Cmax (pharmacology)DISPLAYTITLE:Cmax (pharmacology) Cmax is the maximum (or peak) serum concentration that a drug achieves in a specified compartment or test area of the body after the drug has been administered and before the administration of a second dose. It is a standard measurement in pharmacokinetics. Cmax is the opposite of Cmin, which is the minimum (or trough) concentration that a drug achieves after dosing. The related pharmacokinetic parameter tmax is the time at which the Cmax is observed.
Drug deliveryDrug delivery refers to approaches, formulations, manufacturing techniques, storage systems, and technologies involved in transporting a pharmaceutical compound to its target site to achieve a desired therapeutic effect. Principles related to drug preparation, route of administration, site-specific targeting, metabolism, and toxicity are used to optimize efficacy and safety, and to improve patient convenience and compliance. Drug delivery is aimed at altering a drug's pharmacokinetics and specificity by formulating it with different excipients, drug carriers, and medical devices.
Area under the curve (pharmacokinetics)In the field of pharmacokinetics, the area under the curve (AUC) is the definite integral of the concentration of a drug in blood plasma as a function of time (this can be done using liquid chromatography–mass spectrometry). In practice, the drug concentration is measured at certain discrete points in time and the trapezoidal rule is used to estimate AUC. In pharmacology, the area under the plot of plasma concentration of a drug versus time after dosage (called “area under the curve” or AUC) gives insight into the extent of exposure to a drug and its clearance rate from the body.
Drug classA drug class is a group of medications and other compounds that have similar chemical structures, the same mechanism of action (i.e. binding to the same biological target), similar modes of action, and/or are used to treat the similar diseases. In several dominant drug classification systems, these four types of classifications form a hierarchy. For example, the fibrates are a chemical class of drugs (amphipathic carboxylic acids) that share the same mechanism of action (PPAR agonist) and mode of action (reducing blood triglycerides), and that are used to prevent and treat the same disease (atherosclerosis).
Bayes estimatorIn estimation theory and decision theory, a Bayes estimator or a Bayes action is an estimator or decision rule that minimizes the posterior expected value of a loss function (i.e., the posterior expected loss). Equivalently, it maximizes the posterior expectation of a utility function. An alternative way of formulating an estimator within Bayesian statistics is maximum a posteriori estimation. Suppose an unknown parameter is known to have a prior distribution .
Point estimationIn statistics, point estimation involves the use of sample data to calculate a single value (known as a point estimate since it identifies a point in some parameter space) which is to serve as a "best guess" or "best estimate" of an unknown population parameter (for example, the population mean). More formally, it is the application of a point estimator to the data to obtain a point estimate. Point estimation can be contrasted with interval estimation: such interval estimates are typically either confidence intervals, in the case of frequentist inference, or credible intervals, in the case of Bayesian inference.
Drug designDrug design, often referred to as rational drug design or simply rational design, is the inventive process of finding new medications based on the knowledge of a biological target. The drug is most commonly an organic small molecule that activates or inhibits the function of a biomolecule such as a protein, which in turn results in a therapeutic benefit to the patient. In the most basic sense, drug design involves the design of molecules that are complementary in shape and charge to the biomolecular target with which they interact and therefore will bind to it.
Prescription drugA prescription drug (also prescription medication, prescription medicine or prescription-only medication) is a pharmaceutical drug that is permitted to be dispensed only to those with a medical prescription. In contrast, over-the-counter drugs can be obtained without a prescription. The reason for this difference in substance control is the potential scope of misuse, from drug abuse to practicing medicine without a license and without sufficient education. Different jurisdictions have different definitions of what constitutes a prescription drug.
Experimental uncertainty analysisExperimental uncertainty analysis is a technique that analyses a derived quantity, based on the uncertainties in the experimentally measured quantities that are used in some form of mathematical relationship ("model") to calculate that derived quantity. The model used to convert the measurements into the derived quantity is usually based on fundamental principles of a science or engineering discipline. The uncertainty has two components, namely, bias (related to accuracy) and the unavoidable random variation that occurs when making repeated measurements (related to precision).
Grapefruit–drug interactionsSome fruit juices and fruits can interact with numerous drugs, in many cases causing adverse effects. The effect is most studied with grapefruit and grapefruit juice, but similar effects have been observed with certain other citrus fruits. The effect was first discovered accidentally in 1991, when a test of drug interactions with alcohol used grapefruit juice to hide the taste of the ethanol. A 2005 medical review advised patients to avoid all citrus juices until further research clarifies the risks.
Bayesian inferenceBayesian inference (ˈbeɪziən or ˈbeɪʒən ) is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. Bayesian inference is an important technique in statistics, and especially in mathematical statistics. Bayesian updating is particularly important in the dynamic analysis of a sequence of data. Bayesian inference has found application in a wide range of activities, including science, engineering, philosophy, medicine, sport, and law.
Propagation of uncertaintyIn statistics, propagation of uncertainty (or propagation of error) is the effect of variables' uncertainties (or errors, more specifically random errors) on the uncertainty of a function based on them. When the variables are the values of experimental measurements they have uncertainties due to measurement limitations (e.g., instrument precision) which propagate due to the combination of variables in the function. The uncertainty u can be expressed in a number of ways. It may be defined by the absolute error Δx.
