Mode Of Action Information Research Articles

Quantitative Integration of Mode of Action Information in Dose-Response Modeling and POD Estimation for Nonmutagenic Carcinogens: A Case Study of TCDD.

Traditional dose-response assessment applies different low-dose extrapolation methods for cancer and noncancer effects and assumes that all carcinogens are mutagenic unless strong evidence suggests otherwise. Additionally, primarily focusing on one critical effect, dose-response modeling utilizes limited mode of action (MOA) data to inform low-dose risk. We aimed to build a dose-response modeling framework that continuously extends the curve into the low-dose region via a quantitative integration of MOA information and to estimate MOA-based points of departure (PODs) for nonmutagenic carcinogens. 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) was used as an example to demonstrate the new dose-response modeling framework. There were three major steps included: a) identifying and extracting key quantifiable events (KQEs), b) calculating essential doses that sequentially activate KQEs using the benchmark dose (BMD) methodology, and c) characterizing pathway dose-response relationship for MOA-based POD estimation. We identified and extracted six KQEs and corresponding essential events composing the MOA of TCDD-induced liver tumors. With the essential doses estimated from the BMD method using various settings, three link functions were applied to model the pathway dose-response relationship. Given a toxicologically plausible definition of adversity, an MOA-based POD was derived from the pathway dose-response curve. The estimated MOA-based PODs were generally comparable with traditional PODs and can be further used to calculate reference doses (RfDs). The proposed framework quantitatively integrated mechanistic information in the modeling process and provided a promising strategy to harmonize cancer and noncancer dose-response assessment through pathway dose-response modeling. However, the framework can also be limited by data availability and the understanding of the underlying mechanism. https://doi.org/10.1289/EHP12677.

A mode of action-based probabilistic framework of dose-response assessment for nonmutagenic liver carcinogens: a case study of PCB-126.

A main function of dose-response assessment is to estimate a "safe" dose in the target population to support chemical risk assessment. Typically, a "safe" dose is developed differently for cancer and noncancer effects based on a 2-step procedure, ie, point of departure (POD) derivation and low-dose extrapolation. However, the current dose-response assessment framework is criticized for its dichotomized strategy without integrating the mode of action (MOA) information. The objective of this study was, based on our previous work, to develop a MOA-based probabilistic dose-response framework that quantitatively synthesizes a biological pathway in a dose-response modeling process to estimate the risk of chemicals that have carcinogenic potential. 3,3',4,4',5-Pentachlorobiphenyl (PCB-126) was exemplified to demonstrate our proposed approach. There were 4 major steps in the new modeling framework, including (1) key quantifiable events (KQEs) identification and extraction, (2) essential dose calculation, (3) MOA-based POD derivation, and (4) MOA-based probabilistic reference dose (RfD) estimation. Compared with reported PODs and traditional RfDs, the MOA-based estimates derived from our approach were comparable and plausible. One key feature of our approach was the use of overall MOA information to build the dose-response relationship on the entire dose continuum including the low-dose region. On the other hand, by adjusting uncertainty and variability in a probabilistic manner, the MOA-based probabilistic RfDs can provide useful insights of health protection for the specific proportion of population. Moreover, the proposed framework had important potential to be generalized to assess different types of chemicals other than nonmutagenic carcinogens, highlighting its utility to improve current chemical risk assessment.

Transforming early pharmaceutical assessment of genotoxicity: applying statistical learning to a high throughput, multi end point in vitro micronucleus assay

