An overview of the report: correlation between carcinogenic potency and the maximum tolerated dose: implications for risk assessment

A value of information framework for assessing the trade-offs associated with uncertainty, duration, and cost of chemical toxicity testing

A number of investigators have explored the use of value of information (VOI) analysis to evaluate alternative information collection procedures in diverse decision-making contexts. This paper presents an analytic framework for determining the value of toxicity information used in risk-based decision making. The framework is specifically designed to explore the trade-offs between cost, timeliness, and uncertainty reduction associated with different toxicity-testing methodologies. The use of the proposed framework is demonstrated by two illustrative applications which, although based on simplified assumptions, show the insights that can be obtained through the use of VOI analysis. Specifically, these results suggest that timeliness of information collection has a significant impact on estimates of the VOI of chemical toxicity tests, even in the presence of smaller reductions in uncertainty. The framework introduces the concept of the expected value of delayed sample information, as an extension to the usual expected value of sample information, to accommodate the reductions in value resulting from delayed decision making. Our analysis also suggests that lower cost and higher throughput testing also may be beneficial in terms of public health benefits by increasing the number of substances that can be evaluated within a given budget. When the relative value is expressed in terms of return-on-investment per testing strategy, the differences can be substantial.

Quantum-Mechanical Approach to Predicting the Carcinogenic Potency of N-Nitroso Impurities in Pharmaceuticals

N-Nitroso contaminants in medicinal products are of concern due to their high carcinogenic potency; however, not all these compounds are created equal, and some are relatively benign chemicals. Understanding the structure-activity relationships (SARs) that drive hazards in one molecule versus another is key to both protecting human health and alleviating costly and sometimes inaccurate animal testing. Here, we report on an extension of the CADRE (computer-aided discovery and REdesign) platform, which is used broadly by the pharmaceutical and personal care industries to assess environmental and human health endpoints, to predict the carcinogenic potency of N-nitroso compounds. The model distinguishes compounds in three potency categories with 77% accuracy in external testing, which surpasses the reproducibility of rodent cancer bioassays and constraints imposed by limited (high-quality) data. The robustness of predictions for more complex pharmaceuticals is maximized by capturing key SARs using quantum mechanics, that is, by hinging the model on the underlying chemistry versus chemicals in the training set. To this end, the present approach can be leveraged in a quantitative hazard assessment and to offer qualitative guidance using electronic structure comparisons between well-studied analogues and unknown contaminants.

The Inhibitory Potential of 2'-dihalo Ribonucleotides against HCV: Molecular Docking, Molecular Simulations, MM-BPSA, and DFT Studies

Sofosbuvir is the first approved direct-acting antiviral (DAA) agent that inhibits the HCV NS5B polymerase, resulting in chain termination. The molecular models of the 2′-dihalo ribonucleotides used were based on experimental biological studies of HCV polymerase inhibitors. They were modeled within HCV GT1a and GT1b to understand the structure–activity relationship (SAR) and the binding interaction of the halogen atoms at the active site of NS5B polymerase using different computational approaches. The outputs of the molecular docking studies indicated the correct binding mode of the tested compounds against the active sites in target receptors, exhibiting good binding free energies. Interestingly, the change in the substitution at the ribose sugar was found to produce a mild effect on the binding mode. In detail, increasing the hydrophobicity of the substituted moieties resulted in a better binding affinity. Furthermore, in silico ADMET investigation implied the general drug likeness of the examined derivatives. Specifically, good oral absorptions, no BBB penetration, and no CYP4502D6 inhibitions were expected. Likely, the in silico toxicity studies against several animal models showed no carcinogenicity and high predicted TD50 values. The DFT studies exhibited a bioisosteric effect between the substituents at the 2′-position and the possible steric clash between 2′-substituted nucleoside analogs and the active site in the target enzyme. Finally, compound 6 was subjected to several molecular dynamics (MD) simulations and MM-PBSA studies to examine the protein-ligand dynamic and energetic stability.

