A survey of using EHR as real-world evidence for discovering and validating new drug indications

TL;DR

This survey reviews how Electronic Health Records are utilized as real-world evidence for drug repurposing, highlighting data sources, methodologies, and challenges, including the role of large language models and study design considerations.

Contribution

It provides a comprehensive overview of current EHR-based drug repurposing approaches, emphasizing recent methodological advances and challenges in validation.

Findings

EHR data sources and processing techniques are evolving.

Study designs and statistical frameworks are key to validation.

Large language models are emerging tools in this domain.

Abstract

Electronic Health Records (EHRs) have been increasingly used as real-world evidence (RWE) to support the discovery and validation of new drug indications. This paper surveys current approaches to EHR-based drug repurposing, covering data sources, processing methodologies, and representation techniques. It discusses study designs and statistical frameworks for evaluating drug efficacy. Key challenges in validation are discussed, with emphasis on the role of large language models (LLMs) and target trial emulation. By synthesizing recent developments and methodological advances, this work provides a foundational resource for researchers aiming to translate real-world data into actionable drug-repurposing evidence.