Classification according to chemical structure, mutagenicity to Salmonella and level of carcinogenicity of a further 42 chemicals tested for carcinogenicity by the U.S. National Toxicology Program

This paper is an extension and update of an earlier review published in this journal (Ashby and Tennant, 1988). A summary of the rodent carcinogenicity bioassay data on a further 42 chemicals tested by the U.S. National Toxicology Program (NTP) is presented. An evaluation of each chemical for structural alerts to DNA-reactivity is also provided, together with a summary of its mutagenicity to Salmonella. The 42 chemicals were numbered and evaluated as an extension of the earlier analysis of 222 NTP chemicals. The activity patterns and conclusions derived from the earlier study remain unchanged for the larger group of 264 chemicals. Based on the extended database of 264 NTP chemicals, the sensitivity of the Salmonella assay for rodent carcinogens is 58% and the specificity for the non-carcinogens is 73%. A total of 32 chemicals were defined as equivocal for carcinogenicity and, of these, 11 (34%) are mutagenic to Salmonella. An evaluation is made of instances where predictions of carcinogenicity, based on structural alerts, disagree with the Salmonella mutagenicity result (12% of the database). The majority of the disagreements are for structural alerts on non-mutagens, and that places these alerts as a sensitive primary screen with a specificity lower than that of the Salmonella assay. That analysis indicates some need for assays complementary to the Salmonella test when screening for potential genotoxic carcinogens. It also reveals that the correlation between structural alerts and mutagenicity to Salmonella is probably greater than 90%. Chemicals predicted to show Michael-type alkylating activity (i.e., CH2 = CHX; where X = an electron-withdrawing group, e.g. acrylamide) have been confirmed as a structural alert, and the halomethanes (624 are possible) have been classified as structurally-alerting. To this end an extended carcinogen-alert model structure is presented. Among the 138 NTP carcinogens now reviewed, 45 (33%) are non-mutagenic to Salmonella and possess a chemical structure that does not alert to DNA-reactivity. These carcinogens therefore either illustrate the need for complementary genetic screening tests to the Salmonella assay, or they represent the group of non-genotoxic carcinogens referred to most specifically by Weisburger and Williams (1981); the latter concept is favoured.     

Predicting chemical carcinogenesis in rodents: The state of the art in light of a comparative exercise

Within a recent comparative exercise, different approaches to the prediction of rodent carcinogenicity were challenged on a common set of chemicals bioassayed by the U.S. National Toxicology Program. The approaches were of very different natures. Some prediction systems looked for relationships between carcinogenicity and other, more quickly detectable biological events (activity-activity relationships, AAR). Some approaches tended to find structure-activity relationships (SAR). To give an objective evaluation of the results of the exercise, we have analyzed the rodent results and the predictions with the multivariate data analysis methods. The calculated performances varied according to the adopted carcinogenicity classification of the chemicals. When the four rodent results were summarized into a final + or − call, the Tennant approach (AAR method) showed the best performance (about 75% accuracy), whereas the best SAR systems had 60–65% accuracy. A common limitation of almost all the systems was the lack of specificity (too many false positives). Based on these results, better concordance was obtained when the input information was the very costly (and closer to the final endpoint) biological data, rather than the inexpensive (and farther from the endpoint) knowledge of the chemical structure. However, when the rodent results were summarized into a carcinogenicity classification that maintained, to some extent, the gradation intrinsic to the original experimental data, the performance of the AAR systems declined, and the SAR approaches showed a better performance. The difficulty in evaluating the various approaches was further complicated because of a fundamental difference in the approaches themselves: some approaches were ‘pure’ prediction methods (i.e. their predictions were rigorously based on information not inclusive of carcinogenicity); other approaches (e.g. Tennant, Weisburger) used ‘mixed’ information, inclusive of known carcinogenicity results from experiments performed before the NTP bioassays. As far as the SAR systems are concerned, their sets of predictions showed a fundamental similarity. This happened in spite of the extremely different procedures adopted to treat the chemical formula (initial information): very simple calculations (Benigni), intuition of the experts (Weisburger and Lijinsky), sophisticated computer programs (TOPKAT and CASE). The results of the Bakale Ke method, based on the experimental measurement of the chemical electrophilicity, and of the Salmonella typhimurium mutagenicity assay were similar to the patterns of predictions of the SAR methods.     

Definitive relationships among chemical structure, carcinogenicity and mutagenicity for 301 chemicals tested by the U.S. NTP.