Characterization, in-silico, and in-vitro study of a new steroid derivative from Ophiocoma dentata as a potential treatment for COVID-19

The medicinal potential of marine invertebrates' bioactive components that may act as anti-COVID-19 demonstrated promising results. Ophiocoma dentata, which is common in the Red Sea, is one such source. Therefore, this study aimed to isolate a new compound from the brittle star, Ophiocoma dentata, and evaluate its efficacy as anti-COVID-19 in-silico and in-vitro. Standard procedures were followed in order to assess the isolated compound’s preliminary toxicity and anti-inflammatory properties. Computer virtual screening technology through molecular docking and ADMET studies was conducted as well as a new steroid derivative was isolated for the first time, named 5α-cholesta-4(27), 24-dien-3β, 23 β-diol. Investigation of the Anti-Covid-19 activity of the isolated compound using a Plaque reduction assay revealed 95% inhibition at a concentration of 5 ng/µl (12.48 µM). Moreover, this compound showed an IC₅₀ of 11,350 ± 1500 ng/ml against the normal fibroblast cells, indicating its safety. Interestingly, this compound exhibited anti-inflammatory activity with an IC₅₀ of 51.92 ± 0.03 μg/ml compared to a reference drug’s IC₅₀ of 53.64 ± 0.01 μg/ml, indicating that this compound is a potent anti-inflammatory. In silico data have proved that the isolated compound is a promising viral inhibitor against SARS-CoV2 and is thus recommended as a future nature preventive and curative antiviral drug.

The Pebble Remains in the Master's Hand: Two Careers Spent Learning (Still) from John Evans

In this article, we discuss four vexing problems in risk-based decision making that John Evans has addressed over the last nearly 40 years and has perennially challenged the two of us and others to think about. We tackle the role in decision making of potential thresholds in dose-response functions, how the lack of health reference values for many chemicals may distort risk management, the challenge of model uncertainty for risk characterization, and the yet-untapped potential for value-of-information analysis to enhance public health decision making. Our theme is that work remains to be done on each of these, but that some of that work would merely involve listening to ideas that John has already offered.

Phase I, II and III Trials in Inflammatory Bowel Diseases: A Practical Guide for the Non-specialist

In the last few decades several new molecules have been developed in the field of inflammatory bowel diseases. However, the process that leads to the approval and use of a new drug is very long, expensive and complex, consisting of various phases. There is a pre-clinical phase that is performed on animals and a clinical phase that is directed to humans. Each research phase aims to evaluate different aspects of the drug and involves a specific target group of subjects. In addition, many aspects must be considered in the evaluation of a clinical trial: randomization, presence of a control group, blind design, type of data analysis performed, and patient stratification. The objective of this review is to provide an overview of the clinical trial phases of a new drug in order to better understand and interpret their results.

Quantifying association between liver tumor incidence and early-stage liver weight increase - An NTP data analysis

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Liver tumor incidence and liver weight data were collected from 593 NTP studies.

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Correlation between BMDs from these two types of data were quantified.

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In a general analysis, the correlation coefficient can be as high as 0.78.

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Early liver weight change may be used as an indicator for chemical tumorigenesis.

Two-year toxicology and carcinogenesis rodent studies conducted at the National Toxicology Program (NTP) are used to identify potential adverse health effects in humans due to chemical exposure, including cancer. Liver tumor, the most frequently diagnosed tumor type of chemically induced neoplastic effects documented in NTP’s carcinogenicity studies, is usually difficult to be detected at early stage due to the inconspicuous symptoms. However, the abnormal growth of liver cells can lead to liver weight increase, so it is hypothesized that liver tumor incidence is associated with early stage liver weight increase. In this study, the association between liver weight increase and liver tumor incidence are quantified by (1) calculating the correlation coefficient of and (2) building quantitative linear relationship between benchmark dose estimates derived from these two types of data collected from NTP studies. Together with 151 chemical/species/sex combinations of liver tumor data showing positive evidence collected from 76 NTP long-term studies, short-term liver weight data reported in the same NTP report were extracted to be paired with the liver tumor data for the analyses. Results show that the estimated correlation coefficients (as high as 0.78) along with the adequately fitted linear models suggest that the association between relative liver weight increase and aggregated liver tumor incidence are relatively strong. Additional analyses focused on some more specific situations (e.g., specific tumor type or specific strain/sex combination) further confirmed the strong association. Given the design of this study, the interpretation of the findings is not that liver weight increase can be used to predict liver tumor incidence, instead, evident increase in liver weight might be used as a reason to prioritize the test article for a two-year toxicology and carcinogenesis study.

