Physiologically-based pharmacokinetic PB-PK modelling

Suzuki H, Iwatsubo T, Sugiyama Y. 1995. Applications and prospects for physiologically based pharmacokinetic (PB-PK) models involving pharmaceutical agents. Toxicol Lett 82/83 349-355. 

Sweeney, R.E., Langenberg, J.P., Maxwell, D.M. (2006). A physiologically based pharmacokinetic (PB/PK) model for multiple exposure routes of soman in multiple species. Arch. Toxicol. 80 719-31. 

Physiologically based pharmacokinetic (PB-PK) models for some JP-8 components have been developed to understand the relationship between vapor concentrations and accumulation in tissue and blood compartments. When appropriately developed and validated, PB-PK models can provide a time course of distribution of a chemical or its metabolites in tissues and show the effect of changingphysiologic characteristics on plasma and tissue concentrations. PB-PK models have been applied to predict toxicokinetic parameters and to scale dose in different species. 

Andersen. M. E. (1995). Physiologically based pharmacokinetic (PB-PK) models in the study of the disposition and biological effects of xenobioiic.s and drugs. Toxicol. Ixtll. 82/83, 341-348. 

In addition to a large database on lead exposures assembled empirically, a number of biokinetic models to ascertain exposure biomarkers and body lead burdens exist in the more recent lead literature, mainly in the form of such biomarkers of exposure as PbB. These predictive models of systemic lead exposure are of differing complexity and utility in diverse exposure settings. Historically, they can be defined as classical compartment models, a hybrid of the compartmental and physiologically based pharmacokinetic (PB-PK) models or the PB-PK model type. 

Another method of predicting human pharmacokinetics is physiologically based pharmacokinetics (PB-PK). The normal pharmacokinetic approach is to try to fit the plasma concentration-time curve to a mathematical function with one, two or three compartments, which are really mathematical constructs necessary for curve fitting, and do not necessarily have any physiological correlates. In PB-PK, the model consists of a series of compartments that are taken to actually represent different tissues [75-77] (Fig. 6.3). In order to build the model it is necessary to know the size and perfusion rate of each tissue, the partition coefficient of the compound between each tissue and blood, and the rate of clearance of the compound in each tissue. Although different sources of errors in the models have been... 

Physiologically based pharmacokinetic models provide a format to analyze relationships between model parameters and physicochemical properties for a series of drug analogues. Quantitative structure-pharmacokinetic relationships based on PB-PK model parameters have been pursued [12,13] and may ultimately prove useful in the drug development process. In this venue, such relationships, through predictions of tissue distribution, could expedite drug design and discovery. 

Physiologically based pharmacokinetic modeling (PB-PK) accurately describes nonlinear biochemical and physical processes computer hardware and... 

Physiologic model-physiologically based pharmacokinetic model (PB/PK) A physiologically based model for Gl transit and absorption in humans is presented. The model can be used to study the dependency of the fraction dose absorbed (Fabs) of both neutral and ionizable compounds on the two main physico-chemical input parameters [the intestinal permeability coefficient (Pint) and the solubility in the intestinal fluids (Sint)] as well as the physiological parameters, such as the gastric emptying time and the intestinal transit time. For permeability-limited compounds, the model produces the established sigmoidal dependence between Fabs and Pnt. In case of solubility-limited absorption, the model enables calculation of the critical mass-solubility ratio, which defines the onset of nonlinearity in the response of fraction absorbed to dose. In addition, an analytical equation to calculate the intestinal permeability coefficient based on the compound s membrane affinity and MW was used successfully in combination with the PB-PK model to predict the human fraction dose absorbed of compounds with permeability-limited absorption. Cross-validation demonstrated a root-mean-square prediction error of 7% for passively absorbed compounds. 

OR PEL PB-PK model RD50 REL SCE TOMM TWA UDS USAF odds ratio permissible exposure level physiologically based pharmacokinetic model respiratory depression in 50% of the animals tested recommended exposure limit sister chromatid exchange test of memory and motivation time-weighted average unscheduled DNA synthesis U.S. Air Force... 

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