To provide a comprehensive analysis of small molecule genotoxic potential we have developed and validated an automated, high-content, high throughput, image-based in vitro Micronucleus (IVM) assay. This assay simultaneously assesses micronuclei and multiple additional cellular markers associated with genotoxicity. Acoustic dosing (≤ 2 mg) of compound is followed by a 24-h treatment and a 24-h recovery period. Confocal images are captured [Cell Voyager CV7000 (Yokogawa, Japan)] and analysed using Columbus software (PerkinElmer). As standard the assay detects micronuclei (MN), cytotoxicity and cell-cycle profiles from Hoechst phenotypes. Mode of action information is primarily determined by kinetochore labelling in MN (aneugencity) and γH2AX foci analysis (a marker of DNA damage). Applying computational approaches and implementing machine learning models alongside Bayesian classifiers allows the identification of, with 95% accuracy, the aneugenic, clastogenic and negative compounds within the data set (Matthews correlation coefficient: 0.9), reducing analysis time by 80% whilst concurrently minimising human bias. Combining high throughput screening, multiparametric image analysis and machine learning approaches has provided the opportunity to revolutionise early Genetic Toxicology assessment within AstraZeneca. By multiplexing assay endpoints and minimising data generation and analysis time this assay enables complex genotoxicity safety assessments to be made sooner aiding the development of safer drug candidates.

Key event-informed risk models for benzene-induced acute myeloid leukaemia

Occupational exposure to benzene at levels of 10 ppm or more has been associated with increased risk of acute myeloid leukaemia (AML). The mode of action (MOA) for AML development leading to mortality is anticipated to include multiple earlier key events, which can be observed in hematotoxicity and genetic toxicity in peripheral blood of exposed workers. Prevention of these early events would lead to prevention of the apical, adverse outcomes, the morbidity and mortality caused by the myelodysplastic syndromes (MDS) and AML. Incorporation of key event information should modify the risk model, but few modification approaches have been suggested. To that end, two approaches to risk model modification are described that use sub-linear and segmented linear increases in risk below key events, while maintaining a linear increase in AML mortality risk beginning at 2 ppm, the lowest observed adverse effect concentration (LOAEC) identified for hemato- and geno- toxicity in high quality studies of human occupational exposure. Below 2 ppm two different modification approaches to quantitative risk models were applied: a continuously decreasing slope model and a segmented modification in slope. These two approaches provide greater flexibility to incorporate MOA information in risk model development and selection.

Application of the comparison approach to open TG-GATEs: A useful toxicogenomics tool for detecting modes of action in chemical risk assessment

Mode of action information is one of the key components for chemical risk assessment as mechanistic insight leads to better understanding of potential adverse health effects of a chemical. This insight greatly facilitates assessment of human relevance and enhances the use of non-animal methods for risk assessment, as it ultimately enables extrapolation from initiating events to adverse effects. Recently, we reported an in vitro toxicogenomics comparison approach to categorize (non-)genotoxic carcinogens according to similarities in their proposed modes of action. The present study aimed to make this comparison approach generally applicable, allowing comparison of outcomes across different studies. The resulting further developed comparison approach was evaluated through application to toxicogenomics data on 18 liver toxicants in human and rat primary hepatocytes from the Open TG-GATEs database. The results showed sensible matches between compounds with (partial) overlap in mode of action, whilst matches for compounds with different modes of action were absent. Comparison of the results across species revealed pronounced and relevant differences between primary rat and human hepatocytes, underpinning that information on mode of action enhances assessment of human relevance. Thus, we demonstrate that the comparison approach now is generally applicable, facilitating its use as tool in mechanism-based risk assessment.

Development of a bioanalytical test battery for water quality monitoring: Fingerprinting identified micropollutants and their contribution to effects in surface water