The Multiple Chemicals and Actions Model of carcinogenesis. A possible new approach to developing prevention strategies for environmental carcinogenesis

The number of definite and probable human chemical carcinogens identified by IARC approaches between 1987 and June 2004 is reported to be 50 agents. However, overall, given the rapid expansion in the number of chemicals in use, the throughput of the current approach to identifying potential environmental carcinogens is low. The long-term rodent bioassay, a key part of the current approach, identifies many chemicals which eventually turn out to be irrelevant for human health with regard to cancer. A new approach is suggested which focuses on identifying the potency of environmental mixtures for induction of toxicological changes relevant to carcinogenesis (e.g., cell proliferation, chronic inflammation, inhibition of apoptosis, mutagenicity). Details regarding a suggested strategy for prioritization of mixtures are provided with more detailed information regarding mutagenicity as an end point. The long-term rodent bioassay is not included in the proposal (although it is acknowledged that it will continue to be important in premarketing regulatory schemes) for hazard identification. The Multiple Chemicals and Actions Model (MCAM) is developed. In this model the chemical mixtures in the environment act via a number of mechanisms as ‘effectors’ or ‘inhibitors’ of a multistage carcinogenic process. Identifying effectors and inhibitors of the rate-limiting step would be important for preventive strategies. Genetic polymorphisms act as modulators of effector and inhibitor mixtures. It is suggested that the MCAM model could be used in public education programmes to help inform on public health issues regarding cancer and to help avoid future scares which tend to focus on single chemicals. It is acknowledged that there would need to be basic research undertaken to generate appropriate data to support the application of the proposal before it could be used in cancer prevention strategies.

Comparative time course profiles of phthalate stereoisomers in mice

More efficient models are needed to assess potential carcinogenicity hazard of environmental chemicals based on early events in tumorigenesis. Here, we investigated time course profiles for key events in an established cancer mode of action. Using a case study approach, we evaluated two reference phthalates, di(2-ethylhexyl) phthalate (DEHP) and its stereoisomer di-n-octyl phthalate (DNOP), across the span of a two-year carcinogenicity bioassay. Male B6C3F1 mice received diets with no phthalate added (control), DEHP at 0.12, 0.60, or 1.20%, or DNOP at 0.10, 0.50, or 1.00% (n = 80-83/group) for up to 104 weeks with six interim evaluations starting at week 4. Mean phthalate doses were 139, 845, and 3147 mg/kg/day for DEHP and 113, 755, and 1281 mg/kg/day for DNOP groups, respectively. Incidence and number of hepatocellular tumors (adenoma and/or carcinoma) were greater at ≥ 60 weeks for all DEHP groups with time and dose trends, whereas DNOP had no significant effects. Key events supported a peroxisome proliferator-activated receptor alpha (PPARα) mode of action for DEHP, with secondary cytotoxicity at the high dose, whereas DNOP induced modest increases in PPARα activity without proliferative or cytotoxic effects. Threshold estimates for later tumorigenic effects were identified at week 4 for relative liver weight (+24%) and PPARα activity (+79%) relative to the control group. Benchmark doses (BMDs) for these measures at week 4 clearly distinguished DEHP and DNOP and showed strong concordance with values at later time points and tumorigenic BMDs. Other target sites included testis and kidney, which showed degenerative changes at higher doses of DEHP but not DNOP. Our results highlight marked differences in the chronic toxicity profiles of structurally similar phthalates and demonstrate quantitative relationships between early bioindicators and later tumor outcomes.

