ICCVAM webinar reviews QSARs and read-across techniques
On January 26, NICEATM and EPA hosted the webinar Fundamentals of Using Quantitative Structure-Activity Relationship Models and Read-across Techniques in Predictive Toxicology . This ICCVAM Communities of Practice webinar provided overviews of different computational methods that use data about structure, properties, and toxicity from tested chemicals to make predictions about the characteristics of untested chemicals.
Alexander Tropsha, Ph.D., in his talk Fundamentals of QSAR Modeling: Basic Concepts and Applications, explained how quantitative structure-activity relationship (QSAR) models allow chemical compounds to be characterized mathematically, enabling statistical predictions about the properties of untested chemicals. Tropsha emphasized the importance of curation of chemical and biological databases, pointed out some common errors in QSAR development, and reviewed case studies in which QSARs were used to predict toxicities such as skin sensitization and liver toxicity. Tropsha is on the faculty of the University of North Carolina Eshelman School of Pharmacy in Chapel Hill.
Louis (Gino) Scarano, Ph.D., from the EPA Office of Pollution Prevention and Toxics, then discussed Application of QSAR Principles in the Regulatory Environment: The U.S. EPA New Chemicals Program. He reviewed how EPA uses quantitative tools and models to generate predictions about carcinogenicity, exposure potential, aquatic toxicity, and other toxic effects of new chemicals. These predictions are then used to make occupational risk assessments and identify where further testing might be needed.
ICCVAM Communities of Practice webinars are presented annually and present information on current topics relevant to alternative test method development. The slides from the January 26 webinar are available on the NICEATM website.
