Carcinogens and human health: Part 1

A Systemic Exposure-Based Alternative to the Maximum Tolerated Dose for Carcinogenicity Studies of Human Therapeutics

A systemic exposure-based alternative to the maximum tolerated dose (MTD) for high-dose selection in carcinogenicity studies for human therapeutics was accepted at the Second International Conference on Harmonization (ICH-2). The systemic exposure-based alternative to the MTD is suitable for nongenotoxic compounds with low rodent toxicity that are metabolized similarly in rodents and humans. This is the first product of an evaluation of current standards for rodent carcinogenicity studies of therapeutics. The relative systemic exposure is the ratio of the rat plasma area under the plasma concentration-time curve (AUC) at the MTD/human plasma AUC at the maximum recommended daily dose. An appropriate systemic exposure ratio for high-dose selection in carcinogenicity studies was empirically derived from the distribution of systemic exposure ratios attained by 35 compounds from 11 therapeutic categories in a Food and Drug Administration (FDA) database. Approximately one-third achieved a relative systemic exposure ratio <1 and two-thirds attained an exposure ratio of 10 or less, at the MTD. A systemic exposure ratio of at least 25 was accepted for high-dose selection in carcinogenicity studies at ICH-2. This ratio is high enough to detect all compounds with positive studies in the FDA database and would detect IARC 1 and 2A carcinogenic drugs. A ratio of 25 exceeds the systemic exposure ratio attained by 75% of drugs tested at the MTD in the FDA database and represents an adequate margin of safety which can be attained by a significant proportion of drugs.

Enzyme evolution and cancer: hypothesis why natural carcinogens are more potent than synthetic ones

A great deal of evidence shows that carcinogen induced mutations in human cancers point towards natural rather than man-made agents. Here, we propose a model based on the premise that the evolutionary pressure of nature renders natural carcinogens more potent than artificial ones, present in equal concentration, by suitably modifying kinetic parameters of carcinogen metabolizing enzymes. Enzymes are evolved to bind the transition state of substrates more strongly than substrates themselves, thus obtaining more elevate values of the specificity constant kcat/Km (Ksp). Natural selection optimizing the catalytic power at the proper substrate concentration by suitable raising the Km values, reduce the Gibbs standard activation energy (G(0#)), accelerating the conversion of natural precarcinogens to potent carcinogens. Conversely, "man-made" carcinogens, since the last century in the biosphere, are converted to active metabolites at a lower rate than natural chemicals and the slower rate of activation would allow protective enzymes and DNA repair machinery more time to clean up the damage.

Applied epidemiology and environmental health: emerging controversies

This review article assesses the state of the science in environmental epidemiology, not by summarizing current scientific findings but rather by examining conceptual controversies in the study of how environmental factors influence human health. This approach seems necessary because environmental epidemiology presently stands at a crossroads-in fact, at a number of overlapping crossroads. The field teems with epistemologic debates concerning appropriate paradigms for framing research questions, interpreting data, and applying research findings to policy. The present review focuses on emerging controversies related to three questions: What is considered "environmental"? What counts as credible research in environmental epidemiology? And what does "applied epidemiology" mean in the context of environmental health? The goal is to organize the presently fragmented critical literature on these issues and to promote productive dialogue by identifying central themes in current conceptual debates.

The effects of exposure to "synthetic" chemicals on human health: a review

This article examines how scientists use human, animal, and bacterial evidence to develop policy recommendations about the health consequences of human exposure to modern chemicals. Human evidence is limited because many epidemiological studies are contaminated with selection effects or unobserved heterogeneity. Changes in the aggregate incidence of morbidity (such as cancer) in the population over time are not a substitute for the lack of good individual-level data because incidence data are contaminated by the medicalization of cancer. Animal tests are also problematic because the expense of conducting experiments leads researchers to use only enough animals to allow detection of large differences in cancer incidence between controls and experimental animals that can only arise if the exposure doses are large. Predictions about the cancer incidence that would result in humans at much lower exposure levels, thus, require statistical inferences that implicitly make choices between false positive and false negative inference errors. Policy recommendations about carcinogens, therefore, are as much the product of value choices as "scientific" knowledge.

Research to strengthen the scientific basis for health risk assessment: a survey of the context and rationale for mechanistically based methods and models

Assessment of health risks is an integral part of regulatory decision-making that occurs at the interface between science (e.g. facts) and policy (e.g. values). Because existing scientific knowledge and understanding are often inadequate to answer the most critical risk-related questions, regulatory agencies have developed sets of formalized 'science policies' to extrapolate from existing data to real-life events and situations. These science policies, as, for example, the use of default assumptions or exposure scenarios, can introduce significant uncertainties into the final risk estimate. We survey the rationale for research to reduce extrapolation-related uncertainties, focusing specifically on the need to develop mechanistically based methods and models, including test methods to identify and characterize health effects, integrated human exposure models, physiologically based pharmacokinetic (PBPK) models and biologically based dose-response (BBDR) models.