Speaker
Description
Building exploratory analysis dashboards for clinical trials requires considerable expertise, extensive time, and deep familiarity with specialized frameworks. In this talk, we share our GenAI solution to significantly streamline this process. We will present a tool, powered by Claude Code, that enables biostatisticians and clinical researchers to effortlessly create and immediately preview applications tailored for exploratory clinical data analysis using {teal} R package.
Throughout our journey, we experimented with various GenAI-driven solutions, including code editors integrated with AI assistance tools, and approaches leveraging MCP servers. Current implementation is an interactive AI-powered chat interface designed to simplify the application-building experience, providing users with immediate previews, and reducing both development complexity and the learning curve associated with the {teal} package.
We will demonstrate how GenAI-driven solutions can empower users with limited programming backgrounds to rapidly build effective exploratory analysis dashboards, discuss challenges encountered, and highlight insights gained through our iterative development process.
Additional Material or Paper
https://www.appsilon.com/tealflow
https://github.com/Appsilon/TealFlowMCP
If you used AI tools or services to support the preparation of this submission, please state the name and reason for using each of them.
The tool that will be presented is using heavily AI, it is the goal, not sure if that counts.
| Keywords: Please list up to 5 keywords to help us find the right session for your contribution. | GenAI, clinical trials, teal |
|---|---|
| Virtual Option | This submission is for onsite presentation only |
| Video Recording | Video sharing is fine |
| The author(s) agree(s) to take responsibility and be accountable for the contents of the submission and is/are authorized to present it. | Confirm |