An analysis is presented in which are evaluated correlations among chemical structure, mutagenicity to Salmonella, and carcinogenicity to rats and mice among 301 chemicals tested by the U.S. NTP. Overall, there was a high correlation between structural alerts to DNA reactivity and mutagenicity, but the correlation of either property with carcinogenicity was low. If rodent carcinogenicity is regarded as a singular property of chemicals, then neither structural alerts nor mutagenicity to Salmonella are effective in its prediction. Given this, the database was fragmented and new correlations sought between the derived sub-groups. First, the 301 chemicals were segregated into six broad chemical groupings. Second, the rodent cancer data were partially segregated by target tissue. Using the previously assigned structural alerts to DNA reactivity (electrophilicity), the chemicals were split into 154 alerting chemicals and 147 non-alerting chemicals. The alerting chemicals were split into three chemical groups; aromatic amino/nitro-types, alkylating agents and miscellaneous structurally-alerting groups. The non-alerting chemicals were subjectively split into three broad categories; non-alerting, non-alerting containing a non-reactive halogen group, and non-alerting chemical with minor concerns about a possible structural alert. The tumor data for all 301 chemicals are re-presented according to these six chemical groupings. The most significant findings to emerge from comparisons among these six groups of chemicals were as follows: (a) Most of the rodent carcinogens, including most of the 2-species and/or multiple site carcinogens, were among the structurally alerting chemicals. (b) Most of the structurally alerting chemicals were mutagenic; 84% of the carcinogens and 66% of the non-carcinogens. 100% of the 33 aromatic amino/nitro-type 2-species carcinogens were mutagenic. Thus, for structurally alerting chemicals, the Salmonella assay showed high sensitivity and low specificity (0.84 and 0.33, respectively). (c) Among the 147 non-alerting chemicals less than 5% were mutagenic, whether they were carcinogens or non-carcinogens (sensitivity 0.04).     

Structural basis of carcinogenicity in rodents of genotoxicants and non-genotoxicants

A set of 189 chemicals tested in the National Toxicology Program Cancer Bioassay was subjected to analysis by CASE, the Computer-Automated Structure Evaluation system. In the data set, 63% of the chemicals were carcinogens, approx. 40% of the carcinogens were non-genotoxic, i.e., they possessed neither "structural alerts" for DNA reactivity as defined by Ashby and Tennant, 1988, nor were they mutagenic for Salmonella. The data base can be characterized as a "combined rodent" compilation as chemicals were characterized as "carcinogenic" if they were carcinogenic in either rats or mice or both. CASE identified 23 fragments which accounted for the carcinogenicity, or lack thereof, of most of the chemicals. The sensitivity and specificity were unexpectedly high: 1.00 and 0.86, respectively. Based upon the identified biophores and biophobes, CASE performed exceedingly well in predicting the activity of chemicals not included among the 189 in the original set. CASE predicted correctly the carcinogenicity of non-genotoxic carcinogens thereby suggesting a structural commonality in the action of this group of carcinogens. As a matter of fact biophores restricted to non-genotoxic carcinogens were identified as were "non-electrophilic" biophores shared by genotoxic and non-genotoxic carcinogens. The findings suggest that the CASE program may help in the elucidation of the basis of the action of non-genotoxic carcinogens.     

The second National Toxicology Program comparative exercise on the prediction of rodent carcinogenicity: definitive results

Chemical carcinogenicity has been the target of a large array of attempts to create alternative predictive models, ranging from short-term biological assays (e.g. mutagenicity tests) to theoretical models. Among the theoretical models, the application of the science of structure-activity relationships (SAR) has earned special prominence. A crucial element is the independent evaluation of the predictive ability. In the past decade, there have been two fundamental comparative exercises on the prediction of chemical carcinogenicity, held under the aegis to the US National Toxicology Program (NTP). In both exercises, the predictions were published before the animal data were known, thus using a most stringent criterion of predictivity. We analyzed the results of the first comparative exercise in a previous paper [Mutat. Res. 387 (1997) 35]; here, we present the complete results of the second exercise, and we analyze and compare the prediction sets. The range of accuracy values was quite large: the systems that performed best in this prediction exercise were in the range 60-65% accuracy. They included various human experts approaches (e.g. Oncologic) and biologically based approaches (e.g. the experimental transformation assay in Syrian hamster embryo (SHE) cells). The main difficulty for the structure-activity relationship-based approaches was the discrimination between real carcinogens, and non-carcinogens containing structural alerts (SA) for genotoxic carcinogenicity. It is shown that the use of quantitative structure-activity relationship models, when possible, can contribute to overcome the above problem. Overall, given the uncertainty linked to the predictions, the predictions for the individual chemicals cannot be taken at face value; however, the general level of knowledge available today (especially for genotoxic carcinogens) allows qualified human experts to operate a very efficient priority setting of large sets of chemicals.     

