Developmental Toxicity Risk Assessment Research Articles

Embryology and developmental toxicity risk assessment: complexity, concerns, and implications for industrializing developing nations

Embryology and developmental toxicity risk assessment: complexity, concerns, and implications for industrializing developing nations

A tiered approach to cumulative risk assessment for reproductive and developmental toxicity of food contaminants for the austrian population using the modified Reference Point Index (mRPI)

Through our daily diet, we are exposed to a variety of food contaminants. Yet, assessing the cumulative health risk of chemical mixtures remains a challenge. Using a recently developed method, the modified Reference Point Index (mRPI), the cumulative risks posed by contaminant mixtures were assessed for their effects on reproduction and development. Since these effects can be quite diverse, a tiered approach was adopted to elucidate the risks at a more detailed level based on specific toxicological endpoints. An additional analysis was performed using the modified Maximum Cumulative Ratio (mMCR), which provides the determination of risk-dominating substances in the mixture. Our method represents a novel useful tool to screen and prioritise contaminant mixtures regarding their potential health risks.We found, that in the majority of the calculated scenarios a single substance dominates the cumulative risks. Lead was found to be the primary factor for adverse effects on reproduction and neuronal development of children. Perchlorate was identified as the most prominent risk factor for child development in generalCumulative risks of trichothecenes were dominated by deoxynivalenol. Concerning the impact on pre- and neonatal development, the co-exposure of several substances resulted in increased risks, with none of the considered contaminants dominating substantially.

An overview of developmental and reproductive toxicity risk assessment in China

Development and reproductive toxicology (DART) studies in animals are integral parts of nonclinical safety evaluation of drugs. The State Food and Drug Administration (SFDA) of the People's Republic of China developed a new guideline on DART studies in 2006. This guideline is in broad agreement with ICH guideline S5A (1994), "Detection of Toxicity to Reproduction for Medical Products," and M3, "Nonclinical Safety Studies for the Conduct of Human Clinical Trials for Pharmaceuticals." However, the new guideline on DART testing differs from ICH in some detailed requirements. This overview reviews some main specifications in China's guidelines on DART testing, and also briefly introduces the recommendations for conducting human clinical trials and marketing authorization in China.

Glycol Ethers: A Ubiquitous Family of Toxic Chemicals

Glycol ethers (GE) are chemicals used since the 1930s as solvents in paints, inks, varnishes, and cleaning agents, mainly in water-based products, cosmetics, and drugs. World production approximates 1 million tons. Nineteen GE are produced or imported each year; over 1000 tons in European Union (EU) have been classified as high production volume chemicals (HPVCs). First animal data were published in 1971 and 1979 showing severe reprotoxicity for some GE. Two alerts were launched in the United States in 1982 and 1983, but the first partial GE regulation only occurred in 1993 in the EU. Although these chemicals may expose a very large population, basic toxicity data, more especially carcinogenicity, are still lacking (3/32 GE). However, experimental data were sufficient to lead developmental toxicity risk assessment since the early 1980s. Risk indices over 1000 have been calculated for consumers and workers exposed to reprotoxic GE in domestic and industrial activities. The first ban was decided in 1999 in France, but was only for drugs and cosmetics. Not surprisingly, since the late 1980s, human studies have found results similar to those in animal data: spontaneous abortions, malformations, testicular toxicity, and hematotoxicity. Despite this highly coherent set of data, and although substitution products are available, reprotoxic GE have been and still remain widely used in the world. The case of GE shows the failure of the present system based on a posteriori risk assessment. This pleads for the change of paradigm through the European REACH regulation based on the "No data, no market" principle. Ethics in REACH management should also be considered.

Flexible Quantitative Risk Assessment for Developmental Toxicity Based on Fractional Polynomial Predictors

Risk assessment for developmental toxicity studies in rodents is faced with the fairly involved data structure of clustered multivariate binary outcomes. While likelihood methods for this setting do not abound, we show that a conditional model, combined with pseudo-likelihood inference and fractional polynomial predictor functions, as proposed by Royston and Altman (1994), are a promising way forward. The methods are illustrated using teratology data collected under the National Toxicology Program.

