{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T15:47:01Z","timestamp":1789055221894,"version":"build-2803163510"},"reference-count":50,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2024,11,25]],"date-time":"2024-11-25T00:00:00Z","timestamp":1732492800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["ascpt.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Clin Pharma and Therapeutics"],"published-print":{"date-parts":[[2025,4]]},"abstract":"<jats:p>While drug\u2013drug interactions (DDIs) and their pharmacokinetic (PK) mechanisms are well\u2010studied prior to drug approval, severe adverse drug reactions (SADRs) caused by DDIs often remain underrecognized due to limitations in pre\u2010marketing clinical trials. To address this gap, our study utilized a literature database, applied natural language processing (NLP) techniques, and conducted multi\u2010source electronic health record (EHR) validation to uncover underrecognized DDI\u2010SADR signals that warrant further investigation. PubMed abstracts related to DDIs from January 1962 to December 2023 were retrieved. We utilized PubTator Central for Named Entity Recognition (NER) to identify drugs and SADRs and employed SciFive for Relation Extraction (RE) to extract DDI\u2010SADR signals. The extracted signals were cross\u2010referenced with the DrugBank database and validated using logistic regression, considering risk factors including patient demographics, drug usage, and comorbidities, based on EHRs from Vanderbilt University Medical Center (VUMC) and the All of Us research program. From 160,321 abstracts, we identified 111 DDI\u2010SADR signals. Seventeen were statistically significant (13 by one EHR and 4 by both EHR databases), with 9 being previously not recorded in the DrugBank. These included methadone\u2010ciprofloxacin\u2010respiratory depression, oxycodone\u2010fluvoxamine\u2010clonus, tramadol\u2010fluconazole\u2010hallucination, simvastatin\u2010fluconazole\u2010rhabdomyolysis, ibrutinib\u2010amiodarone\u2010atrial fibrillation, fentanyl\u2010diltiazem\u2010delirium, clarithromycin\u2010voriconazole\u2010acute kidney injury, colchicine\u2010cyclosporine\u2010rhabdomyolysis, and methadone\u2010voriconazole\u2010arrhythmia (odds ratios (ORs) ranged from 1.9 to 35.83, with <jats:italic>P<\/jats:italic>\u2010values ranging from &lt;\u20090.001 to 0.017). Utilizing NLP to extract DDI\u2010SADRs from Biomedical Literature and validating these findings through multiple\u2010source EHRs represents a pioneering approach in pharmacovigilance. This method uncovers clinically relevant SADRs resulting from DDIs that were not evident in pre\u2010marketing trials or the existing DDI knowledge base.<\/jats:p>","DOI":"10.1002\/cpt.3500","type":"journal-article","created":{"date-parts":[[2024,11,25]],"date-time":"2024-11-25T09:28:58Z","timestamp":1732526938000},"page":"1078-1087","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Discovering Severe Adverse Reactions From Pharmacokinetic Drug\u2013Drug Interactions Through Literature Analysis and Electronic Health Record Verification"],"prefix":"10.1002","volume":"117","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8240-1198","authenticated-orcid":false,"given":"Eugene","family":"Jeong","sequence":"first","affiliation":[{"name":"Department of Biomedical Informatics, School of Medicine Vanderbilt University Medical Center  Nashville Tennessee USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6649-4766","authenticated-orcid":false,"given":"Yu","family":"Su","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering College of Engineering, The Ohio State University  Columbus Ohio USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0746-1809","authenticated-orcid":false,"given":"Lang","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics College of Medicine, The Ohio State University  Columbus Ohio USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8232-8840","authenticated-orcid":false,"given":"You","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, School of Medicine Vanderbilt University Medical Center  Nashville Tennessee USA"},{"name":"Department of Computer Science School of Engineering, Vanderbilt University  Nashville Tennessee USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2024,11,25]]},"reference":[{"key":"e_1_2_11_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40266-019-00726-0"},{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(02)11203-7"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1365-2125.2004.02244.x"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/bcp.14762"},{"key":"e_1_2_11_5_1","first-page":"601","article-title":"Pharmacokinetic drug\u2010drug interaction and their implication in clinical management","volume":"18","author":"Palleria C.","year":"2013","journal-title":"J. Res. Med. Sci."},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/clpt.1992.135"},{"key":"e_1_2_11_7_1","first-page":"16","article-title":"Understanding drug safety and how to maximize it for patients","volume":"24","author":"Furberg C.D.","year":"2011","journal-title":"J. Am. Acad. Phy. Assis."