Leveraging Omics Biomarker Data in Drug Development: With a GWAS Case Study
Biomarkers have proven powerful for target identification, understanding disease progression, drug safety and treatment responses in drug development. Recent development of omics technology has offered great opportunities for identifications of omics biomarkers at low cost. Although biomarkers have brought many promises to drug development, steep challenges arise due to high dimensionality of data, complexity of technology and lack of full understanding of biology. In this article, the application of omics data in drug development will be reviewed. A genome wide association study (GWAS) will be presented.
KeywordsBiomarker Omics Simulation GWAS
- 4.Conover, W.J.: Practical Nonparametric Statistics. John Wiley Chichester, New York (1999)Google Scholar
- 13.Morgan, P., Van Der Graaf, P.H., Arrowsmith, J., Feltner, D.E., Drummond, K.S., Wegner, C.D., Street, S.D.: Can the flow of medicines be improved? Fundamental pharmacokinetic and pharmacological principles toward improving Phase II survival. Drug. Discov. Today 17, 419–424 (2012)CrossRefGoogle Scholar
- 19.TESARO’s Niraparib Significantly Improved Progression-Free Survival for Patients With Ovarian Cancer in Both Cohorts of the Phase 3 NOVA Trial (2016). http://ir.tesarobio.com/releasedetail.cfm?releaseid=977524
- 20.Thomas, D.W., Burns, J., Audette, J., Carroll, A., Dow-Hygelund, C., Hay, M.: Clinical Development Success Rates 2006–2015. June 2016. https://www.bio.org/sites/default/files/Clinical%20Development%20Success%20Rates%202006-2015%20-%20BIO,%20Biomedtracker,%20Amplion%202016.pdf
- 22.Wetterstrand, K.A.: DNA Sequencing Costs: Data from the NHGRI Genome Sequencing Program (GSP) (2016). www.genome.gov/sequencingcostsdata. Accessed 23 Dec 2016