Mutagenic impurities in pharmaceuticals: a critique of the derivation of the cancer TTC (Threshold of Toxicological Concern) and recommendations for structural-class-based limits

The cancer TTC (Threshold of Toxicological Concern) concept is currently employed as an aid to risk assessment of potentially mutagenic impurities (PMIs) in food, cosmetics and other sectors. Within the pharmaceutical industry the use of one default cancer TTC limit of 1.5 μg/day for PMIs is being increasingly questioned. Its derivation, originally in the context of foodstuffs, can be broken down into five key elements: dataset composition; determination of carcinogenicity/mutagenicity status and carcinogenic potency (based on TD₅₀s) of compounds in the dataset; linear extrapolation of carcinogenic potencies; evaluation of the more potent compounds in each structural category, and presence of representative structural alerts amongst the more potent compounds. A detailed evaluation reveals that the derivation process is distorted by the use of the lowest statistically significant TD₅₀s (which can produce a false-carcinogen phenomenon) and by employing linear extrapolation for non-mutagenic carcinogens. By correcting for these two factors, it is concluded that only around 50% of conventional structural-alert categories were adequately addressed and that limits higher than the default value appear to be justified in many cases. Using similar criteria for PMIs in pharmaceuticals, four distinct potency categories of conventional structural alerts can be distinguished, ranging from alerts with questionable validity to those with high potency, which are considered to provide a range of flexible and pragmatic limits for such impurities.

Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment

The traditional approach for estimating noncancer and cancer reference values in quantitative chemical risk assessment is time and resource intensive. The extent and nature of the studies required under the traditional approach has limited the number of chemicals with published risk assessments. In this study, female mice were exposed for 13 weeks to multiple concentrations of five chemicals that were positive in a 2-year cancer bioassay. Traditional histological and organ weight changes were evaluated, and gene expression microarray analysis was performed on the target tissues. The histological, organ weight changes, and the original tumor incidences in the original cancer bioassay were analyzed using standard benchmark dose (BMD) methods to identify noncancer and cancer points of departure, respectively. The dose-related changes in gene expression were also analyzed using a BMD approach and the responses grouped based on cellular biological processes. A comparison of the transcriptional BMD values with those for the traditional noncancer and cancer apical endpoints showed a high degree of correlation for specific cellular biological processes. For chemicals with human exposure data, the transcriptional BMD values were also used to calculate a margin of exposure. The margins of exposure ranged from 1900 to 54,000. Both the correlation between the BMD values for the transcriptional and apical endpoints and the margin of exposure analysis suggest that transcriptional BMD values may be used as potential points of departure for noncancer and cancer risk assessment.

Chlorination disinfection by-products, public health risk tradeoffs and me

Since 1974 when trihalomethanes (THMs) were first reported as disinfection by-products (DBPs) in drinking water, there has been an enormous research effort directed at understanding how DBPs are formed in the chlorination or chloramination of drinking water, how these chlorination DBPs can be minimized and whether they pose a public health risk, mainly in the form of cancer or adverse reproductive outcomes. Driven by continuing analytical advances, the original DBPs, the THMs, have been expanded to include over 600 DBPs that have now been reported in drinking water. The historical risk assessment context which presumed cancer could be mainly attributed to exposure to environmental carcinogens played a major role in defining regulatory responses to chlorination DBPs which, in turn, strongly influenced the DBP research agenda. There are now more than 30 years of drinking water quality, treatment and health effects research, including more than 60 epidemiology studies on human populations, directed at the chlorination DBP issue. These provide considerable scope to reflect on what we know now, how our understanding has changed, what those changes mean for public health risk management overall and where we should look to better understand and manage this issue in the future.