},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1177\/106002808702101114"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.amjcard.2020.05.011"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/pds.677"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1002\/pds.1001"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.1080\/00031305.1999.10474456"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s002280050466"},{"key":"e_1_2_11_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40264-014-0180-9"},{"key":"e_1_2_11_15_1","doi-asserted-by":"publisher","DOI":"10.1097\/00001888-200112000-00025"},{"key":"e_1_2_11_16_1","unstructured":"Boyce R.D. Gardner G.&Harkema H.Using natural language processing to extract drug\u2010drug interaction information from package inserts. BioNLP: Proceedings of the 2012 Workshop on Biomedical Natural Language Processing 206\u2013213(2012)"},{"key":"e_1_2_11_17_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1002614"},{"key":"e_1_2_11_18_1","doi-asserted-by":"publisher","DOI":"10.1002\/cpt.1745"},{"key":"e_1_2_11_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2024.104639"},{"key":"e_1_2_11_20_1","doi-asserted-by":"publisher","DOI":"10.1021\/tx700079z"},{"key":"e_1_2_11_21_1","unstructured":"U.S. FDA Drug Development and Drug Interactions: Table of Substrates Inhibitors and Inducers.https:\/\/www.fda.gov\/drugs\/druginteractions\u2010labeling\/drug\u2010development\u2010and\u2010drug\u2010interactions\u2010tablesubstrates\u2010inhibitors\u2010and\u2010inducers. Accessed November 19 2022."},{"key":"e_1_2_11_22_1","unstructured":"Flockhart D. Thacker D. McDonald C.&Desta Z.The Flockhart cytochrome P450 drug\u2010drug interaction table. Division of Clinical Pharmacology Indiana University School of Medicine (updated 2021) (2022)."},{"key":"e_1_2_11_23_1","unstructured":"Agency E.M.Inclusion\/Exclusion criteria for the \u201cImportant Medical Events\u201d list(2016)."},{"key":"e_1_2_11_24_1","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkz389"},{"key":"e_1_2_11_25_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btw343"},{"key":"e_1_2_11_26_1","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkh061"},{"key":"e_1_2_11_27_1","unstructured":"Phan L.N.et al.Scifive: a text\u2010to\u2010text transformer model for biomedical literature.arXiv preprint arXiv:210603598(2021)."},{"key":"e_1_2_11_28_1","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkx1037"},{"key":"e_1_2_11_29_1","doi-asserted-by":"publisher","DOI":"10.1136\/amiajnl-2011-000376"},{"key":"e_1_2_11_30_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2014.02.003"},{"key":"e_1_2_11_31_1","doi-asserted-by":"crossref","first-page":"668","DOI":"10.1056\/NEJMsr1809937","article-title":"The \u201cAll of Us\u201d research program","volume":"381","author":"Investigators, A.o.U.R.P","year":"2019","journal-title":"N. Engl. J. Med."},{"key":"e_1_2_11_32_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.h1059"},{"key":"e_1_2_11_33_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.1047"},{"key":"e_1_2_11_34_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2288-9-56"},{"key":"e_1_2_11_35_1","doi-asserted-by":"publisher","DOI":"10.1080\/02763869.2014.957093"},{"key":"e_1_2_11_36_1","doi-asserted-by":"publisher","DOI":"10.1111\/jth.13614"},{"key":"e_1_2_11_37_1","doi-asserted-by":"publisher","DOI":"10.2146\/ajhp060415"},{"key":"e_1_2_11_38_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00204-018-2244-6"},{"key":"e_1_2_11_39_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(00)03409-7"},{"key":"e_1_2_11_40_1","doi-asserted-by":"publisher","DOI":"10.3109\/15376516.2015.1026008"},{"key":"e_1_2_11_41_1","doi-asserted-by":"publisher","DOI":"10.1177\/2049463712438493"},{"key":"e_1_2_11_42_1","doi-asserted-by":"publisher","DOI":"10.1038\/sj.bjp.0707253"},{"key":"e_1_2_11_43_1","doi-asserted-by":"publisher","DOI":"10.1093\/bja\/aei210"},{"key":"e_1_2_11_44_1","doi-asserted-by":"publisher","DOI":"10.1136\/pmj.77.905.191"},{"key":"e_1_2_11_45_1","doi-asserted-by":"publisher","DOI":"10.2174\/1381612824666180123110042"},{"key":"e_1_2_11_46_1","doi-asserted-by":"publisher","DOI":"10.1016\/0140-6736(91)90245-K"},{"key":"e_1_2_11_47_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0270-9295(03)00090-1"},{"key":"e_1_2_11_48_1","doi-asserted-by":"publisher","DOI":"10.1002\/jcph.743"},{"key":"e_1_2_11_49_1","volume-title":"Medical Genetics Summaries","author":"Dean L.","year":"2017"},{"key":"e_1_2_11_50_1","doi-asserted-by":"publisher","DOI":"10.1111\/cts.13296"}],"container-title":["Clinical Pharmacology &amp; Therapeutics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/ascpt.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/cpt.3500","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,11]],"date-time":"2025-08-11T09:21:11Z","timestamp":1754904071000},"score":1,"resource":{"primary":{"URL":"https:\/\/ascpt.onlinelibrary.wiley.com\/doi\/10.1002\/cpt.3500"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,25]]},"references-count":50,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,4]]}},"alternative-id":["10.1002\/cpt.3500"],"URL":"https:\/\/doi.org\/10.1002\/cpt.3500","archive":["Portico"],"relation":{},"ISSN":["0009-9236","1532-6535"],"issn-type":[{"value":"0009-9236","type":"print"},{"value":"1532-6535","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,25]]},"assertion":[{"value":"2024-07-09","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-11-04","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-11-25","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}