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Publish CardioSafe-benchmark dataset (compounds, labels, splits, supplementary)
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---
license: cc-by-4.0
language:
- en
task_categories:
- tabular-regression
- tabular-classification
tags:
- chemistry
- drug-discovery
- cardiotoxicity
- hERG
- Nav1.5
- Cav1.2
- IKs
- ion-channels
- QSAR
- ChEMBL
- cipa
- benchmark
pretty_name: CardioSafe ion-channel benchmark
size_categories:
- 100K<n<1M
configs:
- config_name: tan70_v1_0
data_files:
- split: train
path: tan70_v1_0/train.parquet
- split: validation
path: tan70_v1_0/validation.parquet
- split: test
path: tan70_v1_0/test.parquet
- config_name: tan60_v1_0
data_files:
- split: train
path: tan60_v1_0/train.parquet
- split: validation
path: tan60_v1_0/validation.parquet
- split: test
path: tan60_v1_0/test.parquet
- config_name: tan70_v1_1
data_files:
- split: train
path: tan70_v1_1/train.parquet
- split: validation
path: tan70_v1_1/validation.parquet
- split: test
path: tan70_v1_1/test.parquet
- config_name: tan60_v1_1
data_files:
- split: train
path: tan60_v1_1/train.parquet
- split: validation
path: tan60_v1_1/validation.parquet
- split: test
path: tan60_v1_1/test.parquet
---
# CardioSafe ion-channel benchmark
Curated multi-task ion-channel labels + Tanimoto-controlled splits +
supplementary materials for **CardioSafe: multi-task prediction of
cardiac ion channel activity with reverse-leak audited benchmarking**
(Jovanović et al., 2026,
[bioRxiv](https://www.biorxiv.org/content/10.64898/2026.05.06.723181v1)).
The canonical source is the
[CardioSafe-benchmark GitHub repository](https://github.com/AppliedScientific/CardioSafe-benchmark).
This HF Datasets repo mirrors `data/` from that deposit and adds
pre-joined per-fold Parquet shards so you can write:
```python
from datasets import load_dataset
# v1.1 (audit-clean) test fold on the tan70 Tanimoto cutoff:
ds = load_dataset("appliedscientific/cardiosafe-benchmark",
"tan70_v1_1", split="test")
print(ds.column_names)
# ['row_idx', 'smiles', 'inchikey', 'herg_pchembl', 'herg_blocker_10um',
# 'herg_blocker_1um', 'nav15_pchembl', 'nav15_blocker', 'cav12_pchembl',
# 'cav12_blocker', 'iks_blocker']
```
Each row is one curated compound. Label columns are NaN-sparse — only
those compounds with primary-screen evidence for the relevant channel
have non-null values.
## Configs (pre-joined splits)
| Config | Split strategy | Version | Compounds (train / val / test) |
| --- | --- | --- | --- |
| `tan70_v1_0` | Tanimoto ≥ 0.70 cutoff | v1.0 preprint | 241,792 / 46,326 / 46,326 |
| `tan60_v1_0` | Tanimoto ≥ 0.60 cutoff | v1.0 preprint | 306,665 / 13,889 / 13,889 |
| `tan70_v1_1` | Tanimoto ≥ 0.70 cutoff | v1.1 retrain | 241,790 / 46,328 / 46,326 |
| `tan60_v1_1` | Tanimoto ≥ 0.60 cutoff | v1.1 retrain | 306,662 / 13,892 / 13,889 |
**v1.1 differs from v1.0 by 2 force-routed analogs in the cardiac-cliff
cluster** (terfenadine/fexofenadine/HMT). The test fold is identical
across v1.0 and v1.1 — paper Table 2/3 metrics are unchanged. See
[`supplementary/note_s3_v1_1_audit_correction.md`](https://github.com/AppliedScientific/CardioSafe-benchmark/blob/main/data/supplementary/note_s3_v1_1_audit_correction.md).
## Label schema
| Column | Head | Type |
| --- | --- | --- |
| `herg_pchembl` | regression — hERG pIC50 | float |
| `herg_blocker_10um` | hERG blocker @ 10 µM | binary {0, 1} |
| `herg_blocker_1um` | hERG blocker @ 1 µM | binary {0, 1} |
| `nav15_pchembl` | regression — Nav1.5 pIC50 | float |
| `nav15_blocker` | Nav1.5 blocker @ 10 µM | binary {0, 1} |
| `cav12_pchembl` | regression — Cav1.2 pIC50 | float |
| `cav12_blocker` | Cav1.2 blocker @ 10 µM | binary {0, 1} |
| `iks_blocker` | IKs blocker @ 10 µM (exploratory) | binary {0, 1} |
IKs has no regression head (n = 115 labelled compounds; treated as
exploratory).