Human-toxicological effect and damage factors of carcinogenic and noncarcinogenic chemicals for life cycle impact assessment

Chemical fate, effect, and damage should be accounted for in the analysis of human health impacts by toxic chemicals in life-cycle assessment (LCA). The goal of this article is to present a new method to derive human damage and effect factors of toxic pollutants, starting from a lognormal dose-response function. Human damage factors are expressed as disability-adjusted life years (DALYs). Human effect factors contain a disease-specific and a substance-specific component. The disease-specific component depends on the probability of disease occurrence and the distribution of sensitivities in the human population. The substance-specific component, equal to the inverse of the ED50, represents the toxic potency of a substance. The new method has been applied to calculate combined human damage and effect factors for 1,192 substances. The total range of 7 to 9 orders of magnitude between the substances is dominated by the range in toxic potencies. For the combined factors, the typical uncertainty, represented by the square root of the ratio of the 97.5th and 2.5th percentile, is a factor of 25 for carcinogenic effects and a factor of 125 for noncarcinogenic effects. The interspecies conversion factor, the (non)cancer effect conversion factor, and the average noncancer damage factor dominate the overall uncertainty.

Tiered chemical testing: a value of information approach

In December 2000 the EPA initiated the Voluntary Children's Chemical Evaluation Program (VCCEP) by asking manufacturers to voluntarily sponsor toxicological testing in a tiered process for 23 chemicals selected for the pilot phase. The tiered nature of the VCCEP pilot program creates the need for clearly defined criteria for determining when information is sufficient to assess the potential risks to children. This raises questions about how to determine the "adequacy" of the existing information and assess the need to undertake efforts to reduce uncertainty (through further testing). This article applies a value of information analysis approach to determine adequacy by modeling how toxicological and exposure data collected through the VCCEP may be used to inform risk management decisions. The analysis demonstrates the importance of information about the exposure level and control costs in making decisions regarding further toxicological testing. This article accounts for the cost of delaying control action and identifies the optimal testing strategy for a constrained decisionmaker who, absent applicable human data, cannot regulate without bioassay data on a specific chemical. It also quantifies the differences in optimal testing strategy for three decision criteria: maximizing societal net benefits, ensuring maximum exposure control while net benefits are positive (i.e., benefits outweigh costs), and controlling to the maximum extent technologically feasible while the lifetime risk of cancer exceeds a specific level of risk. Finally, this article shows the large differences that exist in net benefits between the three criteria for the range of exposure levels where the optimal actions differ.

Synergy between systemic toxicity and genotoxicity: relevance to human cancer risk

The health risk manager and policy analyst must frequently make recommendations based upon incomplete toxicity data. This is a situation which is encountered in the evaluation of human carcinogenic risks as animal cancer bioassay results are often not available. In this study, in order to assess the relevance of other possible indicators of carcinogenic risks, we used the "chemical diversity approach" to estimate the magnitude of the human carcinogenic risk based upon Salmonella mutagenicity and systemic toxicity data of the "universe of chemicals" to which humans have the potential to be exposed. Analyses of the properties of 10,000 agents representative of the "universe of chemicals" suggest that chemicals that have genotoxic potentials as well as exhibiting greater systemic toxicity are more likely to be carcinogens than non-genotoxicants or agents that exhibit lesser toxicity. Since "genotoxic" carcinogenicity is a hallmark of recognized human carcinogens, these findings are relevant to human cancer risk assessment.

Assessing human health response in life cycle assessment using ED10s and DALYs: part 1--Cancer effects

