Computational Toxicology: Evolving Approaches to Risk Assessment Addressing Science and Regulatory Needs. W. H. Farland, US Environmental Protection Agency, DC
There is general agreement in the scientific community that increased use of more and different information will be required to improve our understanding of risks from environmental toxicants. The development of the field of computational toxicology, the marriage of genomic technologies, sophisticated structure activity analysis, and high performance computer modeling of toxicokinetic (TK) and toxicodynamic (TD) pathways, holds real promise to meet these needs. Recent advances in approaches to risk assessment are evolving to accommodate such information. Among other things, these advances focus on breaking down the traditional dichotomy between approaches to evaluating cancer and non-cancer endpoints, on addressing sensitive life stages, and on dealing with aggregate and cumulative exposure. The focus on better metrics for dose, understanding the basis for outcomes within the range of observation and use of these improvements to inform judgment below the range of observation (extrapolation) will result in better characterizations of hazard and risk. Incorporation of computational toxicology information should allow the identification of hazards by providing data on measurable biochemical or cellular endpoints which can serve as biomarkers of response for more complex adverse biological effects such as cancer, or developmental disorders. Ideally, these measurable endpoints should be mechanistically linked to the effect of concern rather than simply being correlated with it. Identification of key events leading to toxicity can provide insights into the conditions necessary for response, and the shape of the dose-response relationship for effects of concern as one goes from high to low dose. Developing means for the incorporation of such in silico data should allow the extension of the dose response relationship established by more traditional toxicology studies to lower levels, using sensitive molecular biolological and computational techniques. This approach should also save steps and reduce animal usage when compared to traditional toxicology. Several examples will be used to illustrate this approach. Application of these approaches to address emerging requirements of environmental legislation and regulation will also be discussed. For instance, the relationship of such approaches to cost-benefit analysis will be addressed.
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