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Drug Metabolism Phcy 172 - University of North Carolina at
Drug Metabolism Phcy 172 - University of North Carolina at

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Toxicodynamics



Toxicodynamics, termed pharmacodynamics in pharmacology, describes the dynamic interactions of a toxicant with a biological target and its biological effects. A biological target, also known as the site of action, can be binding proteins, ion channels, DNA, or a variety of other receptors. When a toxicant enters an organism, it can interact with these receptors and produce structural or functional alterations. The mechanism of action of the toxicant, as determined by a toxicant’s chemical properties, will determine what receptors are targeted and the overall toxic effect at the cellular level and organismal level.Toxicants have been grouped together according to their chemical properties by way of quantitative structure-activity relationships (QSARs), which allows prediction of toxic action based on these properties. endocrine disrupting chemicals (EDCs) and carcinogens are examples of classes of toxicants that can act as QSARs. EDCs mimic or block transcriptional activation normally caused by natural steroid hormones. These types of chemicals can act on androgen receptors, estrogen receptors and thyroid hormone receptors. This mechanism can include such toxicants as dichlorodiphenyltrichloroethane (DDE) and polychlorinated biphenyls (PCBs). Another class of chemicals, carcinogens, are substances that cause cancer and can be classified as genotoxic or nongenotoxic carcinogens. These categories include toxicants such as polycyclic aromatic hydrocarbon (PAHs) and carbon tetrachloride (CCl4). The process of toxicodynamics can be useful for application in environmental risk assessment by implementing toxicokinetic-toxicodynamic (TKTD) models. TKTD models include phenomenas such as time-varying exposure, carry-over toxicity, organism recovery time, effects of mixtures, and extrapolation to untested chemicals and species. Due to their advantages, these types of models may be more applicable for risk assessment than traditional modeling approaches.
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