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COMPUTATIONAL TOXICOLOGY - OBJECTIVE 2: DEVELOPING APPROACHES FOR PRIORITIZING CHEMICALS FOR SUBSEQUENT SCREENING AND TESTING
Citation:
Weber, E J. COMPUTATIONAL TOXICOLOGY - OBJECTIVE 2: DEVELOPING APPROACHES FOR PRIORITIZING CHEMICALS FOR SUBSEQUENT SCREENING AND TESTING. Presented at EPA Science Forum 2004, Washington, DC, June 1-3, 2004.
Impact/Purpose:
This task is divided into four major research areas: (1) Development of computational tools and databases for screening-level modeling of the environmental fate of organic chemicals; (2) Metabolism of xenobiotics: Enhancing the development of a metabolic simulator; (3) Metabonomics: The use of advanced analytical tools to identify toxicity pathways; and (4) Software infrastructure to support development and application of transformation/metabolic simulators.
For many chemicals, multiple transformation/metabolic pathways can exist. Consequently, transformation/metabolic simulators must utilize transformation rate data for prioritization of competing pathways. The prioritization process thus requires the integration of reliable rate data. When this data is absent, it is necessary to generate a database with metabolic and transformation rate constants based on: (1) experimentally measured values, including those requiring the use of advanced analytical techniques for measuring metabolic rate constants in vivo and in vitro; (2) rate constants derived from SPARC and mechanistic-based QSAR models; and (3) data mined from the literature and Program Office CBI. A long-term goal of this project is to build this database. This information will be used to enhance the predictive capabilities of the transformation/metabolic simulators. As indicated previously, exposure genomics, which provide early signs of chemical exposure based on changes in gene expression, will be used to guide chemical fate and metabolism studies. The incorporation of exposure genomics into fate studies will provide information concerning (1) the minimal concentrations at which biological events occur; and (2) the identification of biologically relevant chemicals(s) in mixtures.
The capability of categorizing chemicals and their metabolites based on toxicity pathway is imperative to the success of the CompTox Research Program. Metabonomics, which is the multi-parametric measurement of metabolites in living systems due to physiological stimuli and/or genetic modification, provides such a capability. The application of metabonomics to toxicity testing involves the elucidation of changes in metabolic patterns associated with chemical toxicity based on the measurement of component profiles in biofluids, and enables the generation of spectral profiles for a wide range of endogenous metabolites. Metabolic profiles can provide a measure of the real outcome of potential changes as the result of xenobiotic exposure.
Description:
One of the strategic objectives of the Computational Toxicology Program is to develop approaches for prioritizing chemicals for subsequent screening and testing. Approaches currently available for this process require extensive resources. Therefore, less costly and time-extensive computational approaches must be developed to determine which chemicals or classes of chemicals should be screened and tested first. Three areas where computational approaches will substantially impact on the prioritization process include Quantitative Structure Activity Relationships (QSARs) and other computational approaches, Pollution Prevention strategies, and High Throughput Screening. QSARs have been used to optimize laboratory testing, to provide estimates of missing data in lower tier risk assessment, and to estimate the toxicity of untested chemicals directly from chemical structure. Emerging "omics" technologies have excellent potential to generate information that will inform and improve the QSAR modeling process. In support of pollution prevention strategies, ORD is developing methods to estimate the potential environmental impact of chemicals that are released into the environment. These methods are used to evaluate chemicals for potential harm both to humans and the environment in a life-cycle assessment framework. Regardless of the level of sophistication in the models, the final impact indicators (e.g., a broad range of mid-point effects or final outcomes, such as human deaths, human illnesses, crop damage, water quality issues, air quality issues) could be used to compare a large number of chemicals. Applications of new molecular and other technological advances hold promise for the development of high throughput screens (HTPS). For example, new approaches have the potential for making significant advances over existing screens for Endocrine Disrupting Chemicals (EDCs) in terms of speed, high-throughput capability, sensitivity, reproducibility, and reduction in animal usage in a screening and testing program.