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Genome Sequence Variability Predicts Drug Precautions and Withdrawals from the Market

Despite substantial premarket efforts, a significant portion of approved drugs has been withdrawn from the market for safety reasons. The deleterious impact of nonsynonymous substitutions predicted by the SIFT algorithm on structure and function of drug-related proteins was evaluated for 2504 person...

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Autores principales: Lee, Kye Hwa, Baik, Su Youn, Lee, Soo Youn, Park, Chan Hee, Park, Paul J., Kim, Ju Han
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5045182/
https://www.ncbi.nlm.nih.gov/pubmed/27690231
http://dx.doi.org/10.1371/journal.pone.0162135
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author Lee, Kye Hwa
Baik, Su Youn
Lee, Soo Youn
Park, Chan Hee
Park, Paul J.
Kim, Ju Han
author_facet Lee, Kye Hwa
Baik, Su Youn
Lee, Soo Youn
Park, Chan Hee
Park, Paul J.
Kim, Ju Han
author_sort Lee, Kye Hwa
collection PubMed
description Despite substantial premarket efforts, a significant portion of approved drugs has been withdrawn from the market for safety reasons. The deleterious impact of nonsynonymous substitutions predicted by the SIFT algorithm on structure and function of drug-related proteins was evaluated for 2504 personal genomes. Both withdrawn (n = 154) and precautionary (Beers criteria (n = 90), and US FDA pharmacogenomic biomarkers (n = 96)) drugs showed significantly lower genomic deleteriousness scores (P < 0.001) compared to others (n = 752). Furthermore, the rates of drug withdrawals and precautions correlated significantly with the deleteriousness scores of the drugs (P < 0.01); this trend was confirmed for all drugs included in the withdrawal and precaution lists by the United Nations, European Medicines Agency, DrugBank, Beers criteria, and US FDA. Our findings suggest that the person-to-person genome sequence variability is a strong independent predictor of drug withdrawals and precautions. We propose novel measures of drug safety based on personal genome sequence analysis.
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spelling pubmed-50451822016-10-27 Genome Sequence Variability Predicts Drug Precautions and Withdrawals from the Market Lee, Kye Hwa Baik, Su Youn Lee, Soo Youn Park, Chan Hee Park, Paul J. Kim, Ju Han PLoS One Research Article Despite substantial premarket efforts, a significant portion of approved drugs has been withdrawn from the market for safety reasons. The deleterious impact of nonsynonymous substitutions predicted by the SIFT algorithm on structure and function of drug-related proteins was evaluated for 2504 personal genomes. Both withdrawn (n = 154) and precautionary (Beers criteria (n = 90), and US FDA pharmacogenomic biomarkers (n = 96)) drugs showed significantly lower genomic deleteriousness scores (P < 0.001) compared to others (n = 752). Furthermore, the rates of drug withdrawals and precautions correlated significantly with the deleteriousness scores of the drugs (P < 0.01); this trend was confirmed for all drugs included in the withdrawal and precaution lists by the United Nations, European Medicines Agency, DrugBank, Beers criteria, and US FDA. Our findings suggest that the person-to-person genome sequence variability is a strong independent predictor of drug withdrawals and precautions. We propose novel measures of drug safety based on personal genome sequence analysis. Public Library of Science 2016-09-30 /pmc/articles/PMC5045182/ /pubmed/27690231 http://dx.doi.org/10.1371/journal.pone.0162135 Text en © 2016 Lee et al 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, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Lee, Kye Hwa
Baik, Su Youn
Lee, Soo Youn
Park, Chan Hee
Park, Paul J.
Kim, Ju Han
Genome Sequence Variability Predicts Drug Precautions and Withdrawals from the Market
title Genome Sequence Variability Predicts Drug Precautions and Withdrawals from the Market
title_full Genome Sequence Variability Predicts Drug Precautions and Withdrawals from the Market
title_fullStr Genome Sequence Variability Predicts Drug Precautions and Withdrawals from the Market
title_full_unstemmed Genome Sequence Variability Predicts Drug Precautions and Withdrawals from the Market
title_short Genome Sequence Variability Predicts Drug Precautions and Withdrawals from the Market
title_sort genome sequence variability predicts drug precautions and withdrawals from the market
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5045182/
https://www.ncbi.nlm.nih.gov/pubmed/27690231
http://dx.doi.org/10.1371/journal.pone.0162135
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