Surface waters can contain a diverse range of organic pollutants, including pesticides, pharmaceuticals and industrial compounds. While bioassays have been used for water quality monitoring, there is limited knowledge regarding the effects of individual micropollutants and their relationship to the overall mixture effect in water samples. In this study, a battery of in vitro bioassays based on human and fish cell lines and whole organism assays using bacteria, algae, daphnids and fish embryos was assembled for use in water quality monitoring. The selection of bioassays was guided by the principles of adverse outcome pathways in order to cover relevant steps in toxicity pathways known to be triggered by environmental water samples. The effects of 34 water pollutants, which were selected based on hazard quotients, available environmental quality standards and mode of action information, were fingerprinted in the bioassay test battery. There was a relatively good agreement between the experimental results and available literature effect data. The majority of the chemicals were active in the assays indicative of apical effects, while fewer chemicals had a response in the specific reporter gene assays, but these effects were typically triggered at lower concentrations. The single chemical effect data were used to improve published mixture toxicity modeling of water samples from the Danube River. While there was a slight increase in the fraction of the bioanalytical equivalents explained for the Danube River samples, for some endpoints less than 1% of the observed effect could be explained by the studied chemicals. The new mixture models essentially confirmed previous findings from many studies monitoring water quality using both chemical analysis and bioanalytical tools. In short, our results indicate that many more chemicals contribute to the biological effect than those that are typically quantified by chemical monitoring programs or those regulated by environmental quality standards. This study not only demonstrates the utility of fingerprinting single chemicals for an improved understanding of the biological effect of pollutants, but also highlights the need to apply bioassays for water quality monitoring in order to prevent underestimation of the overall biological effect.

Machine learning algorithms for mode-of-action classification in toxicity assessment

BackgroundReal Time Cell Analysis (RTCA) technology is used to monitor cellular changes continuously over the entire exposure period. Combining with different testing concentrations, the profiles have potential in probing the mode of action (MOA) of the testing substances.ResultsIn this paper, we present machine learning approaches for MOA assessment. Computational tools based on artificial neural network (ANN) and support vector machine (SVM) are developed to analyze the time-concentration response curves (TCRCs) of human cell lines responding to tested chemicals. The techniques are capable of learning data from given TCRCs with known MOA information and then making MOA classification for the unknown toxicity. A novel data processing step based on wavelet transform is introduced to extract important features from the original TCRC data. From the dose response curves, time interval leading to higher classification success rate can be selected as input to enhance the performance of the machine learning algorithm. This is particularly helpful when handling cases with limited and imbalanced data. The validation of the proposed method is demonstrated by the supervised learning algorithm applied to the exposure data of HepG2 cell line to 63 chemicals with 11 concentrations in each test case. Classification success rate in the range of 85 to 95 % are obtained using SVM for MOA classification with two clusters to cases up to four clusters.ConclusionsWavelet transform is capable of capturing important features of TCRCs for MOA classification. The proposed SVM scheme incorporated with wavelet transform has a great potential for large scale MOA classification and high-through output chemical screening.Electronic supplementary materialThe online version of this article (doi:10.1186/s13040-016-0098-0) contains supplementary material, which is available to authorized users.

Consideration of non-linear, non-threshold and threshold approaches for assessing the carcinogenicity of oral exposure to hexavalent chromium

A non-linear approach, consistent with available mode of action (MOA) data, is most scientifically defensible for assessing the carcinogenicity of oral exposure to hexavalent chromium (CrVI). Accordingly, the current paper builds upon previous studies (Haney, 2015a, 2015b) to first develop a non-linear, non-threshold approach as well as a non-linear threshold approach for assessing the oral carcinogenicity of CrVI, and then utilizes available MOA analyses and information for selection of the most scientifically-supported approach. More specifically, a non-linear, non-threshold dose–response function was developed that adequately describes the non-linearity predicted for potential human excess risk versus oral dose due to the sub-linear relationship between oral dose and internal dose (added mg Cr/kg target tissue) across environmentally-relevant doses of regulatory interest. Additionally, benchmark dose modeling was used to derive a reference dose (RfD of 0.003 mg/kg-day) with cytotoxicity-induced regenerative hyperplasia as a key precursor event to carcinogenesis in the mouse small intestine. This RfD value shows remarkable agreement with that published previously (0.006 mg/kg-day) based on a more scientifically-sophisticated, physiologically-based pharmacokinetic modeling approach (Thompson et al., 2013b). The RfD approach is the most scientifically-defensible approach based on the weight-of-evidence of available MOA information and analyses conducted for the most scientifically-supported MOA.

