# Bio Admet Prediction

Predicts ADMET properties using ADMETlab 3.0 API or DeepChem models.

- Repository: https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills (3090 stars)
- Category: Engineering
- License: see repository
- Last updated: 2026-07-21
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-admet-prediction -g -a claude-code -y`
Codex: `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-admet-prediction -g -a codex -y`
Cursor: `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-admet-prediction -g -a cursor -y`
Gemini CLI: `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-admet-prediction -g -a gemini-cli -y`

## Description

Predicts ADMET properties using ADMETlab 3.0 API or DeepChem models. Estimates bioavailability, CYP inhibition, hERG liability, and 119 toxicity endpoints with uncertainty quantification. Filters for PAINS and other structural alerts. Use when filtering compounds for drug-likeness or prioritizing leads by predicted safety.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

## Version Compatibility

Reference examples tested with: RDKit 2024.03+, pandas 2.2+

Before using code patterns, verify installed versions match. If versions differ:
- Python: `pip show <package>` then `help(module.function)` to check signatures

If code throws ImportError, AttributeError, or TypeError, introspect the installed
package and adapt the example to match the actual API rather than retrying.

# ADMET Prediction

**"Predict the drug-likeness and toxicity of my compounds"** → Estimate ADMET properties (bioavailability, CYP inhibition, hERG liability, toxicity) for candidate molecules using the ADMETlab 3.0 API or RDKit PAINS/structural alert filters, producing a safety/drugability profile for lead prioritization.
- Python: ADMETlab 3.0 REST API via `requests`, `FilterCatalog` for PAINS (RDKit)

Predict absorption, distribution, metabolism, excretion, and toxicity properties.

## ADMETlab 3.0 API

**Goal:** Predict ADMET properties for a batch of compounds using a web API.

**Approach:** Submit SMILES to the ADMETlab 3.0 REST endpoint and parse the returned JSON into a DataFrame of 119 endpoint predictions with uncertainty estimates.

ADMETlab 3.0 provides 119 endpoints with uncertainty estimates.

```python
import requests
import pandas as pd

def predict_admet_batch(smiles_list, api_url='https://admetlab3.scbdd.com/api/predict'):
    '''
    Predict ADMET properties using ADMETlab 3.0 API.

    Note: SwissADME has NO API - it is web-only.
    '''
    payload = {
        'smiles': smiles_list
    }

    response = requests.post(api_url, json=payload)
    response.raise_for_status()

    return pd.DataFrame(response.json())

# Example usage
# smiles = ['CCO', 'c1ccccc1O', 'CC(=O)Oc1ccccc1C(=O)O']
# results = predict_admet_batch(smiles)
```

## Key ADMET Endpoints

The rest: https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/blob/HEAD/skills/bio-admet-prediction/SKILL.md