1,908,347 research outputs found
Advancing the Contribution of Occupational Epidemiology to Risk Assessment
No full textThe identification and quantification of risk factors that are characterized by low exposure levels, moderately increased risks, and unspecific exposure-disease relations is a major challenge facing risk assessment today. Occupational epidemiological studies can play a role in addressing this challenge. The main advantage of occupational epidemiological studies over other potential sources of information for risk assessment (primarily animal bioassays) is that in these studies humans are being investigated, rendering the extrapolation of study results from animals to humans unnecessary. However this advantage is also a disadvantage because occupational epidemiological studies are mostly observational by nature which makes them prone to bias. Although some limitations of the use of occupational epidemiological studies in risk assessment are inherent to the discipline, improvements in the design, conduct and interpretation of studies will likely enhance their use in risk assessment. Furthermore, recent developments in the field of molecular biology and the related increase in the understanding of carcinogenesis and other adverse health effects have opened opportunities to further advance the contribution of occupational epidemiological studies to risk assessment. This thesis consists of a set of approaches that can be used as a framework to advance the use of occupational epidemiological studies in risk assessment. The approaches focus on the evaluation of the quality of occupational epidemiological studies for risk assessment, the incorporation of differences in study quality in methods for evidence synthesis, and the incorporation of biomarkers in occupational epidemiological studies. Some of the approaches are ready to be applied in risk assessment. Other approaches need further development before their actual value for risk assessment can be assessed. Further progress in the use of occupational epidemiological studies in risk assessment should come from tailoring study designs to the needs of risk assessment. A strong focus on high quality quantitative exposure assessment in the design of new occupational epidemiological studies and transparency of the steps undertaken to develop quantitative exposure estimates would significantly contribute to an increased weight of evidence for risk assessment and would likely improve the overall quality of risk assessment for many exposures
Challenges of quantitative microbial risk assessment at EU level.
No full textQuantitative microbial risk assessment (QMRA) aims to model the fate of pathogenic micro-organisms along the food chain and the associated health risks. More importantly, it allows the a priori estimation of the impact on public health of interventions in the food chain. The European Food Safety Authority is increasingly asked to provide scientific advice to the European Commission based on QMRA. Its application at the European level poses some unique challenges, both of a scientific and of an organizational nature. On the other hand, collaboration at the European level will lead to more effective use of limited expertise and resources
Evaluating uncertainties in an integrated approach for chemical risk assessment under REACH: more certain decisions?
No full textThis thesis concentrates on uncertainty and variability in the risk assessment methodology for industrial chemicals as applied within the current regulatory framework for industrial chemicals in Europe, REACH (Registration, Evaluation, Authorisation and Restriction of Chemicals). The methodological approaches discussed address the risk assessment for both humans and the environment. The aim of this thesis is to investigate in what way the scientific process of risk assessment can improve decision-making knowing that uncertainties are inherently linked to risk assessment. An important element of this decision-making is consideration of precautionary measures in the event of reasonable grounds for concern of a potential risk that cannot, or not in time, be determined with sufficient certainty. The investigation is built on two frameworks: the IPCS/WHO framework for Integrated Risk Assessment (IRA) and the framework for Uncertainty Management of Walker et al. (2003). The framework of Integrated Risk Assessment was developed to improve the quality and efficiency of the assessment of risks of adverse effects on human health and the environment from chemicals, physical factors, and other environmental stressors and to provide more complete and coherent inputs to the decision making process. The underlying idea is that both the scientific discussion and the regulatory responses can benefit from a more integrated, interdisciplinary approach leading to sharing of information, decreased uncertainties and fully informed decisions. The Uncertainty Management framework closely parallels the stages in the Integrated Risk Assessment scheme and is considered very useful for highlighting different types of uncertainty in risk assessment. The main, general conclusion of this thesis is that both the process and the methodology of risk assessment as a decision-support tool under REACH can be improved. The process can be improved by the introduction of an IRA framework with a strong uncertainty management component (IRA+). The methodology can be improved by a tiered approach for uncertainty analysis, starting with simple deterministic approaches and, if necessary, classification and prioritisation of uncertainties and probabilistic approaches. Qualitative and quantitative tools for uncertainty assessment were shown to be available. If process and methodology follow the direction shown, decision-support will be more transparent, will lead to less communication problems and will improve the trust between various parties involved. Decisions which fully take into account the uncertainties in the assessments performed, including the influence of divergent opinions and assumptions of experts and stakeholders, will be better informed and will lead to transparent decisions which can be communicated in a clear way
An integrated probabilistic framework for cumulative risk assessment of common mechanism chemicals in food: an example with organophosphorus pesticides.