Classification according to chemical structure, mutagenicity to Salmonella and level of carcinogenicity of a further 39 chemicals tested for carcinogenicity by the U.S. National Toxicology Program

This paper is an extension of compilations published previously in this journal. (Ashby and Tennant, 1988; Ashby et al., 1989). A summary of the rodent carcinogenicity bioassay data on a further 39 chemicals tested by the U.S. National Toxicology Program (NTP) is presented. An evaluation of each chemical for structural alerts to DNA-reactivity is also provided, together with a summary of its mutagenicity to Salmonella. Chemicals with an aliphatic nitro group (-C-NO2) have been added to the composite structure of DNA-reactive sub-groups. The 39 chemicals were numbered and evaluated as an extension of the earlier analysis of 264 NTP chemicals. The activity patterns and conclusions derived from the earlier studies are followed by these 39 chemicals, albeit a detailed analysis of the total database of 301 chemicals is reserved for the succeeding paper.     

Cluster analysis in predicting the carcinogenicity of chemicals using short-term assays

Cluster analysis can be a useful tool for exploratory data analysis to uncover natural groupings in data, and initiate new ideas and hypotheses about such groupings. When applied to short-term assay results, it provides and improves estimates for the sensitivity and specificity of assays, provides indications of association between assays and, in turn, which assays can be substituted for one another in a battery, and allows a data base containing test results on chemicals of unknown carcinogenicity to be linked to a data base for which animal carcinogenicity data are available. Cluster analysis was applied to the Gene-Tox data base (which contains short-term test results on chemicals of both known and unknown carcinogenicity). The results on chemicals of known carcinogenicity were different from those obtained when the entire data base was analyzed. This suggests that the associations (and possibly the sensitivities and specificities) which are based on chemicals of known carcinogenicity may not be representative of the true measures. Cluster analysis applied to the total data base should be useful in improving these estimates. Many of the associations between the assays which were found through the use of cluster analysis could be 'validated' based on previous knowledge of the mechanistic basis of the various tests, but some of the associations were unsuspected. These associations may be a reflection of a non-ideal data base. As additional data becomes available and new clustering techniques for handling non-ideal data bases are developed, results from such analyses could play an increasing role in strengthening prediction schemes which utilize short-term tests results to screen chemicals for carcinogenicity, such as the carcinogenicity and battery selection (CPBS) method (Chankong et al., 1985).     

Assembly and preliminary analysis of a genotoxicity data base for predicting carcinogens

With a view to developing methodologies for predicting the carcinogenicity of chemicals on the basis of the results of short-term assays and selecting highly predictive batteries of short-term tests, a data base was assembled. The present is a compilation of data extracted from the reports of Gene-Tox working groups, Salmonella mutagenicity data obtained from the U.S. National Toxicology Program and the Environmental Mutagen Information Center and results from BHK21 transformation assays.     

Development of new structural alerts suitable for chemical category formation for assigning covalent and non-covalent mechanisms relevant to DNA binding

The need to assess the ability of a chemical to act as a mutagen is one of the primary requirements in regulatory toxicology. Several pieces of legislation have led to an increased interest in the use of in silico methods, specifically the formation of chemical categories and read-across for the assessment of toxicological endpoints. One of the key steps in the development of chemical categories for mutagenicity is defining the mechanistic organic chemistry associated with the formation of a covalent bond between DNA and an exogenous chemical. To this end this study has analysed, by use of a large set of mutagenicity data (Ames test), the mechanistic coverage of a recently published set of in silico structural alerts developed for category formation. The results show that the majority of chemicals with a positive result in the Ames test were assigned at least one covalent binding mechanism related to the formation of a DNA adduct. The remaining chemicals with positive data in the Ames assay were subjected to a detailed mechanistic analysis from which 26 new structural alerts relating to covalent binding mechanisms were developed. In addition, structural alerts for radical and non-covalent intercalation mechanisms were also defined. The structural alerts outlined in this study are not intended to predict mutagenicity but rather to identify mechanisms associated with covalent and non-covalent DNA binding. This mechanistic profiling information can then be used to form chemical categories suitable for filling data gaps via read-across. A strategy for chemical category formation for mutagenicity is also presented.     

