Abstract
Attrition of drug candidates during pre-clinical development due to toxicity, especially hepatotoxicity and nephrotoxicity, is an important and continuing problem in the pharmaceutical industry. The reasons for this trend may be multifactorial and there is a need to improve toxicity testing paradigms within the industry. Microarray technologies have the ability to generate massive amounts of gene expression information as an initial step to decipher the molecular mechanisms of toxicologic changes, i.e. toxicogenomics. In the context of the eTOX consortium, one of public private partnership within the framework of the European Innovative Medicines Inititative (IMI), we will discuss here how the integration and analysis of toxicogenomics data can help to understanding the mechanism of toxicity of a compound and so reduce the risk of late-stage failure in pharmaceutical development.
Highlights
Status on Toxicogenomics StudiesThe current cost to bring a drug candidate to market is estimated to US $1.8 billion, with an average success rate of 8% [1]
Attrition of drug candidates during pre-clinical development due to toxicity, especially hepatotoxicity and nephrotoxicity, is an important and continuing problem in the pharmaceutical industry
Since the advent of DNA microarray technology (15 years ago), the field of toxicology started to discuss the great potential of genome-wide expression profiling for toxicity testing: the promise is that the mechanism of action of a chemical at the cellular level, the risk of chemical toxicity, can be identified through the transcriptional activity of cells
Summary
The current cost to bring a drug candidate to market is estimated to US $1.8 billion, with an average success rate of 8% [1]. Since the advent of DNA microarray technology (15 years ago), the field of toxicology started to discuss the great potential of genome-wide expression profiling for toxicity testing: the promise is that the mechanism of action of a chemical at the cellular level, the risk of chemical toxicity, can be identified through the transcriptional activity of cells. Compounds inducing similar gene expression profiles to known model toxicants can be identified as putatively toxic based on the common mechanisms of response at the molecular level. To develop such kind of profiling, access to large and consistent toxicogenomic repositories in conjunction with toxicological outcomes are required. Within less specific contexts for merging microarray data co-expression of transcripts, giving indications about transcriptional networks in general, is mostly what can be achieved
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
