Chemical dose-response

Fig. 5. Toxic chemical dose—response curves (a) no effect (b) linear effect (c) no effect at low dose and (d) beneficial at low dose.

SSDs are being routinely used for the display and interpretation of effects data (Parkhurst et al. 1996 Posthuma et al. 2002). An SSD for atrazine (shown in Figure 7.3) displays the typical S-shaped curve associated with many chemical dose-response relationships. Each point on the curve represents an LC50 for a particular species exposed to atrazine under standard toxicity test protocols. The SSD approach uses only a single statistically derived endpoint from each available toxicity test (e.g., the LC50 or EC50). In contrast, all data collected during any specific toxicity test can be used in a hierarchical model. The ability to use all available data to make inferential decisions is a marked improvement over the standard SSD effects distribution. 

Virtually safe dose (VSD) The dose of chemical corresponding to the level of risk determined and accepted by regulatory agencies the dose-to-risk relationship is based on a chemical dose-response curve. 

Over the past decade there has been a movement to harmonize cancer and noncancer risk assessment (Gaylor 1997 Bogdanffy et al. 2001) based on the premise that cancer and noncancer events share similar pharmacokinetic dependencies and overlapping MOAs and thus have similar dose-response relationships. The benchmark dose approach lends itself to the evaluation of both linear and nonlinear dose-response. In fact, one of the stated purposes of EPA s formalization of the benchmark dose process was to provide a standardized approach to chemical dose-response assessment, regardless of whether the chemical is a carcinogen. 

Dose-Response Assessment For chemicals, dose-response assessment involves describing the quantitative relationship between the amount of exposure and the extent of toxic injury or disease. It requires recognizing the hazard of a material before assessing the effects. A dose-response assessment may provide linear equations relating exposure or dose to response or disease. The equations may result firom regression analysis of dose-response data or other statistical procedures. 

The aroma of fmit, the taste of candy, and the texture of bread are examples of flavor perception. In each case, physical and chemical stmctures ia these foods stimulate receptors ia the nose and mouth. Impulses from these receptors are then processed iato perceptions of flavor by the brain. Attention, emotion, memory, cognition, and other brain functions combine with these perceptions to cause behavior, eg, a sense of pleasure, a memory, an idea, a fantasy, a purchase. These are psychological processes and as such have all the complexities of the human mind. Flavor characterization attempts to define what causes flavor and to determine if human response to flavor can be predicted. The ways ia which simple flavor active substances, flavorants, produce perceptions are described both ia terms of the physiology, ie, transduction, and psychophysics, ie, dose-response relationships, of flavor (1,2). Progress has been made ia understanding how perceptions of simple flavorants are processed iato hedonic behavior, ie, degree of liking, or concept formation, eg, crispy or umami (savory) (3,4). However, it is unclear how complex mixtures of flavorants are perceived or what behavior they cause. Flavor characterization involves the chemical measurement of iadividual flavorants and the use of sensory tests to determine their impact on behavior. 

Natural and synthetic chemicals affect every phase of our daily Hves ia both good and noxious manners. The noxious effects of certain substances have been appreciated siace the time of the ancient Greeks. However, it was not until the sixteenth century that certain principles of toxicology became formulated as a result of the thoughts of Philippus Aureolus Theophrastus Bombastus von Hohenheim-Paracelsus (1493—1541). Among a variety of other achievements, he embodied the basis for contemporary appreciation of dose—response relationships ia his often paraphrased dictum "Only the dose makes a poison."... 

However, there are multiple routes of entry to the body for some materials. When a toxic chemical acts on the body or system, the nature and extent of the injurious response depends upon the dose received, that is, the amount of the chemical actually entering the body or system. This relationship of dose and response is shown in Figure 3. The dose-response curve varies with the type of material and the response. 

Most human or environmental healtli hazards can be evaluated by dissecting tlie analysis into four parts liazard identification, dose-response assessment or hazard assessment, exposure assessment, and risk characterization. For some perceived healtli liazards, tlie risk assessment might stop with tlie first step, liazard identification, if no adverse effect is identified or if an agency elects to take regulatory action witliout furtlier analysis. Regarding liazard identification, a hazard is defined as a toxic agent or a set of conditions that luis the potential to cause adverse effects to hmnan health or tlie environment. Healtli hazard identification involves an evaluation of various forms of information in order to identify the different liaz.ards. Dose-response or toxicity assessment is required in an overall assessment responses/cffects can vary widely since all chemicals and contaminants vary in their capacity to cause adverse effects. This step frequently requires that assumptions be made to relate... 

Not all contaminants or chemicals are created equal in their capacity to cause adi ersc effects. Thus, cleanup standards or action levels are based in part on the compounds toxicological properties. Toxicity data are derived largely from animal experiments in which llie aninuils (primarily mice mid rats) are exposed to increasingly liighcr concentrations or doses. Responses or effects can vary widely from no obscn ablc effect to temporary and reversible effects, to permanent injury to organs, to chronic functional impairment to ultimately, death. 

