| --- |
| license: cc-by-4.0 |
| task_categories: |
| - text-generation |
| - text-classification |
| language: |
| - en |
| tags: |
| - chemistry |
| - toxicity |
| - drug-discovery |
| - llm |
| - reasoning |
| - aop |
| - benchmark |
| pretty_name: ToxReason |
| size_categories: |
| - 10K<n<100K |
|
|
| configs: |
| - config_name: default |
| data_files: |
| - split: mie_matched |
| path: MIE_matched.jsonl |
| - split: mie_ao_matched |
| path: MIE_AO_matched.jsonl |
| - split: evaluation |
| path: evaluation.jsonl |
| --- |
| # ToxReason |
|
|
| 🚀 Accepted at ACL 2026 Findings |
|
|
| ToxReason is a benchmark dataset for mechanistic chemical toxicity reasoning based on Adverse Outcome Pathways (AOPs). |
|
|
| The dataset is designed to evaluate whether large language models can generate biologically interpretable toxicity reasoning trajectories that connect molecular structures, Molecular Initiating Events (MIEs), pathway perturbations, and organ-level adverse outcomes. |
|
|
| ## Dataset Overview |
|
|
| ToxReason consists of three splits: |
|
|
| | Split | Description | |
| |---|---| |
| | `MIE_matched` | Large-scale silver training data constructed by matching chemicals with experimentally supported MIE bioactivity data from ChEMBL. | |
| | `MIE_AO_matched` | Higher-quality training data linking MIEs and curated adverse outcomes through biologically related AOP trajectories. | |
| | `evaluation` | Evaluation data for assessing mechanistic toxicity reasoning performance. | |
|
|
| The benchmark focuses on three major organ toxicity categories: |
|
|
| - Liver Toxicity |
| - Cardiotoxicity |
| - Kidney Toxicity |
|
|
| ## Task Description |
|
|
| Given a molecular structure represented as a SMILES string, models are expected to generate mechanistic toxicity reasoning trajectories. |
|
|
| The expected reasoning may include: |
|
|
| - Molecular Initiating Events (MIEs) |
| - Biological pathway perturbations |
| - Adverse Outcome Pathway information |
| - Organ-level adverse outcomes |
| - Stepwise mechanistic toxicity explanations |
|
|
| ## Intended Use |
|
|
| ToxReason is intended for: |
|
|
| - Toxicity reasoning evaluation |
| - Mechanistic toxicity generation |
| - LLM reasoning benchmark research |
| - AI-assisted drug safety assessment |
| - Explainable AI for toxicology |
|
|
| ## Limitations |
|
|
| - The dataset includes reasoning trajectories derived from curated biological knowledge and rule-based construction. |
| - Biological mechanisms may not fully represent all real-world causal toxicity pathways. |
| - The current benchmark focuses on liver, heart, and kidney toxicities. |
| - This dataset should be used for research purposes and should not be considered a substitute for expert toxicological evaluation. |
|
|
| ## License |
|
|
| This dataset is released under the CC BY 4.0 license. |
|
|
| ## Citation |
|
|
| If you use this dataset, please cite: |
|
|
| ```bibtex |
| @article{park2026toxreason, |
| title={ToxReason: A Benchmark for Mechanistic Chemical Toxicity Reasoning via Adverse Outcome Pathway}, |
| author={Park, Jueon and Jang, Wonjune and Kim, Chanhwi and Park, Yein and Kang, Jaewoo}, |
| journal={arXiv preprint arXiv:2604.06264}, |
| year={2026} |
| } |
| ``` |
