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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...

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Autores principales: Maciejewski, Mateusz, Lounkine, Eugen, Whitebread, Steven, Farmer, Pierre, DuMouchel, William, Shoichet, Brian K, Urban, Laszlo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2017
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
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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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