IWGT report on quantitative approaches to genotoxicity risk assessment I. Methods and metrics for defining exposure–response relationships and points of departure (PoDs)

This report summarizes the discussion, conclusions, and points of consensus of the IWGT Working Group on Quantitative Approaches to Genetic Toxicology Risk Assessment (QWG) based on a meeting in Foz do Iguaçu, Brazil October 31–November 2, 2013. Topics addressed included (1) the need for quantitative dose–response analysis, (2) methods to analyze exposure–response relationships & derive point of departure (PoD) metrics, (3) points of departure (PoD) and mechanistic threshold considerations, (4) approaches to define exposure-related risks, (5) empirical relationships between genetic damage (mutation) and cancer, and (6) extrapolations across test systems and species. This report discusses the first three of these topics and a companion report discusses the latter three. The working group critically examined methods for determining point of departure metrics (PoDs) that could be used to estimate low-dose risk of genetic damage and from which extrapolation to acceptable exposure levels could be made using appropriate mode of action information and uncertainty factors. These included benchmark doses (BMDs) derived from fitting families of exponential models, the No Observed Genotoxic Effect Level (NOGEL), and “threshold” or breakpoint dose (BPD) levels derived from bilinear models when mechanistic data supported this approach. The QWG recognizes that scientific evidence suggests that thresholds below which genotoxic effects do not occur likely exist for both DNA-reactive and DNA-nonreactive substances, but notes that small increments of the spontaneous level cannot be unequivocally excluded either by experimental measurement or by mathematical modeling. Therefore, rather than debating the theoretical possibility of such low-dose effects, emphasis should be placed on determination of PoDs from which acceptable exposure levels can be determined by extrapolation using available mechanistic information and appropriate uncertainty factors. This approach places the focus on minimization of the genotoxic risk, which protects against the risk of the development of diseases resulting from the genetic damage. Based on analysis of the strengths and weaknesses of each method, the QWG concluded that the order of preference of PoD metrics is the statistical lower bound on the BMD>the NOGEL>a statistical lower bound on the BPD. A companion report discusses the use of these metrics in genotoxicity risk assessment, including scaling and uncertainty factors to be considered when extrapolating below the PoD and/or across test systems and to the human.

A Mode-of-Action Approach for the Identification of Genotoxic Carcinogens

Distinguishing between clastogens and aneugens is vital in cancer risk assessment because the default assumption is that clastogens and aneugens have linear and non-linear dose-response curves, respectively. Any observed non-linearity must be supported by mode of action (MOA) analyses where biological mechanisms are linked with dose-response evaluations. For aneugens, the MOA has been well characterised as disruptors of mitotic machinery where chromosome loss via micronuclei (MN) formation is an accepted endpoint used in risk assessment. In this study we performed the cytokinesis-block micronucleus assay and immunofluorescence mitotic machinery visualisation in human lymphoblastoid (AHH-1) and Chinese Hamster fibroblast (V79) cell lines after treatment with the aneugen 17-β-oestradiol (E2). Results were compared to previously published data on bisphenol-A (BPA) and Rotenone data. Two concentration-response approaches (the threshold-[Td] and benchmark-dose [BMD] approaches) were applied to derive a point of departure (POD) for in vitro MN induction. BMDs were also derived from the most sensitive carcinogenic endpoint. Ranking comparisons of the PODs from the in vitro MN and the carcinogenicity studies demonstrated a link between these two endpoints for BPA, E2 and Rotenone. This analysis was extended to include 5 additional aneugens, 5 clastogens and 3 mutagens and further concentration and dose-response correlations were observed between PODs from the in vitro MN and carcinogenicity. This approach is promising and may be further extended to other genotoxic carcinogens, where MOA and quantitative information from the in vitro MN studies could be used in a quantitative manner to further inform cancer risk assessment.

