Best practices for assessing toxicity during drug discovery process

Ingenuity® Systems, the leading provider of information solutions for life science researchers, today announced the release of the white paper, "Best Practices for Assessing Toxicity throughout the Drug Discovery Process: Toxicogenomics."  The white paper is based on input from industry experts and shows how multidisciplinary toxicology teams in drug discovery can leverage toxicogenomics and IPA® for improved predictive toxicology and mechanistic toxicity analysis.  

Understanding the basic biological mechanisms related to toxicity is a top priority for both traditional toxicologists and other researchers whose understanding of toxicity can inform decision making at all phases of a research project.  By complementing a traditional toxicological approach with toxicogenomics, researchers get a better interpretation of large, complex amounts of data with lots of variables, can detect toxicity earlier in drug discovery for faster project decisions, and – most significantly – can better understand molecular level events that underlie toxicity.

Dr. Phil Hewitt, Head of Toxicogenomics at Merck-Serono, believes that gene expression profiling has the greatest potential for improving mechanistic insight and therefore adds a high value to Tox and Safety studies.  According to Dr. Hewitt, "Implementing toxicogenomics with traditional tox approaches will help researchers detect toxicity earlier.  Assessing toxicity is not always clear, and incorporating another source of information can only complement traditional animal studies."

IPA-Tox®, a capability within IPA, is the industry leading toxicogenomics software solution for analyzing this type of expression data to obtain actionable insights. With IPA-Tox, scientists can analyze large scale datasets (genomic and proteomic datasets, dose response datasets, etc.) in order to identify the key functions and pathways that are activated or disrupted upon treatment with a compound. IPA-Tox also links expression data to clinical pathology endpoints for mechanistic hypotheses generation and identification of mechanism of toxicity.