Dose-Response Cune A graphical representation of the quantitative relationship between the administered, applied, or internal dose of a chemical or agent, and a specific biological response to that chemical or agent. 

A basic premise in receptor pharmacology is that all drugs have affinity for receptors (the chemical property that unites the dmg with the receptor), and some drugs have efficacy, the chemical property that causes the receptor to change its behavior toward its host cell. Drugs that have efficacy can produce concentration-dependent responses in physiological systems, characterized by a concentration-response curve (also often referred to as a dose-response cuive). 

The primary objective of CICADs is characterization of hazard and dose-response from exposure to a chemical. CICADs are not a summary of all available data on a particular chemical rather, they include only that information considered critical for characterization of the risk posed by the chemical. The critical studies are, however, presented in sufficient detail to support the conclusions drawn. For additional information, the reader should consult the identified source documents upon which the CICAD has been based. 

Toxic equivalency factors (TEFs) are estimated relative to 2,3,7,8-TCDD, which is assigned a value of 1. They are measures of the toxicity of individual compounds relative to that of 2,3,7,8-TCDD. A variety of toxic indices, measured in vivo or in vitro, have been used to estimate TEFs, including reproductive effects (e.g., embryo toxicity in birds), immunotoxicity, and effects on organ weights. The degree of induction of P450 lAl is another measure from which estimations of TEF values have been made. The usual approach is to compare a dose-response curve for a test compound with that of the reference compound, 2,3,7,8-TCDD, and thereby establish the concentrations (or doses) that are required to elicit a standard response. The ratio of concentration of 2,3,7,8-TCDD to concentration of test chemical when both compounds produce the same degree of response is the TEF. Once determined, a TEF can be used to convert a concentration of a dioxin-like chemical found in an environmental sample to a toxic equivalent (TEQ). 

Some indication of risk of employee exposure to airborne chemicals can be gauged from an analysis of the level of exposure for comparison with known human dose/ response data such as those for carbon monoxide and hydrogen sulphide listed in... 

Of course, the term proven efficacy is central to any resource investment in this area. Basic information on time and dose responses in humans to complex foods rich in carotenoids (and other phytochemicals) is pitifully small. Much of our information is based upon inadequate databases derived from chemical analysis, in vitro models that have not been properly evaluated or validated, and short-term, high-dose human studies. Future research progress requires much more rigorous debate on the experimental systems employed... 

A typical dose-response is shown in Fig. 11.1. This assumes that a dose exists which has no effects due to the capacity of the body to reverse minor changes and maintain cellular homeostasis. The threshold dose is normally taken to be the observed experimental NOAEL, but the NOAEL could be lower than the threshold dose. The NOAEL chosen is the one that represents the most sensitive species studied since all international protocols require that the chemical is tested on at least two species (frequently the rat and the mouse). 

Fig. 11.1 A hypothetical dose-response curve for a toxic chemical.

An inadequate intake in the diet of those food chemicals that are essential nutrients results in health risks. Indeed these risks are by far the most important in terms of the world s population where malnutrition is a major public health problem. But, unlike the toxic chemicals, they would show a very different dose-response if they were subject to similar animal bioassays. At very low doses there would be a high risk of disease that would decrease as the dose was increased, the curve would then plateau until exposure was at such a level that toxicity could occur. Figure 11.2 shows this relationship which is U- or J-shaped rather than the essentially linear dose-response that is assumed for chemicals that are only toxic. The plateau region reflects what is commonly regarded as the homeostatic region where the cell is able to maintain its function and any excess nutrient is excreted, or mechanisms are induced that are completely reversible. 

There is good evidence to suggest that certain chemicals, other than nutrients, show a J- or U-shaped dose-response relationship at levels of exposure which are lower than those where there is some impairment of the inherent... 

Metabolomics studies the entire metabolism of an organism. It is possible to consider characterising the complex pattern of cellular proteins and metabolites that are excreted in urine. Pattern recognition techniques of nuclear magnetic resonance spectra have been applied to determine the dose-response using certain classical liver and kidney toxicants (Robertson et al, 2000). This could well provide a signature of the functional state of the kidney, and perturbations in the pattern as a result of exposure to a chemical could be observed. But first it would be necessary to understand how compounds with known effects on the kidney affect these processes. 

Hazard characterization is a quantitative or semi-quantitative evaluation of the nature, severity, and duration of adverse health effects associated with biological, physical, or chemical agents that may be present in food. The characterization depends on the nature of the toxic effect or hazard. Eor some hazards such as genotoxic chemicals, there may be no threshold for the effect and therefore estimates are made of the possible magnitude of the risk at human exposure level (dose-response extrapolation). 

Cl. Dybing, E. et al.. Hazard characterization of chemicals in food and diet dose response, mechanisms and extrapolation issues. Food Chem. Toxicol, 40, 237, 2002. 

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