Drinking Water and Health, Volume 8 Pharmacokinetics in Risk Assessment (1987) / Chapter Skim
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VII. Summary: Prospectives and Future Directions
VII. Summary: Prospectives and Future Directions
Pages 429-470
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PART V11 Summary: Prospectives and Future Directions
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The human exposure data are estimated retrospectively in whatever fashion possible, but the uncertainty in these calculations is a major hurdle in quantitative analyses. Once a specific chemical becomes suspect, it would be possible to do a set of quantitative experiments in animals.
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, the current preclinical toxicology protocol for anticancer drugs provides the basis for a safe starting dose, tailored to potency in rodents. The human starting dose is 1/10 of the mouse ODD, expressed on a milligrams/square meter basis.
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For these 17 anticancer drugs, the median MTD in humans was equal to the mouse LD~o, when both doses were expressed on a milligram/square meter basis. To compare toxicity on a milligram/kilogram basis, the ordinate was multiplied by 0.083.
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Schedule dependency due to exposure time differences 3. Species differences in target cell sensitivity
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(1983) have reported that with many anticancer drugs, toxicity observations carry across species on a milligram/square meter basis, as long as schedules are similar.
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At the time of awakening, however, the plasma drug concentration was similar in all three species. Thus, this is an example of a species difference in drug effect that is determined by pharmacokinetic changes in exposure patterns.
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, there is no obvious plasma pharmacokinetic explanation for the species difference in toxicity. In contrast to the situation for doxorubicin (in which equitoxic doses produced similar plasma drug concentrations)
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. Because bone marrow suppression is the principal acute toxicity in viva, it appears that the species differences are due to target cell differences for this drug.
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Further work is ongoing at the National Cancer Institute that is exploring the use of C x T data to adjust escalation rates in phase I trials (Collins et al., 19861. CONCLUSIONS The development of new anticancer drugs generates a unique quantitative data base that can be used for interspecies comparisons of toxicity.
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1983. Increasing therapeutic response rates to anticancer drugs by applying the basic principles of pharmacology.
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Because laboratory tests are conducted at relatively high-dose levels to induce measurable rates of response in a small sample of experimental animals, it is often necessary to extrapolate these results to lower doses corresponding more closely to anticipated human exposure levels. Because the test species do not resemble the target species in all respects, it is also necessary to take into account interspecies differences when extrapolating between the animal model used and man.
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In contrast to such mathematical pharmacokinetic models, physiological pharmacokinetic models in which the body is considered to consist of a larger number of relevant physiological compartments have also been employed in recent years. Although they require detailed information on physiological and biochemical parameters, such physiologically based pharmacokinetic models have also been used to predict the risk associated with exposure to specific substances such as styrene and methylene chloride (Ramsey and Andersen, 1984; Andersen et al., 1987)
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In particular, data on formaldehyde, vinyl chloride, and methylene chloride are used to compare risk estimates derived on the basis of administered and delivered doses. The use of physiologically based pharmacokinetic models to extrapolate between species and routes is also illustrated by using data on methylene chloride and perchloroethylene.
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Low-dose linearity also occurs with pharmacokinetic models in those cases in which all kinetic processes are linear at low doses, provided that the probability of tumor occurrence is proportional to the dose delivered to the target tissue in the low-dose region. The assumption of low-dose linearity in carcinogenic risk assessment is supported by the U
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This method of robust linear extrapolation can be advantageous, however, in cases in which the multistage model provides a poor fit to the experimental data, as can occur when the dose-response curve tends to rise sharply at low doses and then plateau at higher doses. PHARMACOKINETIC MODELS Mathematical Pharmacokinetic Models The description of complex phenomena that occur in viva following exposure to a toxicant is accomplished with maximum simplification by means of mathematical equations derived from the conception of biological systems that consist of a small number of compartments.
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The interpretation and quantitation of precise mechanisms that actually occur within physiological compartments in the body, however, are generally not possible by using mathematical pharmacokinetic models. Physiologically Based Pharmacokinetic Models One of the methods of examining the kinetics of absorption, distribution, metabolism, and excretion of a xenobiotic involves a description of the body as a series of relevant physiological compartments arranged as a system of parallel shunts between the venous and arterial blood supplies (Fiserova-Bergerova, 1983; Himmelstein and Lutz, 19791.
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ADMINISTERED AND DELIVERED DOSES One of the potential applications of pharmacokinetics to risk assessment involves the use of pharmacokinetic models to determine the effective dose of compound of interest that reaches the target tissue. The dose delivered to the target tissue can then be used in place of the administered dose in an attempt to obtain more accurate estimates of risk.
