TealFlow Gallery

Clinical Trial Analysis Application Demo

---

About This Application

This is an open-source example application created with TealFlow, Appsilon's AI-powered platform for rapidly building clinical trial analysis applications.

This demo showcases a production-ready Shiny application featuring:

• 📊 Interactive clinical data visualizations
• 🔬 Multiple analysis modules for CDISC ADaM datasets
• 🎨 Custom branding and styling
• 📈 Survival analysis, adverse events, quality of life assessments, and more

Watch TealFlow in action: Demo Video

---

What is TealFlow?

TealFlow is a browser-based AI platform that combines natural language processing with the open-source {teal} R/Shiny framework to generate clinical trial analysis applications in minutes instead of weeks.

Key Benefits

• ⚡ Rapid Development: From idea to prototype in minutes, full application in hours
• 🔒 Data Privacy: AI reviews only dataset structure, never actual patient data
• ✅ Compliance-Ready: Uses pre-validated {teal} modules for GxP compliance
• 👥 No-Code Interface: Describe your analysis goals in natural language
• 🚀 Production-Ready: Export to GitHub or deploy to Posit Connect immediately

Learn more about TealFlow →

---

Build Your Own with TealFlowMCP

Want to create teal applications using AI assistants like Claude Code, GitHub Copilot, or Cursor? Try our open-source TealFlowMCP server!

TealFlowMCP enables LLMs to discover, understand, and generate Teal applications through natural language requests.

Features:

• 🔍 Module discovery and documentation
• 🤖 Automated code generation
• 📦 Dataset and environment management
• ✔️ Validation and compatibility checks

Installation:

pip install tealflow-mcp

View TealFlowMCP Documentation →

---

Getting Started

Prerequisites

• R version 4.4.2 or higher

Installation

1. Clone the repository

   git clone https://github.com/Appsilon/TealFlowGallery
   cd TealFlowGallery

2. Restore R package environment

   This project uses renv for package management. Open R/RStudio in the project directory and run:

   renv::restore()

   This will install all required packages as specified in renv.lock.

3. Run the application

   # Option 1: From R console
   shiny::runApp()
   
   # Option 2: Direct execution
   source("app.R")
   
   # Option 3: In RStudio, click "Run App" button

The application will launch in your default web browser.

---

Application Structure

TealFlowGallery/
├── app.R              # Main application file with UI and module configuration
├── data.R             # Data loading and teal_data object creation
├── _brand.yaml        # Branding configuration (colors, fonts, logos)
├── *.Rds              # Clinical datasets (ADSL, ADTTE, ADRS, ADQS, ADAE)
├── www/               # Static resources
│   ├── logo_color.svg
│   ├── template_style.css
│   └── branding_style.css
└── renv/              # R package management

Clinical Datasets

This application demonstrates analysis of CDISC ADaM standard datasets:

• ADSL: Subject-level analysis (demographics, baseline characteristics)
• ADTTE: Time-to-event analysis (survival, efficacy endpoints)
• ADRS: Response analysis (binary outcomes, tumor response)
• ADQS: Quality of life questionnaires
• ADAE: Adverse events

---

About Appsilon

This application is created and maintained by Appsilon. We are a technology partner for life sciences companies, delivering open-source AI, R and Python solutions, cloud-based statistical computing environments, and SAS-to-Open Source migration to accelerate drug development in regulated settings.

Connect With Us

• 🌐 Website: appsilon.com
• 💼 LinkedIn: linkedin.com/company/appsilon
• 🐙 GitHub: github.com/Appsilon

---

Made with ❤️ by Appsilon