Development of a cancer-based chronic inhalation reference value for hexavalent chromium based on a nonlinear-threshold carcinogenic assessment

The carcinogenicity of hexavalent chromium(CrVI) is of significant interest to regulatory agencies for the protection of public health and to industry. Additionally, the mode of action (MOA) and conditions under which CrVI may induce carcinogenicity (e.g., reductive capacity considerations) have recently been the subject of significant scientific debate. Epidemiological data supported by data relevant to the carcinogenic MOA support considering nonlinear-threshold carcinogenic assessments for comparison to default linear low-dose extrapolation approaches. This study reviews epidemiological studies available in the scientific literature and conducts additional statistical dose–response analyses to identify potential carcinogenic thresholds and points of departure (PODs) in the context of supportive MOA information for a nonlinear-threshold inhalation carcinogenic assessment. Dosimetric adjustments and application of appropriate uncertainty factors (total UF of 30) to the selected cumulative exposure POD results in a cancer-based chronic inhalation reference value (ReV) of 0.24μgCrVI/m3. This chronic ReV is 300 times higher than the 1 in 100,000 excess cancer risk air concentration of 8E-04μg/m3 based on USEPA’s unit risk factor.

A lifestage‐specific approach to hazard and dose‐response characterization for children's health risk assessment

In 2006, the U.S. EPA published a report entitled A Framework for Assessing Health Risks of Environmental Exposures to Children (hereafter referred to as the "Framework") describing a lifestage approach to risk assessment that includes the evaluation of existing data from a temporal perspective (i.e., the timing of both the exposure and the outcome). This article summarizes the lifestage-specific issues discussed in the Framework related to the qualitative and the quantitative hazard and dose-response characterization. Lifestage-specific hazard characterization includes an evaluation of relevant human and experimental animal studies, focusing on the identification of critical windows of development (i.e., exposure intervals of maximum susceptibility) for observed outcomes, evaluation of differential exposure at individual lifestages, the relevance and impact of lifestage-specific toxicokinetic and toxicodynamic data, mode of action information, variability and latency of effects from early lifestage exposure, and describing uncertainties. The interpretation of the hazard data to determine the strength of association between early life exposures and the timing and type of outcomes depends upon the overall weight of evidence. Lifestage-specific dose-response characterization relies on the identification of susceptible lifestages in order to quantify health risk, information on the point of departure, key default assumptions, and descriptions of uncertainty, sensitivity, and variability. Discussion of the strength and limitations of the hazard and dose-response data provides a basis for confidence in risk determinations. Applying a lifestage approach to hazard and dose-response characterization is likely to improve children's health risk assessment by identifying data gaps and providing a better understanding of sources of uncertainty.

State-of-the-Science Workshop Report: Issues and Approaches in Low-Dose–Response Extrapolation for Environmental Health Risk Assessment

Low-dose extrapolation model selection for evaluating the health effects of environmental pollutants is a key component of the risk assessment process. At a workshop held in Baltimore, Maryland, on 23–24 April 2007, sponsored by U.S. Environmental Protection Agency and Johns Hopkins Risk Sciences and Public Policy Institute, a multidisciplinary group of experts reviewed the state of the science regarding low-dose extrapolation modeling and its application in environmental health risk assessments. Participants identified discussion topics based on a literature review, which included examples for which human responses to ambient exposures have been extensively characterized for cancer and/or noncancer outcomes. Topics included the need for formalized approaches and criteria to assess the evidence for mode of action (MOA), the use of human versus animal data, the use of MOA information in biologically based models, and the implications of interindividual variability, background disease processes, and background exposures in threshold versus nonthreshold model choice. Participants recommended approaches that differ from current practice for extrapolating high-dose animal data to low-dose human exposures, including categorical approaches for integrating information on MOA, statistical approaches such as model averaging, and inference-based models that explicitly consider uncertainty and interindividual variability.

