Issues in Qualitative and Quantitative Risk Analysis for Developmental Toxicology1

The qualitative and quantitative evaluation of risk in developmental toxicology has been discussed in several recent publications.(^1–3) A number of issues still are to be resolved in this area. The qualitative evaluation and interpretation of end points in developmental toxicology depends on an understanding of the biological events leading to the end points observed, the relationships among end points, and their relationship to dose and to maternal toxicity. The interpretation of these end points is also affected by the statistical power of the experiments used for detecting the various end points observed. The quantitative risk assessment attempts to estimate human risk for developmental toxicity as a function of dose. The current approach is to apply safety (uncertainty) factors to die no observed effect level (NOEL). An alternative presented and discussed here is to model the experimental data and apply a safety factor to an estimated risk level to achieve an “acceptable” level of risk. In cases where the dose-response curves upward, this approach provides a conservative estimate of risk. This procedure does not preclude the existence of a threshold dose. More research is needed to develop appropriate dose-response models that can provide better estimates for low-dose extrapolation of developmental effects.     

Evaluation of Developmental Toxicity Data: A Discussion of Some Pertinent Factors and a Proposal

There is currently no well-accepted standard method for evaluation of developmental toxicity data. This paper presents one approach to the evaluation of developmental toxicity data. We initially identify some pertinent factors that influence the interpretation of animal data and summarize the literature pertaining to these factors. Such factors include the quality and quantity of data and the relationship between maternal and developmental toxicity. We proceed with a discussion of quantitative assessment of data and propose schemes for qualitative and quantitative developmental hazard assessments.     

Summary of the Workshop on Issues in Risk Assessment: Quantitative Methods for Developmental Toxicology

This report summarizes the proceedings of a conference on quantitative methods for assessing the risks of developmental toxicants. The conference was planned by a subcommittee of the National Research Council's Committee on Risk Assessment Methodology ⁴ in conjunction with staff from several federal agencies, including the U.S. Environmental Protection Agency, U.S. Food and Drug Administration, U.S. Consumer Products Safety Commission, and Health and Welfare Canada. Issues discussed at the workshop included computerized techniques for hazard identification, use of human and animal data for defining risks in a clinical setting, relationships between end points in developmental toxicity testing, reference dose calculations for developmental toxicology, analysis of quantitative dose-response data, mechanisms of developmental toxicity, physiologically based pharmacokinetic models, and structure-activity relationships. Although a formal consensus was not sought, many participants favored the evolution of quantitative techniques for developmental toxicology risk assessment, including the replacement of lowest observed adverse effect levels (LOAELs) and no observed adverse effect levels (NOAELs) with the benchmark dose methodology.     

Implications of Developmental Toxicity Study Design for Quantitative Risk Assessment

Standard experimental designs for conducting developmental toxicity studies typically include three- or four-dose levels in addition to a control group. Some researchers have suggested that designs with more exposure groups would improve dose-response characterization and risk estimation. Such proposals have not, however, been supported by the results of simulation studies, which instead back the use of fewer dose levels. This discrepancy is partly due to using a known dose–response pattern to generate data, making model choice obvious. While the carcinogenicity literature has explored implications of different study designs, little attention has been given to the role of design in developmental toxicity risk assessment (or noncancer toxicology in general). In this research, we explore the implications of various experimental designs for developmental toxicity by resampling data from a large study of 2,4,5-trichlorophenoxyacetic acid in mice. We compare the properties of benchmark dose (BMD) estimation for different design strategies by randomly selecting animals within particular dose groups from the entire 2,4,5-T database of over 77,000 birth outcomes to create smaller "pseudo-studies" that are representative of standard bioassay sample sizes. Our results show that experimental designs which include more dose levels have advantages in terms of risk characterization and estimation.     

Applications of Multinomial Dose-Response Models in Developmental Toxicity Risk Assessment

Reproductive and developmental anomalies induced by toxic chemicals may be identified using laboratory experiments with small mammalian species such as rats, mice, and rabbits. In this paper, dose-response models for correlated multinomial data arising in studies of developmental toxicity are discussed. These models provide a joint characterization of dose-response relationships for both embryolethality and teratogenicity. Generalized estimating equations are used for model fitting, incorporating overdispersion relative to the multinomial variation due to correlation among littermates. The fitted dose-response models are used to estimate benchmark doses in a series of experiments conducted by the U.S. National Toxicology Program. Joint analysis of prenatal death and fetal malformation using an extended Dirichlet-trinomial covariance function to characterize overdispersion appears to have statistical and computational advantages over separate analysis of these two end points. Benchmark doses based on overall toxicity are below the minimum of those for prenatal death and fetal malformation and may, thus, be preferred for risk assessment purposes.     

