Statistical techniques to construct assays for identifying likely responders to a treatment under evaluation from cell line genomic data.

ABSTRACT:

Background

Developing the right drugs for the right patients has become a mantra of drug development. In practice, it is very difficult to identify subsets of patients who will respond to a drug under evaluation. Most of the time, no single diagnostic will be available, and more complex decision rules will be required to define a sensitive population, using, for instance, mRNA expression, protein expression or DNA copy number. Moreover, diagnostic development will often begin with in-vitro cell-line data and a high-dimensional exploratory platform, only later to be transferred to a diagnostic assay for use with patient samples. In this manuscript, we present a novel approach to developing robust genomic predictors that are not only capable of generalizing from in-vitro to patient,

SUBMITTER: Huang EP 

PROVIDER: S-EPMC2984428 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature