Biologically Based Dose-Response assessment

Much of the research efforts in risk assessment are therefore aimed at reducing the need to use these default uncertainty factors, although the risk assessor is limited by data quality of the chemical of interest. With sufficient data and the advent of sophisticated and validated physiologically based pharmacokinetic models and biologically based dose-response models (Conolly and Butterworth, 1995), these default values can be replaced with science-based factors. In some instances there may be sufficient data to be able to obtain distributions rather than point estimates. 

Physiologically Based Pharmacokinetic (PBPK) models and Biologically Based Dose-Response (BBDR) models are finding increasing use in risk assessment... 

Use of a biologically based dose-response (BBDR) model that can capture multiple MOAs, which may dominate in different portions of the dose-response curve [e.g., the formaldehyde assessment by The Hamner Institutes for Health Sciences, formerly Chemical Institute of Industrial Toxicology (CUT 2009)], which has been used in regulatory settings (Conolly et al. 2004). 

Slikker, W.Jr, Scallet, A.C., and Gaylor, D.W., Biologically-based dose-response model for neurotoxicity risk assessment, Toxicol. Lett, 102/103, 429, 1998. 

Dose-response assessment today is generally performed in two steps (1) assessment of observed data to derive a dose descriptor as a point of departure and (2) extrapolation to lower dose levels for the mmor type under consideration. The extrapolation is based on extension of a biologically based model (see Section 6.2.1) if supported by substantial data. Otherwise, default approaches that are consistent with current understanding of mode of action of the agent can be applied, including approaches that assume linearity or nonlinearity of the dose-response relationship, or both. The default approach is to extend a straight line to the human exposure doses. 

The first step of the dose-response assessment is the evaluation of the data within the range of observation. If there are sufficient quantitative data and adequate understanding of the carcinogenic process, a biologically based model may be developed to relate dose and response data. Otherwise, as a default procedure, a standard model can be used to curve-fit the data. For each mmor response, a POD from the observed data is estimated to mark the beginning of extrapolation to lower doses. The POD is an estimated dose (expressed in human-equivalent terms) near the lower end of the observed range, without significant extrapolation to lower doses. 

There are two possible approaches to estimating the human safe dose for chemicals that cause deterministic effects the use of safety and uncertainty factors and mathematical modeling. The former constitutes the traditional approach to dose-response assessment for chemicals that induce deterministic effects. Biologically-based mathematical modeling approaches that more realistically predict the responses to such chemicals, while newer and not used as widely, hold promise to provide better extrapolations of the dose-response relationship below the lowest dose tested. 

Risk assessment is an empirically based process that estimates the risk of adverse health effects from exposure of an individual or population to a chemical, physical, or biological agent or property. The health risk assessment process involves the following steps hazard identification, effects assessment (dose-response assessment), exposure assessment, and risk characterization (Van Leeuwen and Vermeire 2007). 

As shown previously, PBPK models allow the conversion of potential dose or exposure concentration to tissue dose, which can then be used for risk characterization purposes. The choice of an internal dose metric is based principally on an understanding of the mode of action of the chemical species of concern. The internal dose metric (sometimes called the biologically effective dose) is often used in place of the applied dose in quantitative dose-response assessments, in order to reduce the uncertainty inherent in using the applied dose to derive risk values. 

Risk Assessment. This model successfully described the disposition of chloroform in rats, mice and humans following various exposure scenarios and developed dose surrogates more closely related to toxicity response. With regard to target tissue dosimetry, the Corley model predicts the relative order of susceptibility to chloroform toxicity consequent to binding to macromolecules (MMB) to be mouse > rat > human. Linking the pharmacokinetic parameters of this model to the pharmacodynamic cancer model of Reitz et al. (1990) provides a biologically based risk assessment model for chloroform. 

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