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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Despite substantial premarket efforts, a significant portion of approved drugs has been withdrawn from the market for safety reasons.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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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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description | Despite substantial premarket efforts, a significant portion of approved drugs has been withdrawn from the market for safety reasons.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 Both withdrawn (n = 154) and precautionary (Beers criteria (n = 90), and US FDA pharmacogenomic biomarkers (n = 96)) drugs showed significantly lower genomic deleteriousness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. |
format | Online Article Text |
id | pubmed-5045182 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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