About This Project

Molecular Toxicity Prediction Tool

A research tool exploring the application of deep learning methods in molecular toxicity prediction, developed to support early-stage safety assessment in drug discovery.

Our Goal

We aim to contribute to computational toxicology research by developing accessible AI tools that may help researchers and professionals in their safety assessment workflows. This is an ongoing research project, and we welcome feedback and collaboration.

Main Features

Toxicity Prediction

A deep learning tool for predicting molecular toxicity endpoints, aiming to assist in early-stage safety assessment.

Molecular Analysis

Combines graph neural networks and molecular descriptors to analyze chemical structures.

Research Support

Designed to support drug discovery and chemical safety research workflows.

Technologies Used

Machine Learning

  • • Graph Neural Networks
  • • Transformer Models
  • • Deep Learning Frameworks

Molecular Processing

  • • RDKit Library
  • • Molecular Descriptors
  • • SMILES Notation

Potential Applications

Research Support

May assist in early-stage toxicity screening during drug discovery research.

Safety Assessment

Could support preliminary chemical safety evaluation workflows.

Learn More

This is an ongoing research project. We welcome feedback, suggestions, and collaboration opportunities to improve the tool and expand its capabilities.