Computational drug repurposing based on electronic health records: a scoping review

Nansu Zong, Andrew Wen, Sungrim Moon, Sunyang Fu, Liwei Wang, Yiqing Zhao, Yue Yu, Ming Huang, Yanshan Wang, Gang Zheng, Michelle M Mielke, James R. Cerhan, Hongfang Liu

Research output: Contribution to journalReview articlepeer-review


Computational drug repurposing methods adapt Artificial intelligence (AI) algorithms for the discovery of new applications of approved or investigational drugs. Among the heterogeneous datasets, electronic health records (EHRs) datasets provide rich longitudinal and pathophysiological data that facilitate the generation and validation of drug repurposing. Here, we present an appraisal of recently published research on computational drug repurposing utilizing the EHR. Thirty-three research articles, retrieved from Embase, Medline, Scopus, and Web of Science between January 2000 and January 2022, were included in the final review. Four themes, (1) publication venue, (2) data types and sources, (3) method for data processing and prediction, and (4) targeted disease, validation, and released tools were presented. The review summarized the contribution of EHR used in drug repurposing as well as revealed that the utilization is hindered by the validation, accessibility, and understanding of EHRs. These findings can support researchers in the utilization of medical data resources and the development of computational methods for drug repurposing.

Original languageEnglish (US)
Article number77
Journalnpj Digital Medicine
Issue number1
StatePublished - Dec 2022

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Health Informatics
  • Computer Science Applications
  • Health Information Management


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