Semantic Search of FDA Guidance Documents Using Generative AI.

ABSTRACT:

Introduction

Generative artificial intelligence (AI) has the potential to transform and accelerate how information is accessed during the regulation of human drug and biologic products.

Objectives

Determine whether a generative AI-supported application with retrieval-augmented generation (RAG) architecture can be used to correctly answer questions about the information contained in FDA guidance documents.

Methods

Five large language models (LLMs): Flan-UL2, GPT-3.5 Turbo, GPT-4 Turbo, Granite, and Llama 2, were evaluated in conjunction with the RAG application Golden Retriever to assess their ability to answer questions about the information contained in clinically oriented FDA guidance documents. Models were configured to precise mode with a low temperature parameter

SUBMITTER: Proestel S 

PROVIDER: S-EPMC12446095 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature