Indexed on: 16 Jul '09Published on: 16 Jul '09Published in: Toxicological sciences : an official journal of the Society of Toxicology
High visibility efforts in toxicity testing and computational toxicology including the recent National Research Council of the National Academies (NRC) report, Toxicity Testing in the 21st Century: A Vision and Strategy (NRC, 2007a), raise important research questions and opportunities for the field of exposure science. The authors of the National Academies report (NRC, 2007a) emphasize that population-based data and human exposure information are required at each step of their vision for toxicity testing and that these data will continue to play a critical role in both guiding development and use of the toxicity information. In fact, state-of-the-art exposure science is essential for translation of toxicity data to assess potential for risk to individuals and populations and to inform public health decisions. As we move forward to implement the NRC vision, a transformational change in exposure science is required. Application of a fresh perspective and novel techniques to capture critical determinants at biologically motivated resolution for translation from controlled in vitro systems to the open multifactorial system of real-world human-environment interaction will be critical. Development of an exposure ontology and knowledge base will facilitate extension of network analysis to the individual and population for translating toxicity information and assessing health risk. Such a sea change in exposure science is required to incorporate consideration of lifestage, genetic susceptibility, and interaction of nonchemical stressors for holistic assessment of risk factors associated with complex environmental disease. A new generation of scientific tools has emerged to rapidly measure signals from cells, tissues, and organisms following exposure to chemicals. Investment in 21st century exposure science is now required to fully realize the potential of the NRC vision for toxicity testing.