💊 Drug-Drug Interaction (DDI) Prediction Web App

This project is a web-based application for predicting drug-drug interactions (DDIs) using machine learning models. It integrates biomedical datasets (like TWOSIDES, DrugBank, and RDF2Vec embeddings) with pre-trained models (MLP, XGBoost) to identify potential adverse interactions between drugs.

---

🧠 Project Highlights

• ✅ Built with Flask (Python)
• 🧬 Uses drug embeddings (rdf2vec) and curated drug name mappings
• 🤖 Pre-trained models:
  • MLP (.h5 file)
  • XGBoost (.pkl and .json)
• 📊 Data: TWOSIDES, DrugBank, RxNorm mappings
• 🧪 Web interface for predicting and displaying interactions

---

🚀 Getting Started

1. Clone the Repository

git clone https://github.com/Logicrithm/DDI.git
cd DDI

2. Install Dependencies

Make sure you have Python 3.8+ installed. Then install required packages:

pip install -r requirements.txt

3. Run the Web App

cd app
python app.py