🚀 PharmaMind: Agentic AI System for Drug Repurposing Research 🧩 Overview
PharmaMind is an Agentic AI System designed to automate drug repurposing research — discovering new potential uses for existing drugs or molecules.
Instead of scientists manually searching across databases like PubMed, ClinicalTrials.gov, or Google Patents, PharmaMind uses a multi-agent AI architecture to automatically:
Collect biomedical data from multiple sources
Summarize and visualize potential new drug uses
Generate a downloadable, structured report
🎯 Objective
“To build an AI system that can automatically research, summarize, and visualize potential new medical uses for any existing molecule.”
Given a molecule name (e.g., Metformin), the system:
Fetches research papers, clinical trials, patents, and market data
Evaluates repurposing potential using AI reasoning
Summarizes results into an interactive dashboard and PDF report
🧠 System Architecture 🧩 1. Master Agent (Coordinator)
Understands user query (e.g., “Find new uses for Metformin”)
Delegates subtasks to specialized worker agents
Merges all outputs into a structured summary
⚙️ 2. Worker Agents Agent Function Data Source 🧪 Clinical Trials Agent Finds ongoing/past trials for the molecule ClinicalTrials.gov API 📚 Research Agent Fetches related papers and research trends Semantic Scholar API, PubMed API 🧬 Patent Agent Identifies patents involving the molecule Lens.org / Google Patents 💹 Market Agent Estimates disease demand and market size OpenFDA, WHO, Kaggle datasets 📊 Report Agent Compiles all outputs into visual summary (PDF + charts) Local data / Plotly / ReportLab 🧰 Tech Stack 🖥️ Frontend
React.js — Interactive UI
Tailwind CSS / Material UI — Responsive, clean design
Chart.js / Recharts / Plotly — Data visualization
Framer Motion — Animations & transitions
⚙️ Backend
FastAPI (Python) — REST API for AI & data fetching
LangChain / CrewAI / LlamaIndex — Multi-agent orchestration
Celery / AsyncIO — For parallel agent tasks
Pandas + Plotly — Data cleaning & visualization
🧠 AI / NLP Layer
OpenAI GPT-4 / GPT-5 API — Reasoning & summarization
BioBERT / PubMedBERT — Biomedical NLP
SciSpacy — Entity extraction (drugs, diseases)
🗃️ Database
MongoDB — Cache and store query results
Redis (optional) — For fast in-memory caching
🔍 Data Sources Source Description ClinicalTrials.gov Clinical trials data PubMed Central Biomedical research papers Semantic Scholar API Research metadata PubChem Molecular data Lens.org Patent search Kaggle Datasets Market & disease data OpenFDA API Drug usage and approvals 🧩 System Workflow
User Input: → User enters a molecule name (e.g., Metformin)
Master Agent: → Dispatches parallel tasks to worker agents
Worker Agents: → Collect and summarize domain-specific data
Report Agent: → Merges all insights → generates JSON summary + PDF
Frontend Dashboard: → Displays clinical trials, papers, patents, and market trends
Final Output: ✅ Drug overview ✅ Ongoing trials & new indications ✅ Key papers & patents ✅ Market potential chart ✅ Downloadable report
⚙️ Setup & Installation Clone the repository git clone https://github.com/yourusername/pharmamind.git cd pharmamind
Install dependencies pip install -r requirements.txt
Run FastAPI backend uvicorn main:app --reload
Frontend (if using MERN) npm install npm start
🧩 AI Agent Development Roadmap Phase Task Tools Duration 1 Setup environment & Master Agent LangChain, FastAPI 4 hrs 2 Build Clinical & Research Agents APIs 1 day 3 Add Patent & Market Agents Lens.org, Kaggle 1 day 4 Report Agent + Visualization GPT, Plotly, ReportLab 1 day 5 Integration with Backend FastAPI 3 hrs 📄 Example Output
Input: Metformin Output Includes:
12 ongoing clinical trials (mainly cancer & PCOS)
Top 5 papers on new therapeutic uses
3 recent patents (2023–2024)
Global oncology market size: $200B+
Downloadable PDF summary
🔮 Future Scope
Integrate Knowledge Graphs for drug–gene–disease correlations
Use Graph Neural Networks for deeper relationship prediction
Chrome Extension for quick in-browser research
Voice-based molecule search
🧑💻 Team Structure Role Members Responsibilities AI & Agents Team (3) Builds 4 worker agents + Master agent Frontend & Backend Team (2) Builds MERN dashboard + FastAPI bridge