Determination of BMD and BMDL for ETU in VS .NET

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Determination of BMD and BMDL for ETU
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The BMD method has been quite extensively in assessing quantal data, and very often this has involved analysis of data from developmental and reproductive toxicity
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Upper Confidence limit on estimated risk
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Excess fraction of abnormal responses
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0.1 Dose response fitted to experimental data
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BMDL BMD
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Figure 24.3 Benchmark dose determination from dose response relationship with the BMDL corresponding to the lower end of a one-sided 95% con dence interval for the BMD.
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HUMAN HEALTH RISK ASSESSMENT
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studies. In this study example (Crump, 1984), rats were exposed to ethylenethiourea (ETU) at 0, 5, 10, 20, 40, and 80 mg/kg doses, and the number affected with fetal anomalies per number of rats were 0/167, 0/132, 1/138, 14/81, 142/178, and 24/24, respectively. The benchmark dose computation can involve utilization of any given dose-response probability model, but in this example the quantal Weibull model was used and the speci ed effect was set at 0.01 (1%) with con dence level of 0.95. The BMD was determined to be 8.9 mg/kg, and the BMDL was 6.9 mg/kg. This value is close to the NOAEL, which is 5 mg/kg, but it does demonstrate that the NOAEL approximates a lower con dence limit on the BMD corresponding to an excess risk of about 1% for proportions of fetal anomalies. In fact an empirical analysis of some 486 developmental toxicity studies has demonstrated that the NOAEL can result in an excess risk of 5% for proportions of dead or malformed fetuses per litter. The reader should at this stage recognize that the BMD approach can also be used in cancer risk assessment as we are often times working with quantal data that are ideally suited for BMD modeling.
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Quantifying Risk for Noncarcinogenic Effects: Hazard Quotient
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The measure used to describe the potential for noncarcinogenic toxicity to occur is not expressed as the probability. Probabilistic approach is used in cancer RA. For noncancer RA, the potential for noncarcinogenic effects is evaluated by comparing an exposure level (E) over a speci ed time period with a reference dose (RfD). This ratio is called a hazard quotient: Hazard quotient = E . RfD
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In general, the greater the value of E/RfD exceeds unity, the greater is the level of concern. Note that this is a ratio and not to be interpreted as a statistical probability.
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Chemical Mixtures
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Human populations are more likely to be exposed simultaneously or sequentially to a mixture of chemicals rather than to one single chemical. Standard default approaches to mixture risk assessment consider doses and responses of the mixture components to be additive. However, it should also be recognized that components in the mixture can also result in synergistic, antagonistic, or no toxicological effect following exposure to a chemical mixture. Therefore mixture toxicity cannot always be predicted even if we know the mechanisms of all toxic components in a de ned mixture. Furthermore tissue dosimetry can be complicated by interactions at the route of entry (e.g., GIT, skin surface) and clearance mechanisms in the body. In essence, there are considerable uncertainties involved in trying to extrapolate effects following exposure to chemical mixtures. Several PBPK models have been used to quantitate these effects and also provide some information useful for risk assessment of chemical mixtures (Krishnan et al., 1994; Haddad et al. 2001). The 1996 FQPA has also mandated that the EPA should also consider implementing cumulative risk assessments for pesticides. Cumulative risk assessments usually involve
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integration of the hazard and cumulative exposure analysis, and it primarily involves cumulative nonoccupational exposure by multiple routes or pathways to two or more pesticides or chemicals sharing a common mechanism of toxicity. Calculation procedures differ for carcinogenic and noncarcinogenic effects, but both sets of procedures assume dose additivity in the absence of information on mixtures: Cancer risk equation for mixtures : RiskT = RiskI ,
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E1 E2 Ei Noncancer hazard index = + + + . RfD1 RfD2 RfDi This hazard index (HI) approach as well as other indexes (e.g., relative potency factors) are applied for mixture components that induce the same toxic effect by identical mechanism of action. In cases where there are different mechanisms, separate HI values can be calculated for each end point of concern. As the equation above indicates, the HI is easy to calculate, as there is simply scaling of individual component exposure concentrations by a measure of relative potency such as the RfD or RfC, and adding scaled concentrations to get an indicator of risk from exposure to the mixture of concern. However, as noted above, this additivity approach does not take into account tissue dosimetry and pharmacokinetic interactions. Recent published risk assessments have utilized mixture PBPK models to account for multiple pharmacokinetic interactions among mixture constituents. These interaction-based PBPK models can quantify change in tissue dose metrics of chemicals during exposure to mixtures and thus improve the mechanistic basis of mixture risk assessment. Finally the reader should be aware that this HI is different from the a term known as the margin of safety (MOS), which is the ratio of the critical or chronic NOAEL for a speci c toxicological end point to an estimate of human exposure. MOS values greater than 100 are generally considered protective if the NOAEL is derived from animal data.
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