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Reverse translation of adverse event reports paves the way for de-risking preclinical off-targets
The Food and Drug Administration Adverse Event Reporting System (FAERS) remains the primary source for post-marketing pharmacovigilance. The system is largely un-curated, unstandardized, and lacks a method for linking drugs to the chemical structures of their active ingredients, increasing noise and...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5548487/ https://www.ncbi.nlm.nih.gov/pubmed/28786378 http://dx.doi.org/10.7554/eLife.25818 |
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author | Maciejewski, Mateusz Lounkine, Eugen Whitebread, Steven Farmer, Pierre DuMouchel, William Shoichet, Brian K Urban, Laszlo |
author_facet | Maciejewski, Mateusz Lounkine, Eugen Whitebread, Steven Farmer, Pierre DuMouchel, William Shoichet, Brian K Urban, Laszlo |
author_sort | Maciejewski, Mateusz |
collection | PubMed |
description | The Food and Drug Administration Adverse Event Reporting System (FAERS) remains the primary source for post-marketing pharmacovigilance. The system is largely un-curated, unstandardized, and lacks a method for linking drugs to the chemical structures of their active ingredients, increasing noise and artefactual trends. To address these problems, we mapped drugs to their ingredients and used natural language processing to classify and correlate drug events. Our analysis exposed key idiosyncrasies in FAERS, for example reports of thalidomide causing a deadly ADR when used against myeloma, a likely result of the disease itself; multiplications of the same report, unjustifiably increasing its importance; correlation of reported ADRs with public events, regulatory announcements, and with publications. Comparing the pharmacological, pharmacokinetic, and clinical ADR profiles of methylphenidate, aripiprazole, and risperidone, and of kinase drugs targeting the VEGF receptor, demonstrates how underlying molecular mechanisms can emerge from ADR co-analysis. The precautions and methods we describe may enable investigators to avoid confounding chemistry-based associations and reporting biases in FAERS, and illustrate how comparative analysis of ADRs can reveal underlying mechanisms. DOI: http://dx.doi.org/10.7554/eLife.25818.001 |
format | Online Article Text |
id | pubmed-5548487 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-55484872017-08-09 Reverse translation of adverse event reports paves the way for de-risking preclinical off-targets Maciejewski, Mateusz Lounkine, Eugen Whitebread, Steven Farmer, Pierre DuMouchel, William Shoichet, Brian K Urban, Laszlo eLife Human Biology and Medicine The Food and Drug Administration Adverse Event Reporting System (FAERS) remains the primary source for post-marketing pharmacovigilance. The system is largely un-curated, unstandardized, and lacks a method for linking drugs to the chemical structures of their active ingredients, increasing noise and artefactual trends. To address these problems, we mapped drugs to their ingredients and used natural language processing to classify and correlate drug events. Our analysis exposed key idiosyncrasies in FAERS, for example reports of thalidomide causing a deadly ADR when used against myeloma, a likely result of the disease itself; multiplications of the same report, unjustifiably increasing its importance; correlation of reported ADRs with public events, regulatory announcements, and with publications. Comparing the pharmacological, pharmacokinetic, and clinical ADR profiles of methylphenidate, aripiprazole, and risperidone, and of kinase drugs targeting the VEGF receptor, demonstrates how underlying molecular mechanisms can emerge from ADR co-analysis. The precautions and methods we describe may enable investigators to avoid confounding chemistry-based associations and reporting biases in FAERS, and illustrate how comparative analysis of ADRs can reveal underlying mechanisms. DOI: http://dx.doi.org/10.7554/eLife.25818.001 eLife Sciences Publications, Ltd 2017-08-08 /pmc/articles/PMC5548487/ /pubmed/28786378 http://dx.doi.org/10.7554/eLife.25818 Text en © 2017, Maciejewski et al http://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Human Biology and Medicine Maciejewski, Mateusz Lounkine, Eugen Whitebread, Steven Farmer, Pierre DuMouchel, William Shoichet, Brian K Urban, Laszlo Reverse translation of adverse event reports paves the way for de-risking preclinical off-targets |
title | Reverse translation of adverse event reports paves the way for de-risking preclinical off-targets |
title_full | Reverse translation of adverse event reports paves the way for de-risking preclinical off-targets |
title_fullStr | Reverse translation of adverse event reports paves the way for de-risking preclinical off-targets |
title_full_unstemmed | Reverse translation of adverse event reports paves the way for de-risking preclinical off-targets |
title_short | Reverse translation of adverse event reports paves the way for de-risking preclinical off-targets |
title_sort | reverse translation of adverse event reports paves the way for de-risking preclinical off-targets |
topic | Human Biology and Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5548487/ https://www.ncbi.nlm.nih.gov/pubmed/28786378 http://dx.doi.org/10.7554/eLife.25818 |
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