Flexible Quantitative Risk Assessment for Developmental Toxicity Based on Fractional Polynomial Predictors

Flexible Quantitative Risk Assessment for Developmental Toxicity Based on Fractional Polynomial Predictors

Litter-based methods in developmental toxicity risk assessment

Developmental toxicity experiments are designed to assess potential adverse effects of drugs and other exposures on developing fetuses from pregnant dams. Extrapolation to humans is a very difficult problem. An important issue here is whether risk assessment should be based on the fetus or the litter level. In this paper, fetus and litter-based risks that properly account for cluster size are defined and compared for the beta-binomial model and a conditional model for clustered binary data. It is shown how the hierarchical structure of non-viable implants and viable but malformed offspring can be incorporated. Risks based on a joint model for death/resorption and malformation are contrasted with risks based on an adverse event defined as either death/resorption or malformation. The estimation of safe exposure levels for all risk types is discussed and it is shown how estimation of the cluster size distribution affects variance estimation. The methods are applied to data collected under the National Toxicology Program and in large sample simulations.

Invited perspective: In vitro testing in developmental toxicity risk assessment

Invited perspective: In vitro testing in developmental toxicity risk assessment

Benchmark Dose Analysis of Developmental Toxicity in Rats Exposed to Boric Acid

Developmental toxicity risk assessment has typically relied on the estimation of reference doses or reference concentrations based on the use of no-observed-adverse-effect levels (NOAELs) divided by uncertainty factors. The benchmark dose (BMD) approach has been proposed as an alternative basis for reference value calculations. In this analysis of the developmental toxicity observed in rats exposed to boric acid in their diet, BMD analyses have been conducted using two existing studies. By considering various end points (rib XIII effects, variations of the first lumbar rib, and fetal weight changes) and various modeling approaches for those end points, the best approach for incorporating all of the information available from those studies could be determined. Particular emphasis has been placed on methods for combining data across studies and for combining potentially related effects (on rib XIII and on the first lumbar rib). The issues of study and end point selection are ones that will arise frequently in the process of estimating reference values. This example of boric acid suggests that the BMD approach provides a reasonable basis for appropriately comparing and combining study data, as opposed to ad hoc combinations of study results. Moreover, it is shown that the BMD approach can be used with combinations of end points considered to differ in severity. In this case, the preferred approach involved combining the data from the two studies, which were similarly designed and were conducted in the same laboratory, to calculate BMDs that were more accurate and more precise than those that could be derived from either study alone. It was determined that decreased fetal body weight provided the best basis for BMD calculations; BMDs calculated for fetal body weight changes were less than those for all other relevant end points. The appropriate BMD to use as the basis for boric acid reference dose calculation appears to be 59 mg/kg/day, which is very similar to the NOAEL observed in the second of the two studies (55 mg/kg/day). Although the first study failed to establish a NOAEL, the BMD approach could have been applied to that study, thereby avoiding the need for a repeat study. Similar BMD results were obtained in both studies.

Letters: Developmental Toxicity Risk Assessment: What's Really Important?

Letters: Developmental Toxicity Risk Assessment: What's Really Important?

Developmental Toxicity Risk Assessment: Consensus Building, Hypothesis Formulation, and Focused Research

