EXPOSURE-BASED APPROACHES

Any model has its own inherent utilities and limitations. Determination of what model to use should be dependent on the purpose. The purpose of the models used in these two cases was to determine the exposure that was associated with DLT or severe lesions in the discovery and early development phase when the exposure-based prediction needs to be made as reliably as possible in a short time. Although nonspecific measurements (e.g., DLT or lesion scores) do not scale easily across species, this exposure-based approach should still be better in terms of accuracy of prediction than the conventional dose (mg/m2)-only based predictions, such as LD10 in rodents.39... 

Recently, a new approach called artificial neural networks (ANNs) is assisting engineers and scientists in their assessment of fuzzy information, Polymer scientists often face a situation where the rules governing the particular system are unknown or difficult to use. It also frequently becomes an arduous task to develop functional forms/empirical equations to describe a phenomena. Most of these complexities can be overcome with an ANN approach because of its ability to build an internal model based solely on the exposure in a training environment. Fault tolerance of ANNs has been found to be very advantageous in physical property predictions of polymers. This chapter presents a few such cases where the authors have successfully implemented an ANN-based approach for purpose of empirical modeling. These are not exhaustive by any means. 

DeRosa CT, Choudhury H, Peirano WB. 1991. An integrated exposure/pharmacokinetic-based approach to the assessment of complex exposures Lead A case study. Toxicol Ind Health 7(4) 231-247. 

Gerberick, G. F., et al., Understanding fragrance allergy using an exposure-based risk assessment approach, Contact Derm. 45, 333-340, 2001. 

It is furthermore noted that the TTC concepts, including the structure-based approaches, are derived from databases covering substances used as direct and indirect food additives, pesticides, and industrial chemicals, and cover toxic effects related to systemic exposure to these chemicals. In addition, it is underlined that TTC has not been developed for endpoints associated with direct contact such as irritation or sensitization. 

Siemiatycki J, Gerin M, Hubert J. 1981. Exposure-based case control approach to discovering occupational carcinogens Preliminary findings. In Peto R, Schneiderman M, eds. Quantification of occupational cancer, Banbury Report No.9. Cold Spring Harbor, NY Cold Spring Harbor Laboratory, 471-481. 

In the most straightforward risk-based approach, epidemiologic studies have developed exposure-response relationships based on biomarker measurements in hair, blood, urine, or other matrices (e.g., mercury, lead) (see Figure 5-2a). The relationships can be applied directly to new biomonitoring data to determine where on the exposure-response curve any person is. That may facilitate an understanding of risk, but it does not analyze sources of exposure, so other techniques (such as environmental sampling and behavioral surveys) may be needed to assess where the exposure came from. 

As the extent of data and complexity of the analysis along this continuum increases, approaches are often presented probabilistically, including sensitivity analysis. For example, consideration is given to the probabilistic presentation of default uncertainty factors as a basis for development of reference or tolerable concentrations and/or doses or margins of safety or exposure, based on the fraction of the population to be protected. 

This section outlines the current scientific state of the art in the assessment of human health risks for chemical mixtures. It focuses on the gathering, assessment, and evaluation of effect data. The reader is referred to Chapter 1 for detailed information on exposure assessment of chemical mixtures. The section starts with an overview of methods commonly used to obtain effect data on chemical mixtures. This is followed by an overview of the current mixture approaches in human health assessments, that is, the whole mixture approach for common mixtures and the component-based approach. The section concludes with a paragraph on uncertainties in human health assessments of chemical mixtures. 

Component-Based Methods. Component-based approaches (Figure 5.5) are generally used to evaluate human health risks from exposure to a limited number of chemicals as a mixture. Key issues for component-based assessments include similarity in dose-response curves and similar vs. independent toxic modes of action (MOAs) among mixture components. A distinction can be made between 1) assessments using relatively simple additivity methods without the consideration of potential interaction effects, and 2) assessments that include data on toxicological interactions. Both types of assessments are discussed in more detail below. 

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