Format

Send to

Choose Destination
CPT Pharmacometrics Syst Pharmacol. 2015 Jul;4(7):415-25. doi: 10.1002/psp4.51. Epub 2015 Jun 18.

IDEA: Integrated Drug Expression Analysis-Integration of Gene Expression and Clinical Data for the Identification of Therapeutic Candidates.

Author information

1
Department of Genetics, Geisel School of Medicine at Dartmouth Hanover, New Hampshire, USA.
2
Department of Genetics, Geisel School of Medicine at Dartmouth Hanover, New Hampshire, USA ; Institute for Quantitative Biomedical Sciences, Geisel School of Medicine at Dartmouth Lebanon, New Hampshire, USA ; Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth Lebanon, New Hampshire, USA.

Abstract

Cancer drug discovery is an involved process spanning efforts from several fields of study and typically requires years of research and development. However, the advent of high-throughput genomic technologies has allowed for the use of in silico, genomics-based methods to screen drug libraries and accelerate drug discovery. Here we present a novel approach to computationally identify drug candidates for the treatment of breast cancer. In particular, we developed a Drug Regulatory Score similarity metric to evaluate gene expression profile similarity, in the context of drug treatment, and incorporated time-to-event patient survival information to develop an integrated analysis pipeline: Integrated Drug Expression Analysis (IDEA). We were able to predict drug candidates that have been known and those that have not been known in the literature to exhibit anticancer effects. Overall, our method enables quick preclinical screening of drug candidates for breast cancer and other diseases by using the most important indicator of drug efficacy: survival.

Supplemental Content

Full text links

Icon for Wiley Icon for PubMed Central
Loading ...
Support Center