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Computational Toxicology and Exposure (CompTox) Tools for Chemical Risk Analysis
Citation:
Wambaugh, J. Computational Toxicology and Exposure (CompTox) Tools for Chemical Risk Analysis. Class Presentation at North Carolina State University, Virtual, NC, April 20, 2021. https://doi.org/10.23645/epacomptox.14544360
Impact/Purpose:
Presentation to David Reif’s class at North Carolina State University on CompTox tools for assessing risk April 2021
Description:
Chemical risk assessment requires information on hazard, exposure, and toxicokinetics (TK) relevant to the scenario, for example, consumer, ambient, or occupational exposure. Most non-pharmaceutical chemicals - for example, flame retardants, plasticizers, pesticides, solvents - do not have human in vivo TK data. Non-pesticidal chemicals are unlikely to have any in vivo TK data, even from animals. To fill this gap we collect key chemical-specific data in vitro. We define “high throughput toxicokinetics” (HTTK) as the combination of in vitro toxicokinetic data with generic toxicokinetic models. The primary goal of HTTK is to provide a human dose context for bioactive in vitro concentrations from high throughput screening. These methods support in vitro-in vivo extrapolation (IVIVE) - the use of in vitro experimental data to predict phenomena in vivo. Generic TK models are used because they permit evaluation with limited chemical data - we can parameterize a generic TK model for many chemicals and evaluate that model for those chemicals that have in vivo TK data available. We then extrapolate the performance of the generic model to chemicals without in vivo data. As an example, the US EPA provides open source, peer-reviewed tools for HTTK in the R package “httk”. However, acceptance and use of in vitro data for hazard identification, prediction, and estimation is limited, in part, by uncertainties associated with toxicokinetics. With a generic model we do expect larger uncertainty, but also greater confidence in model implementation. We can estimate bias and uncertainty and try to correlate those with chemical-specific properties. EPA has been generating new in vitro TK data and expanding the available models to better cover key exposure routes, including dermal and inhalation. HTTK tools have been coupled to Monte Carlo simulation to allow propagation of both measurement uncertainty and biological variability into IVIVE-base chemical risk prioritizations. HTTK continues to expand the ways in which it can inform risk-based prioritization based on the relationship between in vitro bioactivities and exposures. The views expressed are those of the author and do not necessarily reflect the views or policies of the US EPA.
URLs/Downloads:
DOI: Computational Toxicology and Exposure (CompTox) Tools for Chemical Risk Analysis
COMPTOXCHEMICALRISK-WAMBAUGH-NCSU-042021.PDF (PDF, NA pp, 10600.401 KB, about PDF)