Dose-response assessment database

Evans, R.D., R.S. Harris, and J.W.M. Bunker. 1944. Radium metabolism in rats, and die production of osteogenic sarcoma by experimental radium poisoning. Am. J. Roentgenol. 52 353-373. Faustman, E.M., B.C. Allen, R.J. Kavlick, and C.A. Kimmel. 1994. Dose-response assessment for developmental toxicity. I. Characterization of database and determination of no observed adverse effect levels. Fundam. Appl. Toxicol. 23(4) 478-486. ... 

The science supporting the use of UFs has evolved considerably over the past years. Increased knowledge of inter- and intraspecies sensitivity, mechanism of action, and detailed evaluation of databases has led to improvements that allow for the incorporation of more scientific data into the dose-response assessment of noncancer toxicity, and permit the use of factors other than the standard default values. 

The U.S. EPA approach to risk assessments for toxic chemicals follows the format described by the NRC. Because Hazard Identification and Dose-Response Assessment for an agent do not depend upon specific local situations, EPA assumes that risk assessors evaluating specific sites will not conduct independent analyses in these areas but will instead rely on the results of peer-reviewed evaluations by qualified authorities in toxicology. EPA is assembling an agency-wide database of such authoritative assessments, the Integrated Risk Information System (IRIS). 

In relation to the dose-response curve, KEMI (2003) stated that the slope always has to be considered. A moderate assessment factor (not further specified) may provide an adequate MOS if the dose-response relationship is relatively steep, but may not be sufficiently conservative if the dose-response curve is relatively shallow, see Figure 5.6. In relation to extrapolation from LOAEL to NOAEL, KEMI considered that analysis of several databases does support the statement that a... 

Ilb- larger scale trials in patients (several hundreds) to formally assess the dose-response relationship and continue to expand the efficacy and safety databases. 

In characterizing the database, a number of assumptions are applied when data are not available or are incomplete (USEPA, 1991 IPCS, 2005 Kimmel et al., 2006). These include uncertainties about toxicokinetics, mechanism of action, low-dose-response relationships, and human exposure patterns. Each of these assumptions is supported to some extent by the scientific literature. The following assumptions are generally accepted in risk assessment strategies ... 

It is important that both the qualitative and quantitative characterization be clearly communicated to the risk manager. The qualitative characterization includes the quality of the database, along with strengths and weaknesses, for both health and exposure evaluations the relevance of the database to humans the assumptions and judgements that were made in the evaluation and the level of confidence in the overall characterization. The quantitative characterization also includes information on the range of effective exposure levels, dose-response estimates (including the uncertainty factors applied), and the population exposure estimates. Kimmel et al. (2006) reviewed many of the components of the risk characterization for reproductive and developmental effects and provided a comprehensive list of issues to be considered for each of the components of the risk assessment. 

Risk characterization The synthesis of critically evaluated information and data from exposure assessment, hazard identification, and dose-response considerations into a summary that identifies clearly the strengths and weaknesses of the database, the criteria applied to evaluation and validation of all aspects of methodology, and the conclusions reached from the review of scientific information. 

In light of the fact that numerous terms have been employed to describe hormetic dose-responses and often investigators fail to recognize and acknowledge this effect in their published data, a hormetic database was created in order to systematically collect and assess hormetic dose-responses (Calabrese and Baldwin, 1997 Calabrese and Blain, 2005). The information collected has permitted an evaluation of the quantitative features of the hormetic dose-response relationship, but it has also revealed that hormetic dose-responses occur independent of biological model, endpoint measured, and chemical class. Based upon information contained in this database several dozen dose-response relationships were selected in order to demonstrate the occurrence of hormetic dose-responses across model, endpoint, and chemical class (Figure 5.3). 

The model was demonstrated through a case study utilizing a safety database that contains 30 randomized clinical trials with one primary drug of interest [27]. Posterior probabilities were obtained to assess the potential dose-response relationship, including evaluation of whether or not any potential relationship is clinically meaningful. 

FIGURE 13.4 Development of the number of stored single point (percent of control) and dose-response measurements in the CDB over the last decade. Reprinted from Bioorganic Medicinal Chenustry, VoL 20, Bemd Beck, BioProfile—Extract knowledge from corporate databases to assess cross-reactivities of compounds, 5428-5435, 2012, with permission fix)m Elsevier. 

The size and quality of the available database for an environmental pollutant will vary greatly across substances and will also vary within the four components of the typical risk assessment. The variety of adverse health risks of a substance may be qualitatively well known, for example, but dose—response relationships may be poorly quantifiable because of either limits of inadequate exposure measurement data or absence of good biomarkers of adverse effect or absence of information on the full span of the dose—response curve. Hazard characterization and dose—response relationships may both be understood as general descriptors, but case-specific or scenario-specific exposure data may be lacking, requiring judgment about alternative approaches (e.g., default values). 

As discussed in the introduction to Section 2.1, there are a number of limitations in the human database for most health effects, the data are inadequate to assess the potential for humans having a particular effect. Because the human data are incomplete, hazard and risk must be extrapolated across species. A large number of adverse effects have been observed in animals, and most have been observed in every experimental animal species tested, if the appropriate dose is administered. This is illustrated in Table 2-8 for 8 major effects associated with CDD toxicity (acute lethality, hepatotoxicity, wasting syndrome, chloracne, immunotoxicity, reproductive toxicity, developmental toxicity, and cancer). With the exception of acute lethality in humans, positive responses have been observed in each tested species, when a response has been investigated. Despite the similarities in hazard response between different species, large species differences in sensitivity have been observed. Comparisons of species sensitivity demonstrate that no species is consistently sensitive or refractory for all effects and, for some effects,... 

One endeavor of risk assessment i.s to identify the threshold for a toxicological effect such as hypothermia. It seems that the threshold AChE inhibition for induction of hypothermia would be lowered if the animals were subjected to colder temperatures and more sensitive methods were used to monitor core temperature (i.e., telemetry). Must rodent. studies arc performed at ambient temperatures that are comfortable for humans (-22 °C) but are approximately 6 C below the rat. s lower critical temperature. Our database on threshold doses to achieve physiological responses to anti-ChEs as well as other toxicants could change significantly if the choice of temperatures to house and test rodents was reconsidered. 

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