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Pharmacogenomic considerations in opioid analgesia.

Overview of attention for article published in Pharmacogenomics and Personalized Medicine, August 2012
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86 Mendeley
Title
Pharmacogenomic considerations in opioid analgesia.
Published in
Pharmacogenomics and Personalized Medicine, August 2012
DOI 10.2147/pgpm.s23422
Pubmed ID
Authors

Ruth Landau, Pascal H Vuilleumier, Ulrike M Stamer

Abstract

Translating pharmacogenetics to clinical practice has been particularly challenging in the context of pain, due to the complexity of this multifaceted phenotype and the overall subjective nature of pain perception and response to analgesia. Overall, numerous genes involved with the pharmacokinetics and dynamics of opioids response are candidate genes in the context of opioid analgesia. The clinical relevance of CYP2D6 genotyping to predict analgesic outcomes is still relatively unknown; the two extremes in CYP2D6 genotype (ultrarapid and poor metabolism) seem to predict pain response and/or adverse effects. Overall, the level of evidence linking genetic variability (CYP2D6 and CYP3A4) to oxycodone response and phenotype (altered biotransformation of oxycodone into oxymorphone and overall clearance of oxycodone and oxymorphone) is strong; however, there has been no randomized clinical trial on the benefits of genetic testing prior to oxycodone therapy. On the other hand, predicting the analgesic response to morphine based on pharmacogenetic testing is more complex; though there was hope that simple genetic testing would allow tailoring morphine doses to provide optimal analgesia, this is unlikely to occur. A variety of polymorphisms clearly influence pain perception and behavior in response to pain. However, the response to analgesics also differs depending on the pain modality and the potential for repeated noxious stimuli, the opioid prescribed, and even its route of administration.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
Netherlands 1 1%
Portugal 1 1%
Unknown 81 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 16%
Student > Ph. D. Student 11 13%
Student > Postgraduate 11 13%
Student > Master 10 12%
Student > Bachelor 9 10%
Other 21 24%
Unknown 10 12%
Readers by discipline Count As %
Medicine and Dentistry 29 34%
Agricultural and Biological Sciences 12 14%
Pharmacology, Toxicology and Pharmaceutical Science 10 12%
Biochemistry, Genetics and Molecular Biology 8 9%
Psychology 5 6%
Other 11 13%
Unknown 11 13%