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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Trends in Pharmacolo...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Trends in Pharmacological Sciences
Article . 2017 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Genomics of Adverse Drug Reactions

Authors: Alfirevic, Ana; Pirmohamed, Munir;

Genomics of Adverse Drug Reactions

Abstract

Adverse drug reactions (ADRs) are common, are associated with morbidity and mortality, and are costly to healthcare systems. Genomic factors predispose to ADRs, but these vary depending on the drug, patient, and disease. Genomic testing can not only help to predict and prevent ADRs but can also be used in other ways (diagnosis, closer monitoring of those at risk, pre-emptive genotyping, and understanding of mechanism), all of which will be important in the future to improve the benefit-risk ratio of drugs. In the era of precision medicine, such genomic data will need to be integrated with other forms of data to develop a comprehensive and integrated approach to improve responses to medicines used in patients.

Related Organizations
Keywords

Drug-Related Side Effects and Adverse Reactions, Genotype, Humans, Genetic Testing, Genomics, Precision Medicine

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    54
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
54
Top 10%
Top 10%
Top 1%
Green