Pharmacogenomics in the clinic
By Mary V. Relling, William E. Evans. Nature, 2015
790 citations recorded by the source corpus.
After decades of discovery, inherited variations have been identified in approximately 20 genes that affect about 80 medications and are actionable in the clinic. And some somatically acquired genetic variants direct the choice of 'targeted' anticancer drugs for individual patients. Current efforts that focus on the processes required to appropriately act on pharmacogenomic variability in the clinic are moving away from discovery and towards implementation of an evidenced-based strategy for improving the use of medications, thereby providing a cornerstone for precision medicine.
Subfields: Cancer Research, Molecular Biology, Pharmacology
View Paper: https://www.semanticscholar.org/paper/7cc1e68450c3aedbf3aec8bdfed8df950ffc780b
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- M. Scott
- G. Nelson
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- J. Bakkum-Gamez
- E. Kalogera
- C. Gillis
- G. Glaser
Citations in the corpus
- Pharmacogenomics of GPCR Drug Targets (2018, neutral): “Until recently, drug prescriptions had not been guided by pharmacogenomics, due to the cost and complexity needed to identify, analyze, and interpret genetic variation data (Relling and Evans, 2015).”
- Guidelines for perioperative care in gynecologic/oncology: Enhanced Recovery After Surgery (ERAS) Society recommendations—2019 update (2019, background): “195 This information has emerging importance in post-surgical opioid administration, with one study showing a 50% reduction in opioid use as well as excellent analgesia using pharmacogenetic-guided input.”
- Large-scale whole-genome sequencing of three diverse Asian populations in Singapore (2018, neutral): “, 17 2015), optimization of medication usage (Relling and Evans, 2015), drug development (Nelson et al.”
- Deep learning in cancer diagnosis, prognosis and treatment selection (2021, background): “Lastly, pharmacogenomics, to predict drug responses and the mechanisms of action using genomic characteristics, is an important and exciting area in precision oncology where DL methods have significant potential [154].”