🚀 Drug Launch Intelligence Agent

AI-powered multi-agent system for pharmaceutical launch strategy. Enter any drug and indication — 4 specialist AI agents run in parallel to generate a comprehensive launch intelligence brief in 60 seconds.

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🎯 What It Does

A pharma launch team manually assembling competitive intelligence, clinical evidence, KOL mapping, and market access analysis spends 3-5 days across multiple data sources. This tool does it in 60 seconds.

Enter drug + indication → 4 agents run simultaneously:

• 🔍 Competitive Landscape Agent — searches ClinicalTrials.gov
• 📚 Clinical Evidence Agent — searches PubMed literature
• 👥 KOL Identification Agent — searches NPI Registry
• 📰 Market Intelligence Agent — searches live news via Tavily

Synthesis Agent combines everything into:

• Executive summary with launch readiness rating
• Competitive positioning table
• Evidence strength assessment
• KOL engagement strategy
• Market access and payer outlook
• Top 3 priorities before launch
• Downloadable intelligence brief

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🏗️ Architecture — LangGraph Multi-Agent System

User Query
    ↓
Multi-Agent Orchestrator
    ↓
┌─────────────────────────────────────┐
│ Competitive  Evidence  KOL   News   │
│   Agent    + Agent  + Agent + Agent │
│ (sequential execution)              │
└─────────────────────────────────────┘
    ↓
Synthesis Agent (Claude AI)
    ↓
Launch Intelligence Brief

Full LangGraph implementation available in agent_graph_langgraph.py

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🛠️ Built With

Tool	Purpose
Python	Core language
LangGraph	Multi-agent orchestration architecture
LangChain	Agent framework
ClinicalTrials.gov API	Competitive trial landscape
PubMed / Biopython	Clinical evidence assessment
NPI Registry API	KOL identification
Tavily API	Market and news intelligence
Claude API (Anthropic)	Launch brief synthesis
Streamlit	Web interface

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📁 Project Structure

├── competitive_agent.py        # ClinicalTrials.gov competitor search
├── evidence_agent.py           # PubMed evidence assessment
├── kol_agent.py                # NPI Registry KOL identification
├── news_agent.py               # Tavily market intelligence
├── synthesis_agent.py          # Claude AI brief generation
├── agent_graph.py              # Multi-agent orchestrator
├── agent_graph_langgraph.py    # Full LangGraph implementation
├── streamlit_app.py            # Web interface
├── requirements.txt            # Python dependencies
└── .env.example                # API key template

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🚀 Quick Start

1. Clone the repo

git clone https://github.com/LifeSciForge/Drug_Launch_Intelligence.git
cd Drug_Launch_Intelligence

2. Create virtual environment

python3 -m venv venv
source venv/bin/activate

3. Install dependencies

pip install -r requirements.txt

4. Add your API keys

cp .env.example .env
# Edit .env and add your keys

5. Run the app

streamlit run streamlit_app.py

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💡 Example Searches

Drug	Indication	What You Get
ivonescimab	NSCLC	Pre-launch brief, PDUFA Nov 2026
retatrutide	obesity	Phase 3 launch readiness
zilebesiran	hypertension	RNA interference launch strategy
tarlatamab	small cell lung cancer	BiTE antibody brief

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🎯 Target Users

• Commercial teams — launch strategy and competitive positioning
• Medical Affairs — KOL engagement and publication strategy
• Market Access — payer landscape and formulary strategy
• CI analysts — rapid competitive intelligence

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🔑 API Keys Required

Key	Source	Cost
ANTHROPIC_API_KEY	console.anthropic.com	Free trial available
TAVILY_API_KEY	tavily.com	Free tier — 1000/month

App runs in placeholder mode without API keys — all trial, literature, and KOL data still loads from live sources.

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👤 Author

Pranjal Das AI & Automation for Life Sciences github.com/LifeSciForge

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Data sources: ClinicalTrials.gov · PubMed · NPI Registry · Tavily All data is 100% open and publicly available