Strategies for the use of computational SAR methods in assessing genotoxicity

The relationship between computational SAR studies and relevant data gathering and generation activities is complex. First, the chemical class to be studied is selected on the basis of information requirements for hazard identification and assessment. Membership in the class is determined by consideration of chemical structure and reactivity. Compilation of the existing bioassay data for this chemical class follows immediately from the specification of the class. Bioassay data, qualitative knowledge of general chemical reactivities in this class, and knowledge concerning potential interactions with biomolecular targets all contribute to the derivation of possible mechanisms for biological activity. Computational studies based on modeling the proposed mechanism of action and/or the existing data base can provide a quantitative basis for the differentiation between chemicals. There is the opportunity for continuing feedback between the quantitative computational studies and the development of a relevant bioassay data base for this chemical class. The qualitative and quantitative information on the potential biological responses obtained will provide a rational basis for extrapolation from the extant data base to the chemicals of interest, and to biological responses significant to the assessment for which complete data are unavailable. Knowledge concerning possible mechanisms of action and preexisting data determine the type of computational study that will be most useful.     

Genotoxicity of epoxy resin hardeners in the hepatocyte primary culture/DNA repair test

The genotoxicity of 9 chemicals used as epoxy resin hardeners was examined in the DNA repair test with rat hepatocytes. DNA repair synthesis was elicited by 7 chemicals, i.e., 4-aminodiphenyl ether, 4,4-diaminodiphenyl ether, 3,4,4′-triaminodiphenyl ether, 3,3′-dichloro-4,4′-diaminodiphenyl ether, 1,3-phenylenedi-4-aminophenyl ether, 4,4′-diaminodiphenyl methane and 4,4′-methylene-bis(2-chloroaniline).The positive results obtained with 4 epoxy resin hardeners of unknown carcinogenicity, i.e., 4-aminodiphenyl ether, 3,4,4′-triaminodiphenyl ether, 3,3′-dichloro-4,4′-diaminodiphenyl ether and 1,3-phenylene-di-4-aminophenyl ether suggest that they may be carcinogens. The genotoxicity of 1,4-phenylene-di-4-aminophenyl ether, of unknown carcinogenicity, and 4,4′-diaminodiphenyl sulfone, for which there is no sound proof of carcinogenicity, was not confirmed in the DNA repair test. The result with 4,4′-diaminodiphenyl sulfone was in agreement with its lack of mutagenicity in Salmonella typhimurium.     

Chemical structure, Salmonella mutagenicity and extent of carcinogenicity as indicators of genotoxic carcinogenesis among 222 chemicals tested in rodents by the U.S. NCI/NTP

A survey has been conducted of 222 chemicals evaluated for carcinogenicity in mice and rats by the United States NCI/NTP. The structure of each chemical has been assessed for potential electrophilic (DNA-reactive) sites, its mutagenicity to Salmonella recorded, and the level of its carcinogenicity to rodents tabulated. Correlations among these 3 parameters were then sought. A strong association exists among chemical structure (S/A), mutagenicity to Salmonella (Salm.) and the extent and sites of rodent tumorigenicity among the 222 compounds. Thus, a approximately 90% correlation exists between S/A and Salm. across the 115 carcinogens, the 24 equivocal carcinogens and the 83 non-carcinogens. This indicates the Salmonella assay to be a sensitive method of detecting intrinsic genotoxicity in a chemical. Concordance between S/A and Salm. have therefore been employed as an index of genotoxicity, and use of this index reveals two groups of carcinogens within the database, genotoxic and putatively non-genotoxic. These two broad groups are characterized by different overall carcinogenicity profiles. Thus, 16 tissues were subject to carcinogenesis only by genotoxins, chief among which were the stomach, Zymbal's glands, lung, subcutaneous tissue and circulatory system. Conclusions of carcinogenicity in these 16 tissues comprised 31% of the individual chemical/tissue reports of carcinogenicity. In contrast, both genotoxins and non-genotoxins were active in the remaining 13 tissues, chief among which was the mouse liver which accounted for 24% of all chemical/tissue reports of carcinogenicity. Further, the group of 70 carcinogens reported to be active in both species and/or in 2 or more tissues contained a higher proportion of Salmonella mutagens (70%) than observed for the group of 45 single-species/single-tissue carcinogens (39%). 30% of the 83 non-carcinogens were mutagenic to Salmonella. This confirms earlier observations that a significant proportion of in vitro genotoxins are non-carcinogenic, probably due to their non-absorption or preferential detoxification in vivo. Also, only 30% of the mouse liver-specific carcinogens were mutagenic to Salmonella. This is consistent with tumors being induced in this tissue (and to a lesser extent in other tissues of the mouse and rat) by mechanisms not dependent upon direct interaction of the test chemical with DNA. Detection of 103 of the 115 carcinogens could be achieved by use of only male rats and female mice.(ABSTRACT TRUNCATED AT 400 WORDS)     

