Pharmacogenetics in drug development: Regulatory and clinical considerations

LightTyper platform for high-throughput clinical genotyping

DNA sequence variations due to single nucleotide changes or polymorphisms (SNPs) have demonstrated an association with certain diseases as causative agents or surrogate biomarkers. Identification and genotyping of SNPs requires reliable and robust technologies. Multiple genotyping platforms are available to detect SNPs. Although many of these platforms meet the requirements of the research environment, technologies have also emerged for high-throughput clinical genotyping as well. The LightTyper is one such platform, providing SNP identification by employing melting curve analysis of fluorescently labeled probes. The LightTyper has been used to identify SNPs associated with myocardial infarction, developing and validating assays for approximately 100 SNPs in 30 candidate genes. The LightTyper is also amenable to the use of assays already developed for the LightCycler, which is widely used in clinical laboratories. The initial experience presented here suggests the potential use of the LightTyper for high-throughput clinical genotyping.

Use of pairwise marker combination and recursive partitioning in a pharmacogenetic genome-wide scan

The objective of pharmacogenetic research is to identify a genetic marker, or a set of genetic markers, that can predict how a given person will respond to a given medicine. To search for such marker combinations that are predictive of adverse drug events, we have developed and applied two complementary methods to a pharmacogenetic study of the hypersensitivity reaction (HSR) associated with treatment with abacavir, a medicine that is used to treat HIV-infected patients. Our results show that both of these methods can be used to uncover potentially useful predictive marker combinations. The pairwise marker combination method yielded a collection of marker pairs that featured a spectrum of sensitivities and specificities. Recursive partitioning results led to the genetic delineation of multiple risk categories, including those with extremely high and extremely low risk of HSR. These methods can be readily applied in pharmacogenetic candidate gene studies as well as in genome-wide scans.

Genetic diversity and new therapeutic concepts

The differences in medicinal drug responses among individuals had been known for quite some time. Some patients exhibit a life-threatening adverse reaction while others fail to show an expected therapeutic effect. Intermediate responses between the above two extreme cases are also known. In fact, it has been recently reported that approximately 100,000 deaths and more than 2 million hospitalizations annually in the United States are due to properly prescribed medications. This interindividual variability could be due in part to genetically determined characteristics of target genes or drug metabolizing enzymes. This has now been substantiated by a variety of studies. We know that "one size fits all" is not correct. Therefore, the application of pharmacogenetic concepts to clinical practice is an excellent goal in the postgenomic era. The successful completion of the human genome project provided necessary molecular tools, such as high-throughput SNP genotyping, HapMap, and microarray, that can be applied to develop proper therapeutic options for individuals. Recently, there have been considerable scientific, corporate, and policy interest in pharmacotherapy. However, identification of causal variations in a target gene is only a starting point, and the progress in this rapidly developing field is slower than expected. One major drawback could be due to the multigene determinant of drug response that requires a genome-wide screening. Additionally, application of pharmacogenetic knowledge into clinical practice requires a high level of accuracy, precision (risk/benefit ratio), and strict regulations. This is because the pharmacogenetic approach raises several ethical, moral, and legal questions. It is also necessary that both health professionals and the general public must be urgently educated. Despite these limitations, translation of pharmacogenomic data into clinical practice would certainly provide better opportunities to increase the safety and efficacy of medicine in the future.