A Simulation Study of the Influence of Study Design on the Estimation of Benchmark Doses for Developmental Toxicity1

The benchmark dose (BMD)⁴ approach is emerging as replacement to determination of the No Observed Adverse Effect Level (NOAEL) in noncancer risk assessment. This possibility raises the issue as to whether current study designs for endpoints such as developmental toxicity, optimized for detecting pair wise comparisons, could be improved for the purpose of calculating BMDs. In this paper, we examine various aspects of study design (number of dose groups, dose spacing, dose placement, and sample size per dose group) on BMDs for two endpoints of developmental toxicity (the incidence of abnormalities and of reduced fetal weight). Design performance was judged by the mean-squared error (reflective of the variance and bias) of the maximum likelihood estimate (MLE) from the log-logistic model of the 5% added risk level (the likely target risk for a benchmark calculation), as well as by the length of its 95% confidence interval (the lower value of which is the BMD). We found that of the designs evaluated, the best results were obtained when two dose levels had response rates above the background level, one of which was near the ED₀₅, were present. This situation is more likely to occur with more, rather than fewer dose levels per experiment. In this instance, there was virtually no advantage in increasing the sample size from 10 to 20 litters per dose group. If neither of the two dose groups with response rates above the background level was near the ED₀₅, satisfactory results were also obtained, but the BMDs tended to be more conservative (i.e., lower). If only one dose level with a response rate above the background level was present, and it was near the ED₀₅, reasonable results for the MLE and BMD were obtained, but here we observed benefits of larger dose group sizes. The poorest results were obtained when only a single group with an elevated response rate was present, and the response rate was much greater than the ED₀₅. The results indicate that while the benchmark dose approach is readily applicable to the standard study designs and generally observed dose-responses in developmental assays, some minor design modifications would increase the accuracy and precision of the BMD.     

Design of Developmental Toxicity Studies for Assessing Joint Effects of Dose and Duration

In the assessment of developmental and reproductive effects, the timing and duration of exposures to chemical compounds or other environmental contaminants are of particular interest, as the gestational cycle is known to have periods of increased sensitivity. The goal of this research is to identify optimal experimental designs for conducting developmental toxicity studies when the effects of both exposure level and duration of exposure are of interest. The elements of the study design considered in this evaluation are the allocation of animals to dose-duration exposure groups and the determination of the most efficient intermediate exposure levels. The optimality of various designs is assessed via the accuracy of the estimated excess risk as well as testing criteria. Simulation studies are conducted to compare these criteria and determine optimal design strategies under various underlying dose-response patterns. Asymptotic results are also derived to lend support to the simulation studies.     

A Comparison of Methods for Estimating the Benchmark Dose Based on Overdispersed Data from Developmental Toxicity Studies

Developmental anomalies resulting from prenatal toxicity can be manifested in terms of both malformations among surviving offspring and prenatal death. Although these two endpoints have traditionally been analyzed separately in the assessment of risk, multivariate methods of risk characterization have recently been proposed. We examined this and other issues in developmental toxicity risk assessment by evaluating the accuracy and precision of estimates of the effective dose ( ED ₀₅) and the benchmark dose ( BMD ₀₅) using computer simulation. Our results indicated that different variance structures (Dirichlet-trinomial and generalized linear model) used to characterize overdispersion yielded comparable results when fitting joint dose response models based on generalized estimating equations. (The choice of variance structure in separate modeling was also not critical.) However, using the Rao-Scott transformation to eliminate overdispersion tended to produce estimates of the ED ₀₅ with reduced bias and mean squared error. Because joint modeling ensures that the ED ₀₅ for overall toxicity (based on both malformations and prenatal death) is always less than the ED ₀₅ for either malformations or prenatal death, joint modeling is preferred to separate modeling for risk assessment purposes.