Life cycle assessment (LCA) is a framework for comparing products according to their total estimated environmental impact, summed over all chemical emissions and activities associated with a product at all stages in its life cycle (from raw material acquisition, manufacturing, use, to final disposal). For each chemical involved, the exposure associated with the mass released into the environment, integrated over time and space, is multiplied by a toxicological measure to estimate the likelihood of effects and their potential consequences. In this article, we explore the use of quantitative methods drawn from conventional single-chemical regulatory risk assessments to create a procedure for the estimation of the cancer effect measure in the impact phase of LCA. The approach is based on the maximum likelihood estimate of the effect dose inducing a 10% response over background, ED10, and default linear low-dose extrapolation using the slope betaED10 (0.1/ED10). The calculated effects may correspond to residual risks below current regulatory compliance requirements that occur over multiple generations and at multiple locations; but at the very least they represent a "using up" of some portion of the human population's ability to accommodate emissions. Preliminary comparisons are performed with existing measures, such as the U.S. Environmental Protection Agency's (U.S. EPA's) slope factor measure q1*. By analyzing bioassay data for 44 chemicals drawn from the EPA's Integrated Risk Information System (IRIS) database, we explore estimating ED10 from more readily available information such as the median tumor dose rate TD50 and the median single lethal dose LD50. Based on the TD50, we then estimate the ED10 for more than 600 chemicals. Differences in potential consequences, or severity, are addressed by combining betaED10 with the measure disability adjusted life years per affected person, DALYp. Most of the variation among chemicals for cancer effects is found to be due to differences in the slope factors (betaED10) ranging from 10(-4) up to 10(4) (risk of cancer/mg/kg-day).

Regulatory cancer risk assessment based on a quick estimate of a benchmark dose derived from the maximum tolerated dose

The proposed U.S. Environmental Protection Agency carcinogen risk assessment guidelines employ a benchmark dose as a point of departure (POD) for low-dose risk assessment. If information on the carcinogenic mode of action for a chemical supports a nonlinear dose-response curve below the POD, a margin-of-exposure ratio between the POD and anticipated human exposure would be considered. The POD would be divided by uncertainty (safety) factors to arrive at a reference dose that is likely to produce no, or at most negligible, cancer risk for humans. If nonlinearity below the POD is not supported by sufficient evidence, then linear extrapolation from the incidence at the POD to zero would be used for low-dose cancer risk estimation. The carcinogen guidelines suggest that the lower 95% confidence limit on the dose estimated to produce an excess of tumors in 10% of the animals (LTD10) be used for the POD. Due to the relatively narrow range of doses in 2-year rodent bioassays and the limited range of statistically significant tumor incidence rates, the estimate of the LTD10 obtained from 2-year bioassays is constrained to a relatively narrow range of values. Because of this constraint, a simple, quick, and relatively precise determination of the LTD10 can be obtained by the maximum tolerated dose (MTD) divided by 7. All that is needed is a 90-day study to establish the MTD. It is shown that the LTD10 determined by this relatively easy procedure is generally within a factor of 10 of the LTD10 that would be estimated using tumor incidence rates from 2-year bioassays. Estimates of cancer potency from replicated 2-year bioassays, and hence estimates of cancer risk, have been show to vary by a factor of 4 around a median value. Thus, there may be little gain in precision of cancer risk estimates derived from a 2-year bioassay, compared to the estimate based on the MTD from a 90-day study. If the anticipated human exposure were estimated to be small relative to the MTD/7 = LTD10, there may be little value in conducting a chronic 2-year study in rodents because the estimate of cancer risk would be low regardless of the results of a 2-year bioassay. Linear extrapolation to a risk of less than 1 in 100,000 and use of an uncertainty factor, e.g., of 10,000, would give the same regulatory "safe dose." Linear extrapolation to a virtually safe dose associated with a cancer risk estimate of less than one in a million would be 10 times lower than the reference dose based on the LTD10/10,000.

What do animal cancer tests tell us about human cancer risk?: Overview of analyses of the carcinogenic potency database

