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chem-hazard-toxicity

learningmatter-mit/AtomisticSkills/.agents/skills/chem-hazard-toxicity/SKILL.md

Extract explicit safety warnings, GHS classifications, LD50 toxicity profiles, and acute oral toxicity triage from PubChem PUG VIEW.

Skill172 starsChanged 4 months ago

What's in it

  1. Chemical Hazard and Toxicity Profiling
  2. Goal
  3. Instructions
  4. 1. Extract Safety Profile by CID
  5. 2. GHS Acute Oral Toxicity Triage Helper
  6. Python API Integration
  7. Constraints
---
name: chem-hazard-toxicity
description: Extract explicit safety warnings, GHS classifications, LD50 toxicity profiles, and acute oral toxicity triage from PubChem PUG VIEW.
category: [chemistry, drug-discovery]
---

# Chemical Hazard and Toxicity Profiling

## Goal
To programmatically extract critical safety information from the PubChem PUG-VIEW API. This skill pulls GHS Classifications, Hazard Classes, and Toxicological properties (like LD50/LC50 experimental animal records) for a given compound based on its CID, and performs GHS Acute Toxicity Category assignment and hazard statement consistency analysis.

## Instructions

### 1. Extract Safety Profile by CID
Provide the precise CID of the molecule to query safety metadata.

```bash
# Env: base-agent
python .agents/skills/chem-hazard-toxicity/scripts/get_safety_data.py \
  --cid 2519 \
  --outdir research/caffeine_safety \
  --output safety_caffeine.json
```

### 2. GHS Acute Oral Toxicity Triage Helper
Use `--triage` to extract consensus GHS statements ($\ge 50\%$), lowest rat oral LD50, GHS acute oral category (1–5 or `unclassified`), and check oral hazard code consistency:

```bash
# Env: base-agent
python .agents/skills/chem-hazard-toxicity/scripts/get_safety_data.py \
  --cid 2519 \
  --triage \
  --outdir research/caffeine_safety \
  --output triage_caffeine.json
```

### Python API Integration
Import helper functions directly into python scripts:

```python
from scripts.get_safety_data import (
    extract_consensus_ghs_codes,
    extract_lowest_rat_oral_ld50,
    assign_acute_oral_category,
    check_oral_code_consistency,
    profile_compound,
)

profile = profile_compound(2519, threshold_percent=50.0)
# Returns dict with cid, consensus_ghs_codes, oral_rat_ld50_mg_kg, oral_rat_ld50_evidence, acute_oral_category, ghs_oral_code_consistent
```

> **GHS Category & Code Consistency Rule**:
> - Category 1 ($\le 5\text{ mg/kg}$) & Category 2 ($5 < \text{LD}_{50} \le 50\text{ mg/kg}$) $\rightarrow$ expected GHS oral code `H300` (*Fatal if swallowed*).
> - Category 3 ($50 < \text{LD}_{50} \le 300\text{ mg/kg}$) $\rightarrow$ `H301` (*Toxic if swallowed*).
> - Category 4 ($300 < \text{LD}_{50} \le 2000\text{ mg/kg}$) $\rightarrow$ `H302` (*Harmful if swallowed*).
> - Category 5 ($2000 < \text{LD}_{50} \le 5000\text{ mg/kg}$) $\rightarrow$ `H303` (*May be harmful if swallowed*).
> - `unclassified` ($> 5000\text{ mg/kg}$) $\rightarrow$ empty set (`{}`).

## Constraints
- **Data Availability**: Relies on experimental or reported data listed in PubChem.
- **Network Limits**: Automatically handles standard `HTTP 503/429` rate limiting via exponential backoff.

---
---

**Author:** Bowen Deng
**Contact:** [GitHub @learningmatter-mit](https://github.com/learningmatter-mit)

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