The discovery bodes well for the emerging field of pharmacogenomics, which many have hailed as the next step in the evolution of drug treatments. The use of pharmacogenomic information has the potential to increase drug efficacy, reduce side effects and improve treatment outcomes for patients.
Researchers from Roche, used this mouse genetic analysis method, which utilised a computational method for identifying factors that regulate the metabolism of warfarin, a widely used anticoagulant.
The scientists discovered this computational method could identify genetic variants within drug metabolising enzymes that contribute to different drug responses in mice and provide information about genes that are likely to play a role in human drug metabolism.
"This research and the computational method will help scientists and clinicians better understand the drugs they are developing, as well as the diseases they target," said Gary Peltz, head of Genetics and Genomics at Roche in California.
"It can also be used to identify genetic susceptibility factors affecting drug-induced toxicity. While the research is at an early stage, the next step is to analyse other drugs of clinical importance, including one that induces liver toxicity."
According to the authors, pharmacogenomic data can influence drug development and clinical practice and thus is essential that scientists develop effective strategies to identify genetic factors affecting the metabolism or response to current and future therapies.
One of the areas where pharmacogenomics will stamp its authority is oncology, where genetic factors are set to have more of an influencing factor when determining treatment outcome.
Current therapies of cancer have exhibited limited success with efficacy only in 20-40 per cent of cases. Moreover, penalties of administering optimal therapy that employ high doses of extremely toxic drugs is severe due to the associated side effects.
After the completion of Human Genome Project, the annotation of full complement of human genes and identification of novel cancer causing genes is expected to provide newer gene targets for development of new and better anti cancer drugs.
This is the ultimate aim of the pharmacogenomics related to cancer in this post genomic era and the goal may not be too far to attain predicted by the rapid rate of progress.
The findings are published this week in >Nature Biotechnology (Vol 24, No 5, 2006),