# Admet Reasoning

> Interpretable ADMET analysis with mechanistic reasoning. Maps liabilities to structural causes and biological pathways. Based on CoTox (Park 2025) and DrugR (Liu 2026).

- Skill: `synthetic-sciences/admet-reasoning` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add synthetic-sciences/admet-reasoning`
- Raw SKILL.md: https://api.skillmd.com/api/skills/synthetic-sciences/admet-reasoning/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- License: MIT
- Author: synthetic-sciences (https://skillmd.com/u/synthetic-sciences)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/synthetic-sciences/admet-reasoning

---


# ADMET Reasoning

## Overview

Standard ADMET prediction tools output scores (e.g., "hERG = 0.85") without explaining why. This skill adds mechanistic reasoning — mapping each ADMET liability to its structural cause, the biological mechanism it affects, and a suggested structural fix.

Based on:
- **CoTox** (Park et al., 2025): Chain-of-thought toxicity reasoning with structural + biological context improved F1 from 0.37 to 0.66
- **DrugR** (Liu et al., 2026): Explicit liability reasoning before optimization improved scores 18×

## When to Use This Skill

- **After ADMET prediction**: Interpret flagged liabilities with structural explanations
- **Lead optimization planning**: Understand which structural features to modify and why
- **Toxicity reports**: Generate interpretable toxicity assessments for medicinal chemistry teams
- **Design review**: Evaluate whether proposed modifications address the right liabilities

**Do NOT use this skill for:**
- Raw ADMET score computation (use `admet-prediction` instead)
- Molecular optimization (use `molecular-optimization` instead)

### Related Skills
- **admet-prediction**: Compute ADMET properties (run this first)
- **molecular-optimization**: Iterative optimization using liability analysis
- **rdkit**: Core molecular operations

## Installation

### Required dependencies

```bash
pip install rdkit-pypi numpy pandas
```

## Core Workflows

### 1. Full Liability Report

Generate interpretable ADMET analysis for a molecule:

```bash
python scripts/reason_admet.py --smiles "c1ccc(NC(=O)c2ccccc2Cl)cc1" --output report.json
```

### 2. Batch Liability Analysis

```bash
python scripts/reason_admet.py --input compounds.csv --output liability_report.csv
```

### 3. Targeted Toxicity Reasoning

Focus on specific endpoints:

```bash
python scripts/reason_admet.py --smiles "CCN1CCCC1" --endpoints hERG,DILI,CYP --output tox_report.json
```

## Script Reference

| Script | Purpose | Key Outputs |
|--------|---------|-------------|
| `reason_admet.py` | Full ADMET reasoning with structural explanations | JSON report with liabilities, causes, mechanisms, fixes |