Single nucleotide polymorphisms (SNP) in genes encoding drug receptors, transporters, metabolizing enzymes or DNA repair genes are known to influence the toxicity and efficacy profile of drugs. While the transition of this information to DNA-based tests in order to improve drug selection, identify optimal dosing, maximize drug efficacy or minimize the risk of toxicity has been slow coming, recent advances in molecular biology have yielded new diagnostic assays, some of which have already been incorporated into therapeutic guidelines such as testing for Herceptin protein in breast cancer patients. Moreover, new high-throughput screening methods and data mining approaches have emerged that could revolutionalise the drug development process and reduce the risk of drug failure, while both lowering costs and delivering faster and better results. In this regard, the powerful coupling of linkage to ultra-high throughput genotyping, gene array or proteomics technology, together with innovative bioinformatics resources, provides a focused integrative strategy for pinpointing disease-causing genes that may generate validated drug targets and genes that are responsible for differential drug response. The new information generated has already sparked the initiation of novel strategies and diagnostic approaches in clinical development that are anticipated to ultimately lead to safer and more efficacious drugs.
Keywords: pharmacogenomics, linkage, association, single nucleotide polymorphism, microarray, drug response
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