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Abstract
Utilization of pharmacogenomic information has the potential to significantly improve treatment outcome and markedly reduce the rate of attrition of drugs in clinical development. A major gap that limits our ability to utilize pharmacogenomic information in drug discovery, drug development or clinical practice is that we often do not know the genetic variants responsible for inter-individual differences in drug metabolism or drug response. We examine emerging genomic methods that can fill this gap; these methods can be used to generate new information about drug metabolism or mechanism of action, or to identify predictors of drug response. Although they have not yet had their full impact, a wider application of these emerging genomic technologies has the potential to significantly improve the safety of drugs, the quality of patient care and the efficiency of clinical drug development.
| ABBREVIATIONS | ||
| CYP: | = | cytochrome P450 |
| UGT, UDP: | = | glucuronosyltransferase |
| 1D: | = | one-dimensional |
| 2D NMR: | = | 2-dimensional nuclear magnetic resonance; |
| GWA: | = | genome-wide association |
| MEK: | = | Raf-mitogen activated/ERK |
| BRAF: | = | B-Raf proto-oncogene serine/threonine-protein kinase |