Many important issues in carcinogenesis can be addressed using our Carcinogenic Potency Database, which analyzes and standardizes the literature of chronic carcinogenicity tests in laboratory animals. This review is an update and overview of our analyses during the past 15 years, using the current database that includes results of 5152 experiments on 1298 chemicals. We address the following: 1. More than half the 1298 chemicals tested in long-term experiments have been evaluated as carcinogens. We describe this positivity rate for several subsets of the data (including naturally occurring and synthetic chemicals), and we hypothesize and important role in the interpretation of results for increased cell division due to administration of high doses. 2. Methodological issues in the interpretation of animal cancer tests: constraints on the estimation of carcinogenic potency and validity problems associated with using the limited data from bioassays to estimate human risk, reproducibility of results in carcinogenesis bioassays, comparison of lifetable and summary methods of analysis, and summarizing carcinogenic potency when multiple experiments on a chemical are positive. 3. Positivity is compared in bioassays for two closely related species, rats and mice, tested under similar experimental conditions. We assess what information such a comparison can provide about interspecies extrapolation. 4. Rodent carcinogens induce tumors in 35 different target organs. We describe the frequency of chemicals that induce tumors in rats or mice at each target site, and we compare target sites of mutagenic and nonmutagenic rodent carcinogens. 5. A broad perspective on evaluation of possible cancer hazards from rodent carcinogens is given, by ranking 74 human exposures (natural and synthetic) on the HERP indes.

Activity profiles of carcinogenicity data: application in hazard identification and risk assessment

Animal cancer data play a primary role in human risk assessment due to the limited epidemiological data. The current database of test results from the NCI/NTP rodent bioassays provide valuable information concerning the carcinogenic potential of hundreds of environmental agents. An approach is presented to reduce and graphically display these data as activity profiles to allow visualization and assessment of tumor response trends across multiple parameters, e.g. species, sex, target site, and route of exposure. Spreadsheet graphics are used to construct the profiles organized on the multiple parameters of carcinogenicity in a format that enables comparative analysis among chemicals. Several example applications are described to illustrate the value of activity profiles in hazard identification and risk assessment. The NCI/NTP data used in developing this concept are from the Carcinogen Potency Database (CPDB) complied by Gold et al. (Environ. Health Perspect. 103 (Suppl. 8) (1995) 3-122). Computer links to the underlying details in the CPDB are maintained such that specific histopathologies at individual tumor sites, duration of the study, dose-response data, and notes related to diet, survival, treatments, and the authors evaluation are available to aid in the assessment process. The profiles display carcinogen potency based on the tumorigenic dose rate 50 (TD50), i.e. the chronic dose rate that would induce tumors in half of the test animals at the end of their standard lifespan adjusting for spontaneous tumors. The TD50 values provide an index for establishing a relative potency ranking of the chemicals for any specific parameter, such as species or target site. An example ranking of hepatocarcinogens is presented to illustrate relative potencies for chemical analogs. The rank order indicates that the degree and type of halogenation of alkanes has a direct bearing on the carcinogenic potency of these compounds.

Risk assessment and the use of information on underlying biologic mechanisms: a perspective

Recent years have seen the rapid expansion of scientific understanding of the underlying biologic bases of toxic reactions to chemicals. Use of this information in health risk assessment is expanding, but it has yet to reach its full potential. This article considers what has successfully been done, what approaches are now being developed, and what impediments and difficulties have been encountered in attempts to bring case-specific, mechanistic toxicological information to bear on risk estimation. In hazard identification, mechanistic information can help explain the bearing of various empirical experimental results for inferring human hazard, can increase the sensitivity of detection, and can be considered in attempts to replace 2-year animal bioassays with hazard identification methods that rest on identifying key biological properties underlying carcinogenicity rather than relying only on the experimental observation of tumors. In carcinogen potency estimation, mechanistic information can potentially extend relevant observation to lower dose levels, provide the basis for choosing among empirically based dose-response models, lead to potency estimates through relationships with quantitative measures of short-term test outcomes, and can be considered as a basis for providing direct observation of the biological parameters in biologically based dose-response modeling.

Carcinogens in food: priorities for regulatory action

A pragmatic possible approach to the prioritization of chemical carcinogens occurring as food contaminants is described, based on the carcinogenic risk to the population. This should be of value in ensuring that resources for assessment and management of carcinogens in food are directed to the most important areas with regard to carcinogenic risk to the population. Key components of this approach are an assessment of the carcinogenic hazard to humans combined with estimations of intakes per person and of the proportion of the population exposed. These are used to derive an index referred to as the Population Carcinogenic Index. Concerning the hazard assessment expert judgement is used to place the chemical in one of five categories. The highest category is for chemical carcinogens that are believed to act by a genotoxic mechanism. It is recognised that such compounds may vary enormously with respect to their potency and various approaches to ranking carcinogens on the basis of potency are reviewed. The approach adopted is to subdivide the genotoxic carcinogens category into high, medium and low potency based on the TD50 value. Methods of estimating intakes and exposed populations are considered and an approach which groups these into broad categories is developed. The hazard and exposure assessments are then combined to derive the Population Carcinogenicity Index.