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delivered to the target tissue and the administered dose d can be nonlinear (Hoer et al., 19831. To explore the effects of metabolic activation in estimates of low-dose risks, consider the simple pharmacokinetic model for metabolic activation of a particular toxicant shown in Figure 1 (Krewski et al., 19861.
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Both Linear FIGURE 2 Administered and delivered doses with saturable kinetics. 1 0 To assess the implications of saturable kinetics on linear extrapolation from high to low doses using the administered dose d, we conducted a computer simulation involving the four cases illustrated in Figure 2.
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.1 . ~-Y I, 1 ..oo 1 .01 .1 ~ 10 1 O Upper Con f idence Limit on Slope FIGURE 3 Cumulative distribution of upper confidence limits on low-dose slope based on robust linear extrapolation.
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The temporal profile of the dose delivered to the target tissue is shown in Figure Sa for four different exposure scenarios under the assumption that the detoxification process is nonsaturable (Withey and Murdoch, 19871. Curve A presents the case of continuous inhalation exposure to a constant dose d = 60 ~g/h over an 8-h working day.
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FIGURE 5 Time-dependent exposure patterns with saturable kinetics. Curve B is derived so as to have the same total administered dose of 480 fig following 16 equal oral doses of 30 fig given every 30 min.
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To explore the effects of time-dependent exposure patterns, consider a multistage model in which only one stage is dose dependent. As shown in the Appendix, the carcinogenic risk associated with a delivered dose d*
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(t) that reaches the target tissue during the period of exposure.
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Assuming that covalently bound formaldehyde is associated with neoplastic change, these data can be used to evaluate the impact of the use of the delivered rather than the administered dose in predicting cancer risks at low doses. For purposes of illustration, consider the data on tumor incidence following inhalation exposure of 6 in/day, 5 days/week for 24 months shown in Table 2, as previously considered in this context by Starr and Buck (19841.
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Although the relationship between the delivered and administered doses is unknown below 2 ppm, the data are not inconsistent with a linear relationship in this region with a slope of approximately 0.01 nmol/mg/ ppm. Under this assumption, robust linear extrapolation on the delivered dose scale leads to an upper confidence limit on the slope of the doseresponse curve at the origin of 0.23 mg/nmol, equivalent to a slope of 0.0023 ppm-i = 0.01 nmol/mg/ppm x 0.23 mg/nmol on the administered dose scale.
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. — 10 15 Administered Dose (ppm)
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In this example, the dose-response curve is apparently linear at doses below 200-SOO ppm on either the administered or delivered dose scale. Because of this, robust linear extrapolation based on delivered dose, which focuses primarily on data in this dose range, leads to an upper confidence limit on the low-dose slope of 0.00034 (1lg/4 h)
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Because the rate of delivery of the parent compound is proportional to the rate of the GST path, effects of the parent compound cannot be distinguished from those TABLE 4 Hepatocellular Adenomas/Carcinomas Induced in Female Mice Exposed to Methylene Chlonde Delivered Dose Route of Parent Administration Administered MFO Path GST Path Compound Tumor (dose units) Dose (g/liter/day)
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Based on the GST path, the delivered dose in the high-dose groups is approximately 100 times higher in the inhalation study than in the drinking
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, whereas those in the drinking water study were not. An upper confidence limit on the risk at low doses for female mice can be calculated by using robust linear extrapolation based on the delivered dose data from the inhalation study in Table 4 to be 0.56 (g/liter/day)
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By using a simple mathematical pharmacokinetic model for metabolic activation in which the probability of tumor induction is proportional to the delivered dose, it was shown with a computer simulation that saturation effects in metabolic activation resulting in a curvilinear dose response can have an impact on estimates of low-dose risk obtained by linear extrapolation. In particular, saturation of detoxification processes can result in an appreciable overestimation of risk, whereas saturation of activation processes can lead to some underestimation of risk.
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By using a simple mathematical compartmental model based on linear kinetics, it was demonstrated that exposure regimens with different dosing intervals having the same systemic availability lead to different peak concentrations in the target tissue. In the absence of bioaccumulation, however, it was noted that under the multistage model of carcinogenesis, the area under the concentration-time curve is a better predictor of carcinogenic risk than are peak concentrations.
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1987. Physiologically based pharmacokinetics and the risk assessment process for methylene chloride.
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1979. A review of the applications of physiologically based pharmacokinetic modeling.
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1978. Carcinogenic risk estimation for chloroform: An alternative to EPA's procedure.
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where (ai, bi > 04. For constant exposure data = d, this reduces to the usual form of the multistage model with: tk k H(t)
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over O < u < t, the ratio R of the excess risk under variable dosing as compared with that based on a constant average dose is at most the maximum value of the density Mu; r, k—r + 1, tJ divided by its average value lit. This ratio can be written as: R = ~ ~ leak ~ '(!
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PART V111 Perspectives
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Key Terms
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