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Here, we present a novel high\u2010throughput data\u2010driven algorithm that identifies and prioritizes drug candidates that show significant effects on specific clinical indicators by utilizing large\u2010scale EMR data. We chose four laboratory tests as clinical indicators: hemoglobin A1c (HbA1c), low\u2010density lipoprotein (LDL) cholesterol, triglycerides (TGs), and high\u2010density lipoprotein (HDL) cholesterol. From a 5\u2010year EMR database, we generated datasets consisting of paired data with averaged measurement values during on and off each drug in each patient, adjusted for co\u2010administered drug effects at each timepoint, and applied one sample <jats:italic>t<\/jats:italic>\u2010test with the Bonferroni correction for statistical analysis. Among 1,774 drugs, 45 were associated with increases in HDL cholesterol, and 41, 146, and 65 were associated with reductions in HbA1c, LDL cholesterol, and TGs, respectively. We compared the list of candidate drugs with that of drugs indicated for relevant clinical conditions and found that the algorithm had high values for both sensitivity (range 0.95\u20131.00) and negative predictive value (range 0.95\u20131.00). Our algorithm was able to rediscover well\u2010known drugs that are used for diabetes and dyslipidemia while revealing potential candidates without current indications but have shown promising results in the literature. Our algorithm may facilitate the repositioning of drugs with proven safety profiles.<\/jats:p>","DOI":"10.1002\/cpt.1980","type":"journal-article","created":{"date-parts":[[2020,7,4]],"date-time":"2020-07-04T09:15:03Z","timestamp":1593854103000},"page":"1299-1307","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["High\u2010Throughput Algorithm for Discovering New Drug Indications by Utilizing Large\u2010Scale Electronic Medical Record Data"],"prefix":"10.1111","volume":"108","author":[{"given":"Do\u2010Hoon","family":"Kim","sequence":"first","affiliation":[{"name":"Department of Information Medicine Asan Medical Center Seoul Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jung\u2010Eun","family":"Lee","sequence":"additional","affiliation":[{"name":"Asan Institute for Life Sciences Asan Medical Center Seoul Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong\u2010Gil","family":"Kim","sequence":"additional","affiliation":[{"name":"Division of Rheumatology Department of Internal Medicine Asan Medical Center University of Ulsan College of Medicine Seoul Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yura","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Information Medicine Asan Medical Center Seoul Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dong\u2010Woo","family":"Seo","sequence":"additional","affiliation":[{"name":"Department of Information Medicine Asan Medical Center Seoul Republic of Korea"},{"name":"Department of Emergency Medicine Asan Medical Center University of Ulsan College of Medicine Seoul Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kye Hwa","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Information Medicine Asan Medical Center Seoul Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jae\u2010Ho","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Information Medicine Asan Medical Center Seoul Republic of Korea"},{"name":"Department of Emergency Medicine Asan Medical Center University of Ulsan College of Medicine Seoul Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Woo Sung","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Information Medicine Asan Medical Center Seoul Republic of Korea"},{"name":"Department of Pulmonary and Critical Care Medicine University of Ulsan College of Medicine Seoul Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Young\u2010Hak","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Information Medicine Asan Medical Center Seoul Republic of Korea"},{"name":"Health Innovation Big Data Center Asan Institute for Life Science Asan Medical Center Seoul Republic of Korea"},{"name":"Department of Cardiology Asan Medical Center University of Ulsan College of Medicine Seoul Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ji Seon","family":"Oh","sequence":"additional","affiliation":[{"name":"Department of Information Medicine Asan Medical Center Seoul Republic of Korea"},{"name":"Health Innovation Big Data Center Asan Institute for Life Science Asan Medical Center Seoul Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2020,8,13]]},"reference":[{"key":"e_1_2_10_1_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrd1468"},{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1136\/amiajnl-2014-002649"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1126\/scitranslmed.3002747"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1158\/0008-5472.CAN-11-3439"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.4239\/wjd.v6.i13.1246"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11745-010-3408-1"},{"key":"e_1_2_10_7_1","unstructured":"OHDSI (Observational Health Data Sciences and Informatics)<https:\/\/www.ohdsi.org\/>. 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