No full textThis paper presents a framework for integrated probabilistic risk assessment of chemicals in the diet which accounts for the possibility of cumulative exposure to chemicals with a common mechanism of action. Variability between individuals in the population with respect to food consumption, concentrations of chemicals in the consumed foods, food processing habits and sensitivity towards the chemicals is addressed by Monte Carlo simulations. A large number of individuals are simulated, for which the individual exposure (iEXP), the individual critical effect dose (iCED) and the ratio between these values (the individual margin of exposure, iMoE) are calculated by drawing random values for all variable parameters from databases or specified distributions. This results in a population distribution of the iMoE, and the fraction of this distribution below 1 indicates the fraction of the population that may be at risk. Uncertainty in the assessment is treated as a separate dimension by repeating the Monte Carlo simulations many times, each time drawing random values for all uncertain parameters. In this framework, the cumulative exposure to common mechanism chemicals is addressed by incorporation of the relative potency factor (RPF) approach. The framework is demonstrated by the cumulative risk assessment of organophosphorus pesticides (OPs). By going through this example, the various choices and assumptions underlying the cumulative risk assessment are made explicit. The problems faced and the solutions chosen may be more generic than the present example with OPs. This demonstration may help to familiarize risk assessors and risk managers with the somewhat more complex output of probabilistic risk assessment
Mode of Action Frameworks in Toxicity Testing and Chemical Risk Assessment
No full textRecently, legislative mandates worldwide are requiring systematic consideration of much larger numbers of chemicals. This necessitates more efficient and effective toxicity testing, as a basis to be more predictive in a risk assessment context. This in turn requires much more emphasis early in the design of test strategies on both potential exposure and mechanism or modes of toxicity and a resulting shift based on the latter, from hazard identification to hazard characterization in order to group substances and additionally inform development of predictive computational tools. It also requires a much better common understanding in the regulatory risk assessment community of the nature of appropriate information to inform consideration of mode of action and resulting implications for dose-response and ultimately, risk characterization. This requires a shift in focus from the previously principally qualitative considerations of toxicological science to the necessarily more predictive and quantitative focus of risk assessment and has implications for appropriate communication and training of risk assessors. Human relevance of mode of action frameworks continue to play a critical role in hypothesis generation and the systematic consideration of the weight of evidence supporting the use of mechanistic data in regulatory risk assessment. Framework analyses increase the transparency of delineation of the relative degrees of uncertainty associated with various options for consideration in dose-response and risk characterization for impacted populations. Framework analyses are also instrumental in acquiring transparency on critical data gaps that will further reduce uncertainty. As such, they force distinction of choices made on the basis of science policy versus those that are science judgment related, including reliance on default, based on erroneous premise that it is always health protective. The potential of these frameworks to increase consistency and transparency in decision making contributes to increase common understanding among communities and jurisdictions. They are an important tool for coordination and communication between the research and regulatory risk assessment communities. They are also an essential “bridge” in the evolution of toxicity testing to be more predictive, relevant and risk-based, through relation of early perturbations to apical endpoints in a context relevant to current application in regulatory risk assessment. As we move forward to develop more integrative test strategies to meet evolving and demanding regulatory mandates to deal efficiently with significantly larger numbers of chemicals including groups and combined exposures, early assimilation of the information in a mode of action context as envisaged by application of these frameworks is essential
Personality traits-based terrorism risk assessment: Determining reliability using open-source data
No full textThe chapter, "Personality traits-based terrorism risk assessment: Determining reliability using open-source data" was written by the listed authors including Logan Macnair (Douglas College Faculty). It is part of the "NATO Science for Peace and Security Series - E: Human and Societal Dynamics" series. Prominent terrorism case studies of individuals such as Omar Mateen, Dylann Roof, and Mohammed Merah indicate the need for personality trait-based terrorism risk assessment/threat assessment (TR/TA). This chapter provides an overview of Corrado’s, personality-based TR/TA instrument (see Chapter 14) by explaining the origin of each domain and the purpose of inclusion. Furthermore, this chapter displays results from a preliminary instrument validation study conducted on an open-source sample of 158 terrorists. Results of this study suggest strong statistical significance for many of the domains. This suggests the need for future inclusion of personality-based indicators in terrorism risk assessment. --From publisher description.Published
The use of modelling and probabilistic methods in cumulative risk assessment