Risk assessment for developmental toxicity has become more defined over the last decade and the most recent EPA guidelines for developmental toxicity risk assessment were published in 1991. Development of approaches for risk assessment in this area have relied on building of consensus opinion among experts about the interpretation of developmental toxicity data. These discussions have aided in strengthening the scientific basis for risk assessment for developmental toxicity, including the default assumptions that must be used when more complete information on mechanisms of action and pharmacokinetics are unavailable. Such discussions continue on both a national and international basis. The EPA risk assessment guidelines outlined several major areas of research needed to strengthen risk assessment for developmental toxicity and led to the formulation of hypotheses to be tested in focused research projects. Several major research efforts have focused on dose-related mechanisms and biologically based modeling of specific agents, physiologically based pharmacokinetic models of pregnancy that can be scaled across species, and the influence of dose and duration of exposure on developmental outcomes, as well as the delineation of specific biomarkers of adverse developmental effects. Although such research initiatives will require a long-term effort, it is important that attention be focused now on those approaches that can improve the risk assessment process to avoid continued reliance on default approaches that have been used for the past 30 years or more. The impact of the EPA Guidelines for Developmental Toxicity Risk Assessment has been widespread. One of the main purposes for developing risk assessment guidelines by EPA was to communicate procedures to risk assessors inside the agency in an effort to promote consistency. In addition, the guidelines were to communicate to those outside the agency in private industry and other regulatory agencies how EPA would evaluate and interpret data. The developmental toxicity guidelines have standardized terminology used in developmental toxicity risk assessments. They also have influenced the revision of testing guidelines and the writing of new guidelines, such as the developmental neurotoxicity testing guidelines. More extensive use of developmental toxicity data within the RfD/RfC process was influenced by the guidelines, as well. More recently, the risk assessment guidelines have had a major impact on the harmonization of international testing and risk assessment guidelines through cooperative efforts with the World Health Organization under the auspices of the International Program on Chemical Safety (IPCS) and the Organization for Economic Cooperation and Development (OECD). We foresee these types of interagency and international cooperative efforts continuing as we attempt to make more efficient use of the limited resources available for testing, risk assessment, and research to better understand and prevent developmental toxicity.

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.

Neurotoxicity Modeling for Risk Assessment

The setting of acceptable exposure levels for neurotoxicants has followed the traditional approach of dividing experimental no-observed-adverse-effect-levels (NOAELs) by safety/uncertainty factors. NOAELs are believed by many toxicologists to represent levels having zero or negligible risk, while uncertainty factors are used to account for a number of sources of variation. Although the use of NOAELs in this manner has been criticized because of their imprecise quantitative definition, NOAELs for nonquantal neurotoxic effects have not been replaced by more precisely defined quantities (e.g., benchmark doses), partly due to the absence of a generally accepted methodology for attaching specific risk levels to low exposures. The present paper describes a quantitative approach to modeling nonquantal neurotoxic effects for risk assessment, which can be used to obtain results similar to the familiar results obtained in risk assessment for carcinogenicity and developmental toxicity. The steps involved in implementing the process are discussed, with particular attention being given to the critical step of defining an adverse neurologic effect. An experimental data set is used to illustrate the methodology.

A Simple Data Transformation for Estimating Benchmark Doses in Developmental Toxicity Experiments

Developmental anomalies induced by toxic chemicals may be identified using laboratory experiments with rats, mice or rabbits. Multinomial responses of fetuses from the same mother are often positively correlated, resulting in overdispersion relative to multinomial variation. In this article, a simple data transformation based on the concept of generalized design effects due to Rao-Scott is proposed for dose-response modeling of developmental toxicity. After scaling the original multinomial data using the average design effect, standard methods for analysis of uncorrelated multinomial data can be applied. Benchmark doses derived using this approach are comparable to those obtained using generalized estimating equations with an extended Dirichlet-trinomial covariance function to describe the dispersion of the original data. This empirical agreement, coupled with a large sample theoretical justification of the Rao-Scott transformation, confirms the applicability of the statistical methods proposed in this article for developmental toxicity risk assessment.

