Natural Language to Code: AI-Powered Automation for CDISC-Compliant Datasets

Abstract

This talk introduces a generative AI-powered system that converts natural language coding specifications into R programs used to generate CDISC-compliant datasets, significantly reducing development time while ensuring compliance and accuracy. Leveraging techniques such as prompt engineering and Retrieval-Augmented Generation (RAG), the session will delve into the system’s technical architecture, key lessons learned, and its potential to transform clinical data programming.

Type
Publication
Presented at genAI Day 2025

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