No full textThis thesis was realized as part of the EU integrated project SAFE FOODS, the overall objective of which was to change the scope of decision-making on food safety from single risks to considering foods as sources of risks, benefits and costs associated with their production and consumption, and taking into account the social context in which decisions are made. One of the main goals within this project was the development and application of new quantitative risk assessment methods that better meet these demands of decision-makers. These new methods should account for variability in consumer populations and uncertainties in the assessment, and they should be fit to address the exposure to combinations of various chemicals present in the diet. This thesis combines several contributions to the development of this new approach. Two different computational tools are used for this purpose. Biologically based mathematical models (or mechanistic models) are models that quantitatively describe the behavior of chemicals in a biological system by use of differential equations. In this thesis, these models have been used to study the combined effects of chemicals, and how these could be predicted from information of the chemicals individually. Probabilistic methods are computational methods that combine statistical distributions of variables instead of point estimates. These methods are incorporated in the risk assessment framework to account for the variability in a population and uncertainty in the assessment. The final result is an estimate of potential health risks that may occur in the population, and a statement on how precise that estimation is
The Application of Internal Dose Measures, Biokinetics, and Biomonitoring Data in the Risk Assessment of Dioxin-Like Compounds
No full textThis thesis presents a series of investigations into the biokinetic behavior of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and related compounds and the application of biokinetic modeling and biomonitoring data in quantitative risk assessment for these compounds. The biokinetic properties of TCDD and related compounds affect nearly every facet of the typical risk assessment procedure as applied to these compounds. Qualitative and quantitative differences in the distribution and elimination of TCDD exist between high and low doses, between species, and even between bolus vs. subchronic dosing administration regimens; similarly, differences exist between TCDD and other dioxin, furan, and PCB compounds of interest. These factors should be considered in risk assessments for dioxins. Because of these complexities, preference should be given to studies most easily interpretable in the context of current human exposure tracking and assessment, which is dominated by the use of biomonitoring efforts. Where possible, use of human studies that rely upon biomonitoring data for exposure quantification concurrent with the measurement of outcome of interest may provide the most reliable basis for risk assessment. Where such data are judged to be unavailable or insufficient, animal studies conducted under chronic or subchronic dosing regimens with measured tissue concentrations may provide the most relevant dose-response data. The substantial uncertainties and interindividual variability in human biokinetics suggests that exposure-response assessments relying on extensive back-calculation of serum TCDD levels should be used only with a great deal of caution, perhaps as supportive analyses rather than the main basis for quantitative risk assessment. Research presented here uses newly-available data sets on elimination of TCDD in highly-exposed human populations to modify and implement a previously-developed model of distribution and elimination for TCDD and to examine the sources of variability and uncertainty involved in the application of such modeling to human occupational cohorts. This research demonstrates that the resulting uncertainty and variations in estimated cumulative exposures may substantially impact a quantitative risk assessment derived based on such estimated exposures. Other research presented in this dissertation demonstrates a variety of approaches for using human biomonitoring and response data in risk assessment for cancer and non-cancer endpoints. Finally, remaining issues related to the role of biokinetics in interspecies extrapolation and risk assessment for dioxins and related compounds are identified. These include the need for assessment of relative potencies on a tissue concentration (rather than intake) basis and the need for further understanding of the role of lactational transfer and interspecies correspondence in critical developmental windows in the occurrence of developmental effects of dioxin-like compounds
Uncertainties in risk assessment of dioxin-like compounds : A focus on systemic relative potencies and species differences
No full textThis thesis describes experimental work undertaken to reduce uncertainties in the risk assessment of dioxin-like compounds. The toxic equivalency factor (TEF) approach is the most commonly used method for assessing the risk of complex mixtures of dioxin-like compounds. Consequently, accurate estimates of TEF values are crucial for human risk assessment. The TEF-concept is mainly based on animal experiments with oral dosage as the principal route of exposure, but human risk assessment is often assessed based on systemic (plasma) concentration. The major objectives of this thesis were to establish if there is a need for development of specific “systemic” TEFs and to evaluate whether there are consistent species-specific differences in relative potencies. The research described in this thesis shows that for some congeners the current TEF might under- or over- estimate the risk for humans based on plasma concentrations. This is due to either congener-specific toxicokinetics or species differences in response. Taking these congener- and species- specific differences into account can help to improve human risk assessment of dioxin-like compounds
Strengths and weaknesses of Monte Carlo simulation models and Bayesian belief networks in microbial risk assessment.
No full textWe discuss different aspects of farm-to-fork risk assessment from a modelling perspective. Stochastic simulation models as they are presented today represent a mathematical representation of nature. In food safety risk assessment, a common modelling approach consists of a logic chain beginning at the source of the hazard and ending with the unwanted consequences of interest. This 'farm-to-fork' approach usually begins with the hazard on the farm, sometimes with different compartments presenting different parts of the production chain, and ends with the 'dose' received by the consumer or in case a dose response model is available the number of cases of illness. These models are typically implemented as Monte Carlo simulations, which are unidirectional in nature, and the link between statistics and simulation model is not interactive. A possible solution could be the use of Bayesian belief networks (BBNs) and this paper tries to discuss in an intuitive way the possibilities of using BBNs as an alternative for Monte Carlo modelling. An inventory is made of the strengths and weaknesses of both approaches, and an example is given showing an additional use of BBNs in biotracing problems
- …