Quantitative risk assessment and the limitations of the linearized multistage model

1. Quantifying carcinogenic risk is an important objective for assisting in the assessment and management of risks from chemical exposure. The most widely used of the many mathematical models proposed for extrapolation of carcinogenicity data from animal studies to low dose human exposures is the linearized multistage (LMS) model. This has, in effect, become the default approach for much of Quantitative Risk Assessment (QRA). The practical properties of this model have been investigated. 2. Analysis of stimulated data using the LMS model showed (i) that the Maximum Likelihood Estimate (MLE) of the low dose slope, q1, was unstable and extremely sensitive to small changes in the data; (ii) the 95% Upper Confidence Limit (UCL) estimate, q1*, preferred by the US Environmental Protection Agency (EPA) was insensitive with only small changes in values being obtained for large changes in the data; (iii) data sets where there was no statistical significance could give risk estimates similar to those obtained from data sets with clear dose-related effects; (iv) the size of the values of the Virtually Safe Dose (VSD) obtained did not necessarily relate to the biological interpretation of the data sets; (v) the value of q1* obtained was closely related to the top dose used in the study. 3. Limitations of the LMS model were illustrated by examples of its use in assessing the carcinogenicity of 2, 3, 7, 8-TCDD leading to the conclusion that the existing models are not suitable for routine use in the estimation of the risk from chemical carcinogens. The use of the LMS model has been justified in part by its original derivation from a mathematical model based upon a multistage model of carcinogenesis. However, estimates of the parameters of the model used to provide estimates of low dose risk to humans have no direct relationship to specific biological event in carcinogenesis. Further developments in mathematical models and increased understanding of the biological events underlying the carcinogenesis will lead to more biologically plausible QRA methods which would then justify serious consideration of QRA by regulatory authorities throughout the world.

Improved prediction of carcinogenic potencies from mutagenic potencies for chemicals positive in rodents and the Ames test

Most studies of correlation between logs of mutagenic potency (MP) and cancer potency (CP) have obtained relatively small but statistically significant estimates of correlation (r) and corresponding log-log slope (b, in Log[CP] = a + b Log[MP]). But for mutagenic carcinogens, multistage cancer theory predicts that b and r should be highest when MP values best estimate mutation yields per unit dose at concentrations at least as high as those observed to cause cancer in bioassay animals. To test this hypothesis, the correlation of Ames test and rodent cancer potencies was examined for a total number n of 134 chemicals reported as positive in both assays. Values of maximum significant cancer potency (CP, in [mmol/kg-day]-1) were obtained from a published carcinogenic potency database. Values of maximum mutagenic potency (MP, as revertants per mmol/L-plate) were estimated from 2,347 sets of Ames test data reported by the NTP mutagenicity testing program, supplemented by similar data newly obtained for ten heterocyclic amines. For compounds with one or more significantly positive MP estimates based on approximately linear Ames test dose-response data, linear regression of maximum values of Log(CP) on Log(MP) yielded b = 0.27 +/- 0.065 and r = 0.39 (P = 0.0001, n = 105), similar to previously reported results for relatively large n. As predicted, when MP values were additionally restricted to include only values estimated from Ames test data approximately linear at corresponding lowest-TD50 concentrations, similar regressions yielded significantly improved fits (e.g,. b and r approximately 0.6, P < 10(-7), n = 68). Implications of these findings are discussed concerning the quantitative role that mutations like those measured in the Ames test may have in explaining observed cancer-bioassay results.