Session 4: Toxicogenomics and heterogeneous data
Shionogi & Co. Ltd., Japan
ABSTRACT CONTENT / DETAILS:
Toxicogenomics is an effective mean for investigating adverse effects and mode-of-action of compounds based on microarray techniques for mRNA.
Predictive model, using transcript signatures and machine learning techniques, enables the efficient selection of drug candidates at an early stage of drug development, resulting in a significant reduction in the time and cost associated with development of new molecular entities.
In Japan, the Toxicogenomics Project (TGP; Uehara et al, 2010) has constructed a large-scale database called TG-GATEs. The open accessible version, Open TG-GATEs, is available for free public download.
In recent years, biomarkers to predict for several toxicity endpoints (e.g. nongenotoxic hepatocarcinogenicity, nephrotoxicity) have been successfully identified by using this database.
Furthermore, development of other high throughput techniques, such as microarrays for microRNA, NGS, metabolomics, leads to the emergence of promising new fields of toxicogenomics.
In this session, we will share our experiences on exploration of biomarkers and challenges in bioinformatics analysis in dealing with integrated 'omics' data.