Applied Genetic Toxicity for Regulatory Decision Making: The Road Ahead

Applied Genetic Toxicity for Regulatory Decision Making: The Road Ahead
Potsdam, Germany , United States
March 22, 2018 – March 23, 2018

Background and Objectives
Applied genetic toxicology is undergoing a major paradigm shift towards changing the strategies employed for assessment of chemically-induced genomic damage, evaluation methods of the mechanisms by which that damage translates into adverse effects, and the quantitative methods used to interpret dose-response data. This shift entails a movement away from simple dichotomous evaluations of genotoxicity (i.e., yes/no), that only supports identification of potential carcinogens, and towards a greater understanding of the diversity of adverse outcomes related to genomic damage, of the multitude of mechanisms (or modes of action) underscoring genomic damage, and the ability to determine point of departure metrics for human health risk assessment and regulatory decision making. Moreover, advanced technologies to investigate genotoxic mechanisms and to analyze dose-response functions are being developed and incorporated into assessments of genomic damage.


This workshop was organized by the HESI Genetic Toxicology Technical Committee (GTTC). The HESI GTTC brings together an international cohort of genetic toxicologists from industry, academia, and government to address issues related to all aspects of genetic toxicity assessment. These aspects include the development and validation of assessment approaches, technologies and strategies for mode-of-action determination, and approaches for data interpretation. The GTTC is comprised of experts in the fields of genetic and general toxicology, risk assessment, and computational biology. The workshop will examine a new generation of testing strategy for assessment of genomic damage, new approaches and technologies for mode-of-action determination and interpretation, and recent developments in quantitative interpretation of genetic toxicity dose-response data.