Computational and Mathematical Methods in Medicine
Volume 2013 (2013), Article ID 865980, 9 pages
http://dx.doi.org/10.1155/2013/865980
Review Article

Genomic Biomarkers for Personalized Medicine: Development and Validation in Clinical Studies

Department of Data Science, The Institute of Statistical Mathematics, 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan

Received 26 January 2013; Accepted 22 March 2013

Academic Editor: Chuhsing Kate Hsiao

Copyright © 2013 Shigeyuki Matsui. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The establishment of high-throughput technologies has brought substantial advances to our understanding of the biology of many diseases at the molecular level and increasing expectations on the development of innovative molecularly targeted treatments and molecular biomarkers or diagnostic tests in the context of clinical studies. In this review article, we position the two critical statistical analyses of high-dimensional genomic data, gene screening and prediction, in the framework of development and validation of genomic biomarkers or signatures, through taking into consideration the possible different strategies for developing genomic signatures. A wide variety of biomarker-based clinical trial designs to assess clinical utility of a biomarker or a new treatment with a companion biomarker are also discussed.