Mode of Action Frameworks: A Critical Analysis

Mode of action (MOA) information is increasingly being applied in human health risk assessment. The MOA can inform issues such as the relevance of observed effects in laboratory animals to humans, and the variability of response within the human population. Several collaborative groups have developed frameworks for analyzing and utilizing MOA information in human health risk assessment of environmental carcinogens and toxins, including the International Programme on Chemical Safety, International Life Sciences Institute, and U.S. Environmental Protection Agency. With the goal of identifying gaps and opportunities for progress, we critically evaluate several of these MOA frameworks. Despite continued improvement in incorporating biological data in human health risk assessment, several notable challenges remain. These include articulation of the significant role of scientific judgment in establishing an MOA and its relevance to humans. In addition, binary (yes/no) decisions can inappropriately exclude consideration of data that may nonetheless be informative to the overall assessment of risk. Indeed, the frameworks lack a broad consideration of known causes of human disease and the potential for chemical effects to act additively with these as well as endogenous background processes. No integrated analysis of the impact of multiple MOAs over the same dose range, or of varying MOAs at different life stages, is included. Separate consideration of each MOA and outcome limits understanding of how multiple metabolites, modes, and toxicity pathways contribute to the toxicological profile of the chemical. An extension of the analyses across outcomes with common modes is also needed.

Implications of Research on Assays to Characterize Thyroid Toxicants

Many aspects of thyroid endocrinology are very well conserved across vertebrate taxa. These aspects include thyroid hormone chemistry, the mechanism of its synthesis, and the proteins involved in these processes. In addition, the system by which the hormone is delived from the thyroid gland to target cells, including transport and regulation within the hypothalamic-pituitary-thyroid (HPT) axis, and the proteins that regulate the different components of this delivery system appear to be highly conserved across the vertebrates. Finally, the receptors that mediate thyroid hormone action and the roles thyroid hormone plays are very similar among the vertebrates. Thus, the goal of this chapter is to provide a brief synopsis of the literature supporting existing screening and testing strategies in different vertebrate taxa, and to provide insight into the strengths, weaknesses, and likely changes over time. It was determined during this review that, because of the complexity of the thyroid system, it is unlikely that current in vitro assays for thyroid toxicity will be able to sufficiently replace in vivo assays for thyroid toxicants. However, the in vitro assays serve an important purpose in providing mode of action information and could provide potential screening tools, and should continue to be developed for use. Moreover, because in vivo assays are added on to preexisting reproductive or developmental screens and tests, there are no additional animals required for the in vivo assays. Specific in vitro assays were identified for development, including the thyroid receptor binding and activation assays, and in vitro assays to evaluate thyroid hormone action. Some in vivo endpoints suggested for further research included neuronal differentiation and migration, measures of histogenesis, and measures for thyroid gland thyroid hormone content, which may be more sensitive indicators of TSH stimulation. The most commonly used endpoints currently used to monitor thyroid function are thyroid hormone levels (T3 and T4), TSH, thyroid gland weight, and thyroid histology. Thyroid endocrinology is rapidly advancing and new discoveries will certainly warrant incorporation into future assays. The development of additional endpoints that measure thyroid hormone's actions peripheral to the HPT axis and the development of new reagents for nonmammalian vertebrate species will significantly improve the ability of today's assays to detect chemicals that disrupt the thyroid system in multiple vertebrate species. It is our hope that this series of thyroid articles will provide regulators and research scientists the information needed for each individual to identify the assays and endpoints most suited for their specific purposes.

Report of an independent peer review of an acrylonitrile risk assessment

A peer review panel made up of experts in toxicology, epidemiology, cancer mode of action (MOA), cancer mechanisms, carcinogenicity, genotoxicity, dose-response, US Environmental Protection Agency (EPA) cancer and noncancer methods, pharmacokinetic modeling and acrylonitrile, met on 22-23 September 2003 in Cincinnati, OH. The purpose of the meeting was to provide an independent review of a risk assessment of acrylonitrile that had been prepared by the Acrylonitrile Group (AN Group). Toxicology Excellence for Risk Assessment (TERA) organized the peer review and selected the panel. The panel discussed the toxicity and epidemiology literature of acrylonitrile and MOA information, and reached conclusions regarding its MOA, weight of evidence (WOE) for carcinogenicity, preferred approach for dose-response assessment and risk values. This paper summarizes the discussion and conclusions of the panel regarding the acrylonitrile assessment. Subsequent to the peer review, the authors of the acrylonitrile assessment revised their report and the panel reviewed the revised report. A manuscript of the revised assessment is being published in Regulatory Toxicology and Pharmacology.

