adme-prediction

Official

Predict ADME properties of molecules with ML.

AuthorInternScience
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Predict ADME properties of small molecules from SMILES strings to accelerate early-stage drug discovery by rapidly evaluating pharmacokinetic traits.

Core Features & Use Cases

  • Morgan fingerprint-based predictions using Random Forest models for six key ADME properties: Caco-2 permeability, PAMPA, HIA, Pgp inhibition, Bioavailability, and Lipophilicity.
  • CLI and Python API support for single and batch predictions, enabling integration into existing pipelines and notebooks.
  • Real-world scenario: screen a library of SMILES to filter candidates with favorable permeability and oral bioavailability before synthesis.

Quick Start

Use the adme-prediction skill to predict ADME properties for a given SMILES string.

Dependency Matrix

Required Modules

rdkitscikit-learnnumpypandastdc

Components

scripts

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: adme-prediction
Download link: https://github.com/InternScience/ChemClaw/archive/main.zip#adme-prediction

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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