Application of a cellular test battery in the decision point approach to carcinogen identification

The assessment of the potential carcinogenicity of a chemical requires a systematic approach taking into account various types of data. Important information on the DNA reactivity and other genetic effects of chemicals can be obtained from a battery of cellular tests. A battery is described which includes DNA repair in hepatocytes, mutagenesis in Salmonella typhimurium, mutagenesis, chromosome alterations, and transformation in mammalian cells. The interpretation of findings in this battery for the identification of potential carcinogenicity of chemicals is discussed.     

Computer-aided rodent carcinogenicity prediction

The potential of the computer program PASS (Prediction Activity Spectra for Substances) to predict rodent carcinogenicity for chemical compounds was studied. PASS predicts carcinogenicity of chemical compounds on the basis of their structural formula and of structure-activity relationship analysis of known carcinogens and non-carcinogens. The data on structures and experimental results of 2-year carcinogenicity assays for 412 chemicals from the NTP (National Toxicological Program) and 1190 chemicals from the CPDB (Carcinogenic Potency Database) were used in our study. The predictions take into consideration information about species and sex of animals. For evaluation of the predictive accuracy we used two procedures: leave-one-out cross-validation (LOO CV) and leave-20%-out cross-validation. In the last case we randomly divided the studied data set 20 times into two subsets. The data from the first subset, containing 80% of the compounds, were added to the PASS training set (which includes about 46,000 compounds with about 1500 biological activity types collected during the last 20 years to predict biological activity spectra), the second subset with 20% of the compounds was used as an evaluation set. The mean accuracy of prediction calculated by LOO CV is about 73% for NTP compounds in the 'equivocal' category of carcinogenic activity and 80% for NTP compounds in the 'evidence' category of carcinogenicity. The mean accuracy of prediction for the CPDB database is 89.9% calculated by LOO CV and 63.4% calculated by leave-20%-out cross-validation. Influence of incorporation of species and sex data on the accuracy of carcinogenicity prediction was also investigated. It was shown that the accuracy was increased only for data on male animals.     

PharmEcology: A pharmacological approach to understanding plant-herbivore interactions: an introduction to the symposium

A central goal in understanding the ecology and evolution of animals is to identify factors that constrain or expand breadth of diet. Selection of diet in many animals is often constrained by chemical deterrents (i.e., secondary metabolites) in available food items. The integration of chemistry and ecology has led to a significant understanding of the chemical complexity of prey (e.g., animals, plants, and algae) and the resultant foraging behavior of consumers. However, most of the literature on chemical defenses of marine and terrestrial prey lacks a mechanistic understanding of how consumers tolerate, or avoid, chemically-defended foods. In order to understand ecological patterns of foraging and co-evolutionary relationships between prey and consumers, we must advance our understanding of the physiological mechanisms responsible for chemical interactions. Such mechanistic studies require the integration of the discipline of pharmacology with ecology, which we call "PharmEcology." Pharmacology provides the tools and insight to investigate the fate (what the body does to a chemical) and action (what a chemical does to the body) of chemicals in living organisms, whereas ecology provides the insight into the interactions between organisms (e.g., herbivores) and their environment (e.g., plants). Although, the general concepts of pharmacology were introduced to ecologists studying plant-herbivore interactions over 30 years ago, the empirical use of pharmacology to understand mechanisms of chemical interactions has remained limited. Moreover, many of the recent biochemical, molecular and technical advances in pharmacology have yet to be utilized by ecologists. The PharmEcology symposium held at a meeting of the Society for Integrative and Comparative Biology in January of 2009 was developed to define novel research directions at the interface of pharmacology and ecology.     

Hormesis and ecological risk assessment: Fact or fantasy?

