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Annals of Translational Medicine
Article . 2016 . Peer-reviewed
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Companion diagnostics—a tool to improve pharmacotherapy

Authors: Jørgensen, Jan Trøst; Hersom, Maria;

Companion diagnostics—a tool to improve pharmacotherapy

Abstract

The variability of pharmacotherapy can be of a significant magnitude, and the main reason for this is often diseases heterogeneity. Patients who have similar diagnoses very often respond differently to the same pharmacological intervention, with great variability in both efficacy and safety outcome. Despite having discussed personalized medicine for more than a decade, we still see that most drug prescriptions for severe chronic diseases are largely based on 'trial and error' and not on solid biomarker data. However, with the advance of molecular diagnostics and a subsequent increased understanding of disease mechanisms, things are slowly changing. Within the last few years, we have seen an increasing number of predictive biomarker assays being developed to guide the use of targeted cancer drugs. This type of assay is called companion diagnostics and is developed in parallel to the drug using the drug-diagnostic co-development model. The development of companion diagnostics is a relatively new discipline and in this review, different aspects will be discussed including clinical and regulatory issues. Furthermore, examples of drugs, such as the ALK and PD-1/PD-L1 inhibitors, that have been approved recently together with a companion or complimentary diagnostic will be given.

Country
Denmark
Keywords

PD-L1, ALK, Companion diagnostics, EGFR, HER2, Complementary diagnostics, Personalized medicine

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    selected citations
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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).
    64
    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 10%
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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!
64
Top 10%
Top 10%
Top 10%
gold