Risk assessment process description

These four stages are identical to the four steps of the risk assessment process set out in a key 1983 US publication on risk assessment (NRC, 1983), demonstrating the influence of the US approach on Europe. It is recognized, however, that this model is not always appropriate, with ozone depletion being quoted as an effect for which stages 2 and 3 do not apply. In these cases regulators have to assess risks on a case-by-case basis and give a full description and justification of their assessments in their report to the Commission. In Chapter 7 I discuss how risk from chemicals are assessed in practice. 

Biomarkers are used at several stages in the risk assessment process. Biomarkers of exposure are important in risk assessment, as an indication of the internal dose is necessary for the proper description of the dose-response relationship. Similarly, biomarkers of response are necessary for determination of the no observed adverse effect level (NOAEL) and the dose-response relationship (see below). Biomarkers of susceptibility may be important for identifying especially sensitive groups to estimate an uncertainty factor. 

While risk assessment in the context of protecting public health has been performed for many years, it is the 1983 U.S. National Academy of Sciences Report (Committee on the Institutional Means for Assessment of Risks to Public Health Commission on Life Sciences National Research Council 1983) that has served as the tenet for practicing risk assessors (see Chapter 1). Risk assessment was defined as the characterization of the potential adverse health effects of human exposures to environmental hazards. The predictive aspect of risk assessment was set by the use of the word potential. A fundamental expectation of the risk assessment process was that it should attempt to accm-ately predict adverse effects before there is evidence of disease in the population. Thus, risk assessment goes beyond the mere description of epidemiological and clinical case-control studies. In that report, the committee defined logical components of a risk assessment which still serve as guiding principles today. They were and are (a) hazard assessment or the qualitative determination that a stressor poses a hazard as evidence by causal evidence of an ill effect,... 

Risk characterization is the final step in the risk assessment process. It comprises quantitative or semiquantitative estimations, including uncertainties, of the probability of adverse health effects in people associated with exposure to the toxic agents. Risk characterization is based on the information gathered through the first three steps in the risk assessment procedure. It is important that the weight of evidence leading to the conclusions be openly discussed. Risk characterization should include a description of the primary causes of uncertainties. 

This section contains the description of related engineering and analytical processes that are used generally in nuclear engineering related to the design and operation of nuclear processes. Chapters 19 and 20 describe the safety evaluations that are used for nuclear facilities. Chapter 19 introduces the risk assessment and safety analysis process that is used for nuclear reactors that are licensed in the United States by the Nuclear Regulatory Commission (NRC). This process has evolved from a relatively simple safety analysis used in the 1950s to a detailed risk assessment process that is used today. Chapter 20 describes the process used in the United States by the Department of Energy for safety analysis of its facilities. It is more prescriptive and less probability and risk based than the process used by the NRC. 

Examples follow in Tables 1-5 to show variations in the terms and their descriptions as used in a variety of applied risk assessment processes for the probability of occurrence and severity of consequence. There is no one right method in selecting probability and severity categories and their descriptions. 

The third category of methods addressed in this chapter are error analysis and reduction methodologies. Error analysis techniques can either be applied in a proactive or retrospective mode. In the proactive mode they are used to predict possible errors when tasks are being analyzed during chemical process quantitative risk assessment and design evaluations. When applied retrospectively, they are used to identify the underlying causes of errors giving rise to accidents. Very often the distinction between task analysis and error analysis is blurred, since the process of error analysis always has to proceed from a comprehensive description of a task, usually derived from a task analysis. 

Figure 10-1 illustrates the normal procedure for using hazards identification and risk assessment. After a description of the process is available, the hazards are identified. The various scenarios by which an accident can occur are then determined. This is followed by a concurrent... 

Risk Categorization. The first step in this process is to clearly define the risk associated with the operation of this laboratory. This step includes a brief description of the operation followed by a risk assessment and a recommendation on the level of system safety required. 

Figure 23-1 shows the hazards identification and risk assessment procedure. The procedure begins with a complete description of the process. This includes detailed PFD and P I diagrams, complete specifications on all equipment, maintenance records, operating procedures, and so forth. A hazard identification procedure is then selected (see Haz-ard Analysis subsection) to identify the hazards and their nature. This is followed by identification of all potential event sequences and potential incidents (scenarios) that can result in loss of control of energy or material. Next is an evaluation of both the consequences and the probability. The consequences are estimated by using source models (to describe the... 

Typically extrapolations of many kinds are necessary to complete a risk assessment. The number and type of extrapolations will depend, as we have said, on the differences between condition A and condition B, and on how well these differences are understood. Once we have characterized these differences as well as we can, it becomes necessary to identify, if at all possible, a firm scientific basis for conducting each of the required extrapolations. Some, as just mentioned, might be susceptible to relatively simple statistical analysis, but in most cases we will find that statistical methods are inadequate. Often, we may find that all we can do is to apply an assumption of some sort, and then hope that most rational souls find the assumption likely to be close to the truth. Scientists like to be able to claim that the extrapolation can be described by some type of model. A model is usually a mathematical or verbal description of a natural process, which is developed through research, tested for accuracy with new and more refined research, adjusted as necessary to ensure agreement with the new research results, and then used to predict the behavior of future instances of the natural process. Models are refined as new knowledge is acquired. 

Some risk assessors describe the process of setting up for risk assessment as developing a scenario. A scenario is a description of the population that is of interest and the way such a population is or could become exposed to a chemical or group of chemicals. Some typical scenarios for risk assessment are set out in Table 8.1, in abbreviated form. 

Fault tree analysis is based on a graphical, logical description of the failure mechanisms of a system. Before construction of a fault tree can begin, a specific definition of the top event is required for example the release of propylene from a refrigeration system. A detailed understanding of the operation of the system, its component parts, and the role of operators and possible human errors is required. Refer to Guidelines for Hazard Evaluation (CCPS, 1992) and Guidelines for Chemical Process Quantitative Risk Assessment (CCPS, 2000). 

The focus of this book is on methods and processes designed to predict drug-like properties, exposure and safety during hit and lead discovery. We do not intend to cover specific cultural considerations and marketing aspects [3]. What we will highlight is the need of a risk aware environment for drug discovery, where data-based integrated risk assessment is part of daily life of the team and drives the projects towards molecules with features fit for the description of an efficacious and safe medicine. 

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