Per-channel label counts (primary binary head, all folds combined):
| Channel | n labelled | n blockers |
| --- | --- | --- |
| hERG (10 µM) | 331,127 | 11,881 |
| Nav1.5 (10 µM) | 3,160 | 1,240 |
| Cav1.2 (10 µM) | 1,138 | 548 |
| IKs (10 µM) | 115 | 30 |
## Raw canonical files
`raw/` contains the source-of-truth files exactly as published in the
GitHub repo, for power users doing custom merges:
```
raw/
├── compounds.parquet # 334,444 × (row_idx, smiles, inchikey)
├── labels.parquet # 334,444 × 8 sparse labels
├── splits/
│ ├── tan70.parquet # v1.0 — paper preprint splits
│ ├── tan60.parquet
│ ├── tan70_v1_1.parquet # v1.1 — audit-clean retrain splits
│ └── tan60_v1_1.parquet
├── labels_MANIFEST.json # curation provenance (sources, voting policy)
├── splits_CHANGELOG.md # v1.0 → v1.1 diff
└── README.md # full data-deposit notes from GitHub
```
All splits share the same `row_idx` keying — join on it for arbitrary
slicing.
## Comparators
`comparators/` ships the CToxPred2 and CardioGenAI predictions on the
v1.0 `tan70` test fold, the inputs to the reverse-leak audit and the
head-to-head comparison in paper Tables 3 / 3b / S2 / S3 / Figure 4.
## Supplementary materials
`supplementary/` ships verbatim:
- **Notes S1, S2, S3** — Y-randomization mechanism; activity-cliff
curation provenance + bibliography + per-pair composition + filtered
cliff manifests; audit-driven v1.1 correction + retrain metrics + the
cardiac-cliff case study
- **Tables S0, S1, S2, S3, S5, S6, S7, S8, S9** — descriptor spec,
per-head confusion matrices, comparator panels pre/post de-leak, tan60
drug panel, failure-mode SMILES, AD per-bin metrics, L1000 threshold
sweep, curation sensitivity (no S4 — paper supplementary numbering
jumps S3 → S5)
- **Figure S1** — hERG reliability curves across applicability-domain
bins (PDF + PNG + JSON of the underlying decile data)
## Source data
- **Labels** are derived from ChEMBL 36 (source dump SHA-256
`b25820eef0f0481ad7712bdf4bac3b45f354e3cbacb76be1fdbf4205d6b48fb9`,
available from <https://www.ebi.ac.uk/chembl/>) and the **hERG Central
primary screen**, under a pharmacology-aware curation policy that
retains censored values and inhibition-percentage votes. Full
provenance lives in `raw/labels_MANIFEST.json`.
- **Splits** are Tanimoto-controlled across train / val / test on
Morgan-r2-2048 fingerprints, with terfenadine and fexofenadine
force-routed to `val` so the canonical cardiac activity cliff is
available as a held-out case study. v1.1 additionally force-routes the
hydroxymethyl-terfenadine analogs flagged by an exhaustive
O(n_train × n_other) Tanimoto leakage audit
(`scripts/audit_tanimoto_leak.py` in the GitHub repo).
## What is **not** here
- **L1000 raw signatures** used to train the expression encoder —
available from GEO under GSE92742 (Phase I) and GSE70138 (Phase II).
- **Continually-updated production ensemble** — served at
[platform.appliedscientific.ai/cardiosafe](https://platform.appliedscientific.ai/cardiosafe).
This deposit is the frozen paper snapshot.
- **Model weights** — at
[`appliedscientific/cardiosafe`](https://huggingface.co/appliedscientific/cardiosafe)
(5-seed v1.0 + v1.1 ensembles + L1000 encoder, CC-BY-NC-4.0).
- **Interactive demo** — at
[`appliedscientific/cardiosafe` (Space)](https://huggingface.co/spaces/appliedscientific/cardiosafe).
## License
CC-BY-4.0. Use with attribution; commercial use allowed under the
license terms. See the
[full LICENSE-DATA](https://github.com/AppliedScientific/CardioSafe-benchmark/blob/main/LICENSE-DATA)
in the GitHub repo for the exact text.
Note: the *model weights* are CC-BY-NC-4.0 (non-commercial), not the
data. They live at a separate HF repo —
[`appliedscientific/cardiosafe`](https://huggingface.co/appliedscientific/cardiosafe).
## Citation
```bibtex
@article{cardiosafe2026,
title = {CardioSafe: multi-task prediction of cardiac ion channel
activity with reverse-leak audited benchmarking},
author = {Jovanović, Mihailo and Weidener, Lukas and Brkić, Marko and
Ulgac, Emre and Meduri, Aakaash},
year = {2026},
journal = {bioRxiv},
doi = {10.64898/2026.05.06.723181},
url = {https://www.biorxiv.org/content/10.64898/2026.05.06.723181v1}
}
```