omation mbers - Society for Laboratory Automation and Screening

11:30 am Thursday, February 5 Clinical – Arrays Room C1
Richard Hockett
Eli Lilly and Company
Lilly Corporate Center
Indianapolis, Indiana 46285
hockett@lilly.com
Clinical Validation of the Affymetrix Microarray and the Challenges Faced
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Co-Author(s)
Carmen Dumaual, Crystal Dotson,
Sandra Kirkwood, Mark Farmen
The use of microarray technology has resulted in a huge number of expression studies on human tissue.
Identification of genes which better classify tumors, or even predict the likely response to therapy has been touted
as a means to improve clinical outcome. Before microarrays can become common clinical tools, this technology
must undergo a thorough validation and ultimately FDA review. We have begun to validate microarrays for use in
clinical drug development and will discuss the validation plan, review validation data, and describe the numerous
challenges faced during this exercise.
1:30 pm Thursday, February 5 Clinical – Pharmacogenomics Room C1
Audrey Papp
Ohio State University
5160 Graves Hall
333 W. 10th. Avenue
Columbus, Ohio 43210
papp.2@osu.edu
Potential Role of Pharmacogenomics in Reducing Risk of Adverse Reactions and
Optimizing Therapy
Co-Author(s)
Wolfgang Sadée
Numerous genes play a role in determining drug response in individual patients. Genetic variants may either affect
drug efficacy or adverse effects. Adverse affects are often associated with polymorphisms in genes encoding
metabolizing enzymes and transporters, or less frequently with drug receptors. On the other hand, drug efficacy
may depend upon genes that also function as susceptibility factors in disease. We focus on drug efficacy
in complex disorders, including coronary artery disease, CNS disorders, and cancer, each involving multiple
candidate genes. As a general approach we analyze genetic variations in multiple candidate genes in clinical
association studies. Multiple polymorphisms (mostly single nucleotide polymorphisms) per gene are measured
to determine the main haplotypes in a population, followed by functional analysis of mRNA processing, and
protein analysis as feasible. Haplotypes are either inferred by statistical methods, or are measured experimentally.
This approach requires high throughput genotyping of numerous polymorphisms in large patient and control
populations. In addition, quantitative analysis of alleles in DNA and mRNA is necessary. We present methods
capable of addressing these complex problems, and show select results on association of candidate gene
haplotypes with clinical phenotypes.
PODIUM ABSTRACTS