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A thorough, standardized set of indications and symptoms is needed to identify these confounders in such datasets for drug research and safety assessment. The aim of this study is to create a comprehensive list of drug-indication associations and disease-symptom associations using multiple resources, including existing databases and natural language processing.<\/jats:p>\n<\/jats:sec><jats:sec>\n<jats:title>Methods<\/jats:title>\n<jats:p>Drug indications for drugs approved in the USA were extracted from two databases, RxNorm and Side Effect Resource (SIDER). Symptoms for these indications were extracted from MedlinePlus and using natural language processing from PubMed abstracts.<\/jats:p>\n<\/jats:sec><jats:sec>\n<jats:title>Results<\/jats:title>\n<jats:p>A total of 1361 unique drugs, 1656 unique indications, and 2201 unique symptoms were extracted from a wide variety of MedDRA System Organ Classes. Text-mining precision was maximized at 0.65 by examining Term Frequency Inverse Document Frequency (TF-IDF) scores of the disease-symptom associations.<\/jats:p>\n<\/jats:sec><jats:sec>\n<jats:title>Conclusion<\/jats:title>\n<jats:p>The drug-indication associations and disease-symptom associations collected in this study may be useful in identifying confounders in other datasets, such as safety reports. With further refinement and additional drugs, indications, and symptoms, this dataset may become a quality resource for disease symptoms.<\/jats:p>\n<\/jats:sec>","DOI":"10.1007\/s00228-020-02898-w","type":"journal-article","created":{"date-parts":[[2020,6,3]],"date-time":"2020-06-03T15:56:23Z","timestamp":1591199783000},"page":"1291-1299","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Aggregation and analysis of indication-symptom relationships for drugs approved in the USA"],"prefix":"10.1007","volume":"76","author":[{"given":"Ananth","family":"Punyala","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rachana","family":"Lankapalli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Diane","family":"Hindman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5487-5692","authenticated-orcid":false,"given":"Rebecca","family":"Racz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,6,3]]},"reference":[{"issue":"7","key":"2898_CR1","doi-asserted-by":"publisher","first-page":"682","DOI":"10.18553\/jmcp.2018.24.7.682","volume":"24","author":"KB Sonawane","year":"2018","unstructured":"Sonawane KB, Cheng N, Hansen RA (2018) Serious adverse drug events reported to the FDA: analysis of the FDA Adverse Event Reporting System 2006-2014 database. 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All other authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article reflects the views of the authors and should not be construed to represent the views or policies of the FDA. The mention of commercial products, their sources, or their use in connection with material reported herein is not to be construed as either an actual or implied endorsement of such products by the Department of Health and Human Services. FDA has a contract with Linguamatics for use of the I2E OnDemand and Enterprise versions of the software.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclaimer"}}]}}