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Systematic drug repositioning through mining adverse event data in ClinicalTrials.gov

Drug repositioning (i.e., drug repurposing) is the process of discovering new uses for marketed drugs. Historically, such discoveries were serendipitous. However, the rapid growth in electronic clinical data and text mining tools makes it feasible to systematically identify drugs with the potential...

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Detalles Bibliográficos
Autores principales: Su, Eric Wen, Sanger, Todd M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5366063/
https://www.ncbi.nlm.nih.gov/pubmed/28348935
http://dx.doi.org/10.7717/peerj.3154
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author Su, Eric Wen
Sanger, Todd M.
author_facet Su, Eric Wen
Sanger, Todd M.
author_sort Su, Eric Wen
collection PubMed
description Drug repositioning (i.e., drug repurposing) is the process of discovering new uses for marketed drugs. Historically, such discoveries were serendipitous. However, the rapid growth in electronic clinical data and text mining tools makes it feasible to systematically identify drugs with the potential to be repurposed. Described here is a novel method of drug repositioning by mining ClinicalTrials.gov. The text mining tools I2E (Linguamatics) and PolyAnalyst (Megaputer) were utilized. An I2E query extracts “Serious Adverse Events” (SAE) data from randomized trials in ClinicalTrials.gov. Through a statistical algorithm, a PolyAnalyst workflow ranks the drugs where the treatment arm has fewer predefined SAEs than the control arm, indicating that potentially the drug is reducing the level of SAE. Hypotheses could then be generated for the new use of these drugs based on the predefined SAE that is indicative of disease (for example, cancer).
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spelling pubmed-53660632017-03-27 Systematic drug repositioning through mining adverse event data in ClinicalTrials.gov Su, Eric Wen Sanger, Todd M. PeerJ Bioinformatics Drug repositioning (i.e., drug repurposing) is the process of discovering new uses for marketed drugs. Historically, such discoveries were serendipitous. However, the rapid growth in electronic clinical data and text mining tools makes it feasible to systematically identify drugs with the potential to be repurposed. Described here is a novel method of drug repositioning by mining ClinicalTrials.gov. The text mining tools I2E (Linguamatics) and PolyAnalyst (Megaputer) were utilized. An I2E query extracts “Serious Adverse Events” (SAE) data from randomized trials in ClinicalTrials.gov. Through a statistical algorithm, a PolyAnalyst workflow ranks the drugs where the treatment arm has fewer predefined SAEs than the control arm, indicating that potentially the drug is reducing the level of SAE. Hypotheses could then be generated for the new use of these drugs based on the predefined SAE that is indicative of disease (for example, cancer). PeerJ Inc. 2017-03-23 /pmc/articles/PMC5366063/ /pubmed/28348935 http://dx.doi.org/10.7717/peerj.3154 Text en ©2017 Su and Sanger http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Su, Eric Wen
Sanger, Todd M.
Systematic drug repositioning through mining adverse event data in ClinicalTrials.gov
title Systematic drug repositioning through mining adverse event data in ClinicalTrials.gov
title_full Systematic drug repositioning through mining adverse event data in ClinicalTrials.gov
title_fullStr Systematic drug repositioning through mining adverse event data in ClinicalTrials.gov
title_full_unstemmed Systematic drug repositioning through mining adverse event data in ClinicalTrials.gov
title_short Systematic drug repositioning through mining adverse event data in ClinicalTrials.gov
title_sort systematic drug repositioning through mining adverse event data in clinicaltrials.gov
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5366063/
https://www.ncbi.nlm.nih.gov/pubmed/28348935
http://dx.doi.org/10.7717/peerj.3154
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