Honest evaluation of emergent 3-drug interaction prediction from FAERS using GNNs

Thesis research on open cross domain transfer learning in Graph Isomorphism Networks.

AushadhiNet-GATv2-128 is GNN Model to Predict Multiple Drug Pair Interaction

Multi-task GNN predicting inhibition of 5 major cytochrome P450 enzymes (CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP3A4) for drug-drug interaction assessment.

💊 Drug Annotation from Regulatory Texts (DART) is a structured dataset of Italian drug product leaflets ("Riassunti delle Caratteristiche del Prodotto", or RCPs), curated for Clinical NLP applications.

Exploration of vanilla GIN, GIN with edge heuristics in prediction head, Heuristics weighted Edge-GNN for link prediction in ogbl-ddi dataset

CureLens AI is an AI-powered medication safety platform designed to help healthcare professionals and patients make safer medication decisions. The platform uses machine learning models to predict potential drug-drug interactions, assess personalized medication risks based on patient profiles, and recommend safer alternative medications.

Towards Interpretable Drug-Drug Interaction Prediction: A Graph-Based Approach with Molecular and Network-Level Explanations

A next-js app to check interactions between drugs.

This is the repository for the AI4ALL Ignite Class 13B project on predicting adverse effects of drug interactions.

Scripts for the research paper "SF-Rx: A Multi-output Deep Neural Network-Based Framework Predicting Drug-Drug Interaction under Realistic Conditions for Safe Prescription"

A DNN model for predicting adverse drug-drug and drug-food interactions (Top 7 in Northern Region, GDGoC Hackathon 2025)

Drug interaction prediction using deep learning leverages neural networks to identify harmful combinations by analyzing biomedical and molecular data. This enhances patient safety and supports smarter drug development.

Code for my Master thesis on "Intelligent Drug-Drug Interaction Extraction: A Natural Language Processing Approach to Biomedical Text Analysis".

Uncovering Amiloride's Mechanisms of Action in Multiple Myeloma: A Bioinformatics Approach

Data and code of CADGL: Context-Aware Deep Graph Learning for Predicting Drug-Drug Interactions

DrugDoseFinder: A Python tool that uses fuzzy name matching and RDF graphs to search for drugs and retrieve their dosage information. Designed for accurate querying and easy integration with personalized medical RDF datasets.

Official Implementation of ADEP paper.