Организмнің стимулға жауап беру шамасы

Measure of organism response to stimulus

The dose–response relationship, or exposure–response relationship, describes the magnitude of the response of an organism, as a function of exposure (or doses) to a stimulus or stressor (usually a chemical) after a certain exposure time. Dose–response relationships can be described by dose–response curves. This is explained further in the following sections. A stimulus response function or stimulus response curve is defined more broadly as the response from any type of stimulus, not limited to chemicals.

Studying dose response, and developing dose–response models, is central to determining "safe", "hazardous" and (where relevant) beneficial levels and dosages for drugs, pollutants, foods, and other substances to which humans or other organisms are exposed. These conclusions are often the basis for public policy. The U. S. Environmental Protection Agency has developed extensive guidance and reports on dose–response modeling and assessment, as well as software. The U. S. Food and Drug Administration also has guidance to elucidate dose–response relationships during drug development. Dose response relationships may be used in individuals or in populations. The adage The dose makes the poison reflects how a small amount of a toxin has no significant effect, while a large amount may be fatal. This reflects how dose–response relationships can be used in individuals. In populations, dose–response relationships can describe the way groups of people or organisms are affected at different levels of exposure. Dose response relationships modelled by dose response curves are used extensively in pharmacology and drug development. In particular, the shape of a drug's dose–response curve (quantified by EC50, nH and ymax parameters) reflects the biological activity and strength of the drug.

Logarithmic dose–response curves are generally sigmoidal shape and monotonic and can be fit to a classical Hill equation. The Hill equation is a logistic function with respect to the logarithm of the dose and is similar to a logit model. A generalized model for multiphasic cases has also been suggested. The Hill equation is the following formula, where is the magnitude of the response, [A] is the drug concentration (or equivalently, stimulus intensity) and is the drug concentration that produces a 50% maximal response and is the Hill coefficient. The parameters of the dose response curve reflect measures of potency (such as EC50, IC50, ED50, etc.) and measures of efficacy (such as tissue, cell or population response). A commonly used dose–response curve is the EC50 curve, the half maximal effective concentration, where the EC50 point is defined as the inflection point of the curve. Dose response curves are typically fitted to the Hill equation. The first point along the graph where a response above zero (or above the control response) is reached is usually referred to as a threshold dose. For most beneficial or recreational drugs, the desired effects are found at doses slightly greater than the threshold dose. At higher doses, undesired side effects appear and grow stronger as the dose increases. The more potent a particular substance is, the steeper this curve will be. In quantitative situations, the Y axis often is designated by percentages, which refer to the percentage of exposed individuals registering a standard response (which may be death, as in ). Such a curve is referred to as a quantal dose–response curve, distinguishing it from a graded dose–response curve, where response is continuous (either measured, or by judgment). The Hill equation can be used to describe dose–response relationships, for example ion channel open probability vs. ligand concentration. Dose is usually in milligrams, micrograms, or grams per kilogram of body weight for oral exposures or milligrams per cubic meter of ambient air for inhalation exposures. Other dose units include moles per body weight, moles per animal, and for dermal exposure, moles per square centimeter.

The concept of linear dose–response relationship, thresholds, and all or nothing responses may not apply to non linear situations. A threshold model or linear no threshold model may be more appropriate, depending on the circumstances. A recent critique of these models as they apply to endocrine disruptors argues for a substantial revision of testing and toxicological models at low doses because of observed non monotonicity, i. e. U shaped dose/response curves. Dose–response relationships generally depend on the exposure time and exposure route (e. g., inhalation, dietary intake); quantifying the response after a different exposure time or for a different route leads to a different relationship and possibly different conclusions on the effects of the stressor under consideration. This limitation is caused by the complexity of biological systems and the often unknown biological processes operating between the external exposure and the adverse cellular or tissue response.

Schild analysis may also provide insights into the effect of drugs.