TY - JOUR
T1 - Computational drug repurposing based on electronic health records
T2 - a scoping review
AU - Zong, Nansu
AU - Wen, Andrew
AU - Moon, Sungrim
AU - Fu, Sunyang
AU - Wang, Liwei
AU - Zhao, Yiqing
AU - Yu, Yue
AU - Huang, Ming
AU - Wang, Yanshan
AU - Zheng, Gang
AU - Mielke, Michelle M
AU - Cerhan, James R.
AU - Liu, Hongfang
N1 - Funding Information:
This work was supported by grants from the National Institute of Health (NIH) NIGMS (K99GM135488). We thank Gerberi, Danielle J. from Mayo Clinic Library to provide a literature search.
Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - 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.
AB - 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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U2 - 10.1038/s41746-022-00617-6
DO - 10.1038/s41746-022-00617-6
M3 - Review article
AN - SCOPUS:85131872277
SN - 2398-6352
VL - 5
JO - npj Digital Medicine
JF - npj Digital Medicine
IS - 1
M1 - 77
ER -