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The two domains in clinical pharmacology dealing with optimizing dosing recommendations are pharmacokinetics and pharmacodynamics. Pharmacokinetics characterized concentration-time courses of drugs in different body fluids, whereas pharmacodynamics was used to either describe concentration-effect relationships or the time course of pharmacological effect after dosing. PK/PD modeling can elucidate the causative relationship between drug exposure and response and provide a better understanding of the sequence of events that results in the observed drug effect. This information can then be used to streamline the drug development process and dose optimization.
Pharmacokinetic models developed at present include compartmental, physiologically based, and statistical. Measurements of the active compound, the free fraction, active metabolite, or active enantiomer must be performed with fully validated analytic methodologies. When experimental studies are carried out, it is strongly advised that the number of measurements (concentration, but also effect) be as large as possible to obtain the greatest precision in parameter estimation.
In PK/PD modeling, the availability of realistic measures of pharmacologic response intensity is a basic consideration. The pharmacodynamic analysis involves quantifying drug concentration/effect relationships. Ideally, concentrations should be measured at the effect site, the site of action or biophase, where the interaction with the respective biological receptor system takes place, but in most situations, this is not possible. In the plotting of drug effect vs concentrations, connecting data in chronological order may confirm the appearance of a hysteresis loop, in which one effect corresponds to more than one concentration. If such a phenomenon were not present, basic pharmacodynamic models could be used. Otherwise, more complex, time-dependent models must be employed.
Most drugs have their target site outside the plasma. Hence, distribution to the site of action might represent a rate-limiting step in the onset and the duration of the effect. The so-called “effect compartment model” has been successfully applied to account for hysteresis caused by distribution to extracellular targets by passive diffusion. Using this model, meaningful drug concentration-effect relationships have been estimated in pre-clinical animal studies. However, target distribution kinetics might be more complex, particularly for drugs acting on intracellular targets and/or with a site of action in organs protected by specific barriers.
Fig.1 A typical whole-body physiologically based pharmacokinetic model. (Danhof, 2008)
Modeling target binding and activation aim at predicting in vivo drug concentration-effect relationships, which depend on numerous factors related to the drug and the biological system. Specifically, the prediction of in vivo drug concentration-effect relationships requires making a strict distinction between “drug-specific” and “biological system-specific” parameters as predictors of the concentration-effect relationship.
Fig.2 The shape and location, in terms of concentration, of in vivo drug concentration-effect relationships is determined by drug-specific and biological system-specific properties. (Danhof, 2008)
In PK/PD modeling the concept of “transduction” refers to the processes that govern the transduction of target activation into the response in vivo.
The application of PK/PD modeling and simulation principles represents an opportunity to identify optimal drug candidates and possibly to develop drugs in the shortest time frame possible. Incorporation of PK/PD studies throughout preclinical and clinical development may lead to earlier identification of optimal dosing regimens in clinical development and may contribute to shortening the overall time of drug development. In addition, the increased understanding of drug action derived from PK/PD-based drug development may lead to a definition of strategies for individualization of drug dosage regimens to ensure optimal therapeutic outcomes. The building of a PK/PD database during drug development can provide an essential framework for continued refinement and improvement during post marketing drug use.
A primary objective of PK/PD modeling is to identify key properties of a drug in vivo; this allows characterization and prediction of the time-course of drug effects under physiologic and pathologic conditions. In terms of application, PK/PD modeling has been proposed as relevant in all phases of drug development. Novel concepts of mechanism-based PK/PD modeling have been developed, which constitute a scientific basis for predicting drug effects in humans based on information from pre-clinical in vitro and in vivo investigations.
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