Critical Periods of Exposure and Developmental Outcome

The most unique aspect of the Held of developmental toxicology, which sets it apart from all other areas of toxicologic investigation, is the rapidly changing susceptibility of the conceptus to insult. In this presentation, an overview of the changing susceptibility of the conceptus will be given, with a discussion of the difficulties this presents for risk assessment. Prenatal development of all mammalian species can be divided up into the preim-plantation, embryonic, and fetal periods, with each period possessing its own characteristic susceptibility and unique response to prenatal insult. Most developmental toxicity studies have focused on the embryonic period, with malformations as the outcome of major concern. As understanding of mammalian development has increased, it is now clear that susceptibility to functional impairments, as well as to physiologic alterations, also exist during the embryonic and fetal period, which have major consequences for the offspring. The pattern of outcome can vary dramatically depending on the time of exposure; differences in exposure intervals as short as one day can result in a shifting of the pattern of malformation and even determine whether malformations, embryonic death, or functional impairment occurs. Consequently, in considering risk assessment for developmental toxicity, the time of exposure has to be taken into consideration, as well as the level of exposure.

Dose-Response Assessment for Developmental Toxicity: I. Characterization of Database and Determination of No Observed Adverse Effect Levels

Dose-Response Assessment for Developmental Toxicity. I. Characterization of Database and Determination of No Observed Adverse Effect Levels. Faustman, E. M., Allen, B. C., Kavlock, R. J., and Kimmel. C. A. (1994). Fundam. Appl. Toxicol. 23, 478-486. Developmental toxicity risk assessment currently relies on the estimation of reference doses (RfD DTs) or reference concentrations (RfC DTs) based on the use of no observed adverse effect levels (NOAELs) and uncertainty factors. The benchmark dose (BMD) has been proposed as an alternative basis for reference value calculations. A large database of 246 developmental toxicity experiments (Segment II-type studies) representing 1825 data subsets for various endpoints was compiled for use in comparing NOAEL and BMD approaches to developmental toxicity risk assessment. This paper describes the characteristics of the database used and the estimation of NOAELs using several approaches. For each endpoint evaluated, two NOAELs were calculated using the NOSTASOT procedure (Tukey et al., 1985). The first NOAEL calculation, the QNOAEL, was based on a quantal response where a litter was defined as "affected" if one or more fetuses or implants in the litter had the endpoint of interest. The second NOAEL calculation, the CNOAEL, was based on the proportion of fetuses or implants affected within each litter and was treated as a continuous response variable. Fifty-seven percent of the 246 experiments had at least one endpoint that showed a significant trend with dose. A total of 386 data sets were significant with respect to both the quantal and continuous test of trend. An additional 44 data sets were identified with significant trend only by the quantal approach whereas 177 additional data sets were identified with significant trend tests only by the continuous approach. Thus, the continuous approach appeared to be more powerful in detecting dose-related toxicity, but the patterns detected by the two approaches differed. QNOAELs and CNOAELs were compared by examining the degree to which they selected the same dose group. For 98% of the 386 data sets with both significant continuous and quantal trend tests, the CNOAEL was within one dose level of the QNOAEL. For data sets having significant continuous and/or quantal trend tests, 99% of the two NOAELs were within two dose levels. Twenty of the NTP studies were reviewed for comparison of "expert" versus statistically derived NOAELs. Most of the 360 NOAELs derived were identical for these two approaches; for the 8% that were different, approximately 80% were within one dose level. Thus, the statistically derived NOAELs that were used as the basis of our data comparisons were reflective of the typical methods used in deriving NOAELs. Compilation and characterization of such a large database of Segment II developmental toxicity experiments provide us with an opportunity to evaluate new quantitative approaches for developmental toxicity risk assessment and to make decisions about appropriate approaches for evaluation.

