Spelling suggestions: "subject:"biologically based dos response"" "subject:"biologically based done response""
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Quantitative Structure-Activity Relationships for Organophosphates Binding to Trypsin and ChymotrypsinRuark, Christopher Daniel 02 July 2010 (has links)
No description available.
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Exploration of Contextual Influences on the Incorporation of Chemical- and Scenario-Specific Data in the Derivation of Environmental Health and Occupational Exposure Limits for ChemicalsDeveau, Michelle Leigh 29 July 2021 (has links)
Outputs of dose–response assessments can be used as benchmarks that help to identify the need for risk management measures to reduce population health risks associated with exposure to chemicals. Various approaches can be used to facilitate the incorporation of chemical- or scenario-specific data into dose–response analyses, as a means of replacing or influencing default assumptions and extrapolations. The goal of the first part of this thesis was to examine the evolution of approaches to the incorporation of chemical- and scenario-specific data in dose–response assessments in regulatory settings, and identify contextual factors that serve as barriers and facilitators to the use of approaches. A main focus of the investigation was on physiological modelling, which is the most commonly-used category of approaches enabling extrapolations that depart from default assumptions. Evaluations of the dose–response applications of physiological modelling in the peer-reviewed scientific literature and in regulatory reports were conducted. Similarities between the scientific literature databases and regulatory reports were observed with respect to the evolution of physiological modelling in dose–response assessments, notably related to the timing, quantity, and annual frequency of publications. These similarities indicate that a factor in the low dose–response application of physiological modelling, relative to the overall production of physiological models, is an absence of data. However, variability in adoption of physiological modelling in regulatory dose–response assessments was observed among—and even within—organizations faced with the same data, indicating that other factors influence regulatory uptake of physiological modelling. Analysis of a survey indicated that factors acting as barriers or facilitators to regulatory risk assessors’ incorporation of increasingly data-informed approaches originated in both external and internal contexts. The external context was composed of the regulatory environment, domestic and international alignment, availability of external expertise, background of peer reviewers and stakeholders, availability and accessibility of software and tools, and chemical-dependent factors. The internal context was influenced by problem formulation, time and financial resources, organizational and management support, and training. A conceptual framework demonstrating how these factors impact a risk assessor’s ability to incorporate chemical- and scenario-specific data in dose–response analysis was developed, and subsequently used to provide recommendations on actions that could be taken to increase regulatory adoption of increasingly data-informed approaches.
The second part of the thesis focused on the development of a knowledge translation tool designed to assist risk managers in the evaluation of dose–response analyses. The tool was focused on occupational exposure limits (OELs), and provides a guide to occupational hygienists in evaluating the relevance and reliability of individual OELs. When occupational hygienists are faced with multiple varying OELs for a chemical of interest, these evaluations can support the selection of the most appropriate OEL for a given situation. The usefulness of the tool was demonstrated for the selection of OELs for an OEL-rich compound (n-hexane), an OEL-poor compound (methamphetamine), and one additional compound (manganese). Such a tool can improve occupational hygienists’ understanding of the basis of OELs and the levels of protection afforded by each, which can contribute to more informed risk management decisions.
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