README.md

metadata

title: CardioSafe
emoji: ❤️‍🩹
colorFrom: red
colorTo: indigo
sdk: gradio
sdk_version: 5.6.0
python_version: '3.11'
app_file: app.py
pinned: false
license: cc-by-nc-4.0
models:
  - appliedscientific/cardiosafe
short_description: hERG/Nav1.5/Cav1.2/IKs safety prediction from SMILES

CardioSafe — interactive demo

Paste SMILES, get predictions for the four CiPA cardiac ion channels:

Head	Output
hERG pIC50, Nav1.5 pIC50, Cav1.2 pIC50	raw regression (un-z-scored)
hERG blocker (10 µM / 1 µM)	classification output (CO; sigmoid in [0, 1], not a calibrated probability)
Nav1.5 blocker, Cav1.2 blocker, IKs blocker	classification output (CO)

v1.1 is the recommended ensemble. It differs from v1.0 (the preprint snapshot) by 2 force-routed analogs in the cardiac-cliff cluster — see Note S3. Test fold and headline metrics are unchanged; v1.0 is retained for paper reproduction.

This is the paper-snapshot model from Jovanović et al. 2026 (bioRxiv). The continually-updated production ensemble — trained on CRO-validated bioassay data — is served at platform.appliedscientific.ai/cardiosafe.

• Weights: appliedscientific/cardiosafe
• Source: AppliedScientific/CardioSafe-benchmark
• License: weights CC-BY-NC-4.0; code MIT — see LICENSE-WEIGHTS.

Predictions made with this pipeline rely on MolGpKa (Pan et al. 2021, doi:10.1021/acs.jcim.1c00075) for pKa-derived descriptors, and ChemBERTa-77M-MTR (Ahmad et al. 2022) for chemical-language embeddings. Please cite both if you publish predictions made here.