Dose-Response Assessment for Developmental Toxicity: II. Comparison of Generic Benchmark Dose Estimates with No Observed Adverse Effect Levels

Dose-Response Assessment for Developmental Toxicity. II. Comparison of Generic Benchmark Dose Estimates with No Observed Adverse Effect Levels. Allen, B. C., Kavlock, R. J., Kimmel, C. A., and Faustman, E. M. (1994). Fundam. Appl. Toxicol. 23, 487-495. Developmental toxicity risk assessment currently relies on the estimation of reference doses (RfD DTs) or reference concentrations (RfC DTs) based on the use of no observed adverse effect levels (NOAELs) divided by uncertainty factors (UFs). The benchmark dose (BMD) has been proposed as an alternative basis for reference value calculations. A large database of 246 developmental toxicity experiments representing 1825 endpoints related to dead implants or malformed fetuses has been compiled for use in evaluating alternative approaches to developmental toxicity risk assessment. Using this database we have compared two approaches for BMD estimation with each other and with corresponding statistically derived NOAELs. Comparisons have been based on proportion of affected litters (litters with one or more affected offspring, a quantal response variable) and on the proportion of affected offspring within each litter (a continuous response variable). A quantal Weibull model was used to calculate generic BMDs for the quantal response variable (QBMDs) and a continuous power model was used to calculate generic BMDs for the continuous response variable (CBMDs) at three levels of additional risk (10, 5, and 1%). CBMD 05s (continuous benchmark doses for 5% risk) and CNOAELs (statistically derived NOAELs based on the continuous response variable) were similar, with over 98% of the data subsets having CBMD 05 and CNOAEL values that differed by less than an order of magnitude. In contrast, QNOAELs tended to be greater than corresponding QBMD 10s. The observed conservatism of the QBMD values relative to the corresponding CBMD values was attributed to two factors, lower maximum likelihood estimates for the quantal model and wider confidence intervals around the maximum likelihood estimates, compared to the continuous model. Comparisons of different quantitative dose-response assessments for developmental toxicity experiments should help to identify appropriate risk assessment approaches for developmental toxicity risk assessment.

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.

Dose—Response Assessment for Developmental Toxicity

Developmental toxicity risk assessment currently relies on the estimation of reference doses (RfDDTs) or reference concentrations (RfDDTs) based on the use of no observed adverse effect levels (NOAELs) divided by uncertainty factors (UFs). The benchmark dose (BMD) has been proposed as an alternative basis for reference value calculations. A large database of 246 developmental toxicity experiments representing 1825 endpoints related to dead implants or malformed fetuses has been compiled for use in evaluating alternative approaches to developmental toxicity risk assessment. Using this database we have compared two approaches for BMD estimation with each other and with corresponding statistically derived NOAELs. Comparisons have been based on proportion of affected litters (litters with one or more affected offspring, a quantal response variable) and on the proportion of affected offspring within each litter (a continuous response variable). A quantal Weibull model was used to calculate generic BMDs for the quantal response variable (QBMDs) and a continuous power model was used to calculate generic BMDs for the continuous response variable (CBMDs) at three levels of additional risk (10, 5, and 1%). CBMD05s (continuous benchmark doses for 5% risk) and CNOAELs (statistically derived NOAELs based on the continuous response variable) were similar, with over 98% of the data subsets having CBMD05 and CNOAEL values that differed by less than an order of magnitude. In contrast, QNOAELs tended to be greater than corresponding QBMD10s. The observed conservatism of the QBMD values relative to the corresponding CBMD values was attributed to two factors, lower maximum likelihood estimates for the quantal model and wider confidence intervals around the maximum likelihood estimates, compared to the continuous model. Comparisons of different quantitative dose-response assessments for developmental toxicity experiments should help to identify appropriate risk assessment approaches for developmental toxicity risk assessment.

Developmental Toxicity Risk Assessment: A Rough Sets Approach

A rough-sets approach was applied to a data set consisting of animal study results and other compound characteristics to generate local and global (certain/possible) sets of rules for prediction of developmental toxicity in human subjects. A modified version of the rough-sets approach is proposed to allow the construction of an approximate set of rules to use for prediction in a manner similar to that of discriminant analysis. The modified rough-sets approach is superior in predictability to the original form of rough-sets methodology. In comparison to discriminant analysis, modified rough sets (approximate rules) appear to be better in overall classification, sensitivity, positive and negative predictive values. The findings were supported by applying the modified rough sets and discriminant analysis on a test data set generated from the original data set by using a resampling plan.