THE ROLE OF STATISTICS IN PHARMACOGENOMICS(Keynote Papers)

The sequence of the human genome released earlier this year is a significant scientific achievement. The goal of pharmacogenomics is the application of genetic information and technology to develop better therapeutics or to guide the use of pharmaceuticals in the treatment or prevention of disease. Statistical theory and probability will play an expanded role in interpreting genetic information through the development of new analytical methodology and the novel application of traditional statistical theory. Examples in gene mapping and microarray expression analysis will be used to broadly illustrate the essential role of statistical theory in pharmacogenomics research. Specific gene mapping methodologies discussed include linkage analysis, linkage disequilibrium studies, and haplotype analysis. Application of statistical theory to gene chip experiments to obtain high-quality data including experimental design, minimizing variability, and well-controlled verification strategies and applications to identify gene expression differences between experimental groups will be reviewed. The combination of statistical applications and genomic technologies is key to understanding the genetic differences that identify patients susceptible to disease, stratify patients by clinical outcome, indicate treatment response, or predict adverse event occurrences.