PharmaCPU2 credits

ADMET Prediction

Predict absorption, distribution, metabolism, excretion, and toxicity

Predict ADMET properties from SMILES to assess drug-likeness and safety early in the discovery pipeline. Covers solubility, permeability, CYP metabolism, hERG liability, and hepatotoxicity risk.

$0.02

per API call

credits per call

/v1/pharma/adme

API endpoint

Features

Absorption: Caco-2 permeability, HIA prediction

Distribution: plasma protein binding, BBB penetration

Metabolism: CYP450 inhibition/substrate prediction

Excretion: clearance estimation

Toxicity: hERG, hepatotoxicity, AMES mutagenicity

Drug-likeness: Lipinski, Veber, PAINS filters

Quick Start

ADMET-AI — Python Examplepython

import requests

API_KEY = "sk-sci-your-key-here"
url = "https://scirouter.ai/v1/pharma/adme"

response = requests.post(url, json={
    "smiles": "CC(=O)Oc1ccccc1C(=O)O"  # Aspirin
}, headers={"Authorization": f"Bearer {API_KEY}"})

admet = response.json()
print(f"Caco-2 Permeability: {admet['absorption']['caco2']}")
print(f"hERG Risk: {admet['toxicity']['herg']}")
print(f"Hepatotoxicity: {admet['toxicity']['hepatotoxicity']}")