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Computational drug repurposing based on electronic health records: a scoping review
Journal article   Open access   Peer reviewed

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, …
NPJ digital medicine, Vol.5(1), pp.77-77
06/14/2022
DOI: 10.1038/s41746-022-00617-6
PMCID: PMC9198008
PMID: 35701544
url
https://doi.org/10.1038/s41746-022-00617-6View
Published (Version of record) Open Access

Abstract

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.

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