Overview: Using Mode of Action and Life Stage Information to Evaluate the Human Relevance of Animal Toxicity Data

A complete mode of action human relevance analysis—as distinct from mode of action (MOA) analysis alone—depends on robust information on the animal MOA, as well as systematic comparison of the animal data with corresponding information from humans. In November 2003, the International Life Sciences Institute's Risk Science Institute (ILSI RSI) published a 2-year study using animal and human MOA information to generate a four-part Human Relevance Framework (HRF) for systematic and transparent analysis of MOA data and information. Based mainly on non-DNA-reactive carcinogens, the HRF features a “concordance” analysis of MOA information from both animal and human sources, with a focus on determining the appropriate role for each MOA data set in human risk assessment. With MOA information increasingly available for risk assessment purposes, this article illustrates the further applicability of the HRF for reproductive, developmental, neurologic, and renal endpoints, as well as cancer. Based on qualitative and quantitative MOA considerations, the MOA/human relevance analysis also contributes to identifying data needs and issues essential for the dose-response and exposure assessment steps in the overall risk assessment.

Use of genetic toxicology information for risk assessment

Genetic toxicology data are used worldwide in regulatory decision-making. On the 25th anniversary of Environmental and Molecular Mutagenesis, we think it is important to provide a brief overview of the currently available genetic toxicity tests and to outline a framework for conducting weight-of-the-evidence (WOE) evaluations that optimize the utility of genetic toxicology information for risk assessment. There are two major types of regulatory decisions made by agencies such as the Environmental Protection Agency (EPA) and the Food and Drug Administration (FDA): (1) the approval and registration of pesticides, pharmaceuticals, medical devices, and medical-use products, and (2) the setting of standards for acceptable exposure levels in air, water, and food. Genetic toxicology data are utilized for both of these regulatory decisions. The current default assumption for regulatory decisions is that chemicals that are shown to be genotoxic in standard tests are, in fact, capable of causing mutations in humans (in somatic and/or germ cells) and that they contribute to adverse health outcomes via a "genotoxic/mutagenic" mode of action (MOA). The new EPA Guidelines for Carcinogen Risk Assessment [Guidelines for Carcinogen Risk Assessment, USEPA, 2005, EPA Publication No. EPA/630/P-03/001F] emphasize the use of MOA information in risk assessment and provide a framework to help identify a possible mutagenic and/or nonmutagenic MOA for potential adverse effects. An analysis of the available genetic toxicity data is now, more than ever, a key component to consider in the derivation of an MOA for characterizing observed adverse health outcomes such as cancer. We provide our perspective and a two-step strategy for evaluating genotoxicity data for optimal use in regulatory decision-making. The strategy includes integration of all available information and provides, first, for a WOE analysis as to whether a chemical is a mutagen, and second, whether an adverse health outcome is mediated via a mutagenic MOA.

Role of repellents in vector control and disease prevention.

Repellents are an inexpensive and practical means of protection against nuisance and disease vector arthropods in conjunction with or when other control measures are not feasible. Appropriate selection of skin and/or clothing repellents along with proper wear of clothing can provide adequate protection from biting arthropods, and are available in a wide variety of forms including lotions, creams, foams, soaps, aerosols, sticks, and towellettes. A coordinated effort among different research groups associated with advances in the science of insect repellents such as mode of action information, doses of repellents to generate threshold level responses and controlled release delivery mechanisms, may help in understanding the mechanisms by which repellents work. This in turn may revolutionize the development of repellents for personal protection and their use in vector control.