03Standardized benchmark groups with rigorous 5-seed evaluation protocols

04Access to 100+ AI-ready drug discovery datasets including ADME, Toxicity, and HTS

05Advanced data splitting techniques including scaffold, cold-drug, and temporal splits

06Chemical utilities for format conversion between SMILES, SELFIES, PyG, and DGL

ユースケース

01Predicting binding affinities for drug-target interactions (DTI) and drug-drug interactions (DDI)

02Benchmarking machine learning models on standardized pharmaceutical tasks like ADME/Tox prediction

03Generating and optimizing novel molecules with specific biological or chemical properties

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add ovachiever/droid-tings pytdc

For use in Claude.ai and ChatGPT

Download Skill