Omics and Biomarker Study Design

Smarter Studies: Although a careful consideration of study design upfront is much cheaper than subsequent failed or suboptimal experiments, it is probably the most important neglected factor in numerous post-genomic studies.

"To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: He may be able to say what the experiment died of."

Sir Ronald Aylmer Fisher, ca 1938

"As new ‘-omics’ fields are explored to assess molecular markers for cancer, bias will increasingly be recognized as the most important ‘threat to validity’ that must be addressed in the design, conduct and interpretation of such research."

David F. Ransohoff, Nature Reviews Cancer 5 (2005) 142

Clear guidelines only begin to emerge, but there is a wealth of prior knowledge from traditional marker studies or when considering different omics fields jointly. Numerous guidelines and standards are given here as a help for considering the crucial factors for your own experiments. Regardless if developing companion diagnostics in a regulatory setting or performing an academic research study, issues like (pre-)analytical validity, randomisation, bias and confounding factors should be essential considerations before beginning any study.

Epidemiological Data

Contact

Dr. Juergen von Frese
Data Analysis Solutions
DA-Sol GmbH

Telephone: +49 8143 9977293
Fax: +49 8143 9977294
E-Mail: jvf@da-sol.com

Disclaimer

This page has been compiled for your convenience. The author reserves the right not to be responsible for the correctness, completeness or quality of the information provided and shall in no event be liable for any direct, indirect, incidental, consequential, or exemplary damages. The author is not responsible for any contents linked or referred to from his pages.