Unified Python SDK for OpenFDA, PubMed, and ClinicalTrials.gov with clinical intelligence, interaction detection, and research tools.

Comprehensive bioinformatics platform for precision medicine. Explore drug-gene interactions, pharmacokinetics, clinical trials, and drug repurposing. 20+ research modules. Free & open-source (MIT).

AI-powered pharmacogenomics platform using GATv2 to predict organ health, drug interactions, and personalized longevity insights from DNA, lifestyle, and medications.

Production-ready healthcare AI agent with 9 LangChain tools, 5-layer verification, and 100-case eval dataset. Integrates with OpenEMR.

Clinical Decision Support MCP Server for Healthcare AI - Drug interactions, risk scores, lab interpretation, FHIR integration

Persistent, auditable clinical memory for healthcare AI agents. MCP + A2A. Powered by mind-mem and MIND Lang scoring kernels. Built for Agents Assemble Healthcare AI Hackathon.

Web application for checking drug interactions in Estonian.

drug interactions with 2 drugs

ML training pipelines with RunPod serverless GPU infrastructure. Includes DDI drug interaction classifier using Bio_ClinicalBERT on 176K DrugBank samples.

A Django web application to search for medicinal products basing on criteria specified by the user. The app scrapes a website and saves the downloaded data into its own database, allowing you to search for the desired drug and visualize its interactions with other drugs. It also implements the functionality of a thematic internet forum.

🧠 SafeMeds is an intelligent LangGraph-based medical assistant that checks drug interactions, recognizes medicines from images, and answers health-related questions.

Integrated cheminformatics platform for molecular descriptor analysis, drug-likeness evaluation, and drug–drug interaction prediction using RDKit, PubChem, and SwissADME validation.

Zero-dependency Python API for herb-drug interactions: 250 plants, 53 drug classes, 592 interactions.

Full-stack web application that analyzes drug interactions using FDA's OpenFDA API. Built with Python/Flask, featuring real-time drug label search, interaction detection, and user-friendly interface for healthcare safety information.

ML-driven platform for Glioblastoma drug recommendation using GDSC data. Features multi-model prediction (RF, XGBoost, NN, SVM, KNN), molecular similarity analysis (Tanimoto, MCS, GCN), pathway enrichment, drug interaction checking, and combination therapy optimization with interactive dashboard.

Drug Interaction Cascade Analyzer — Detect dangerous multi-drug interactions using knowledge graph + CYP450 enzyme cascade analysis on real FDA data

Drug interaction checker & pharmaceutical compliance

Aushadhi — AI Drug Interaction Predictor. LLM-augmented multi-drug interaction prediction for polypharmacy safety.

Heterogeneous GAT with temporal attention for drug-drug interaction prediction. Multi-task learning (interaction + metabolite pathway + temporal dynamics) on Tox21 molecular data. 99.9% interaction accuracy, 0.875 temporal correlation.

A machine learning system for predicting potential drug-food interactions using ensemble methods and explainable AI techniques. This project implements multiple classification algorithms to identify interaction risks and provides interpretable predictions through SHAP and LIME analysis.