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

arXiv 2505.24767 ↗First posted 30 May 2025stat.AP cs.AIcited by 0

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Abstract (arXiv)

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.

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References · 16

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  12. 2023Structured prompt interrogation and recursive extraction of semantics (SPIRES): A method for populating knowledge bases using zero-shot learningcited by 50
4 more
  1. 2023Bias and Fairness in Chatbots: An Overviewcited by 20
  2. 2018Natural Language Processing for EHR-Based Computational Phenotypingcited by 18
  3. 2023Enhancing Phenotype Recognition in Clinical Notes Using Large Language Models: PhenoBCBERT and PhenoGPTcited by 18
  4. 2020Drug repurposing for COVID-19 using graph neural network and harmonizing multiple evidencecited by 10

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