Hormesis is a widespread phenomenon across occurring many taxa and chemicals, and, at the single species level, issues regarding the application of hormesis to human health and ecological risk assessment are similar. However, interpreting the significance of hormesis for even a single species in an ecological risk assessment can be complicated by competition with other species, predation effects, etc. In addition, ecological risk assessments may involve communities of hundreds or thousands of species as well as a range of ecological processes. Applying hormetic adjustments to threshold effect levels for chemicals derived from sensitivity distributions for a large number of species is impractical. For ecological risks, chemical stressors are frequently of lessor concern than physical stressors (e.g., habitat alteration) or biological stressors (e.g., introduced species), but the relevance of hormesis to non‐chemical stressors is unclear. Although ecological theories such as the intermediate disturbance hypothesis offer some intriguing similarities between chemical hormesis and hormetic‐like responses resulting from physical disturbances, mechanistic explanations are lacking. While further exploration of the relevance of hormesis to ecological risk assessment is desirable, it is unlikely that hormesis is a critical factor in most ecological risk assessments, given the magnitude of other uncertainties inherent in the process.     

The structural basis of the mutagenicity of chemicals in Salmonella typhimurium: the Gene-Tox data base

The CASE structure-activity methodology has been applied to a Gene-Tox derived Salmonella mutagenicity data base consisting of 808 chemicals. Based upon qualitative structural features, CASE identified 29 activating and 3 inactivating structural determinants which correctly predicted the probability of carcinogenicity of 93.7% of the known mutagens and non-mutagens in the data base (sensitivity = 0.998, and specificity = 0.704). Additionally, based upon a qualitative structure-activity analysis, CASE's performance was even better, leading to a sensitivity of 0.981 and a specificity of 1.000. Using the structural determinants identified in this data base, CASE gave excellent predictions of the mutagenicity of chemicals not included in the data base. The identified biophores and biophobes can also be used to investigate the structural basis of the mutagenicity of various chemical classes.     

Development and prevalidation of a list of structure-activity relationship rules to be used in expert systems for prediction of the skin-sensitising properties of chemicals

The new European Union (EU) chemicals policy, as described in the White Paper entitled Strategy for a Future Chemicals Policy, has identified a need for computer-based tools suitable for predicting the hazardous properties of chemicals. Two sets of structural alerts (fragments of chemical structure) for the prediction of skin sensitisation hazard classification ("R43, may cause sensitisation by skin contact") have been drawn up, based on sensitising chemicals from a regulatory database (containing data for the EU notification of new chemicals). These alerts comprise 15 rules for chemical structures deemed to be sensitising by direct action of the chemicals with cells or proteins within the skin, and three rules for substructures that act indirectly, i.e. requiring chemical or biochemical transformation. The predictivity rates of the rules were found to be good (positive predictivity, 88%; false-positive rate, 1%; specificity, 99%; negative predictivity, 74%; false-negative rate, 80%; sensitivity, 20%). Because of the confidential nature of the regulatory database, the rules are supported by examples of sensitising chemicals taken from the "Allergenliste" now held by the Federal Institute for Risk Assessment (BfR) and the DEREK for Windows expert system. The rules were prevalidated against data not used for their development. As a result of the prevalidation study, it is proposed that the two sets of structural alerts should be taken forward for formal validation, with a view to incorporating them into regulatory guidelines.     

Animal carcinogenicity studies: implications for the REACH system

The 2001 European Commission proposal for the Registration, Evaluation and Authorisation of Chemicals (REACH) aims to improve public and environmental health by assessing the toxicity of, and restricting exposure to, potentially toxic chemicals. The greatest benefits are expected to accrue from decreased cancer incidences. Hence the accurate identification of chemical carcinogens must be a top priority for the REACH system. Due to a paucity of human clinical data, the identification of potential human carcinogens has conventionally relied on animal tests. However, our survey of the US Environmental Protection Agency's (EPAs) toxic chemicals database revealed that, for a majority of the chemicals of greatest public health concern (93/160, i.e. 58.1%), the EPA found animal carcinogenicity data to be inadequate to support classifications of probable human carcinogen or non-carcinogen. A wide variety of species were used, with rodents predominating; a wide variety of routes of administration were used; and a particularly wide variety of organ systems were affected. These factors raise serious biological obstacles that render accurate extrapolation to humans profoundly difficult. Furthermore, significantly different International Agency for Research on Cancer assessments of identical chemicals, indicate that the true human predictivity of animal carcinogenicity data is even poorer than is indicated by the EPA figures alone. Consequently, we propose the replacement of animal carcinogenicity bioassays with a tiered combination of non-animal assays, which can be expected to yield a weight-of-evidence characterisation of carcinogenic risk with superior human predictivity. Additional advantages include substantial savings of financial, human and animal resources, and potentially greater insights into mechanisms of carcinogenicity.