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Physiologically based pharmacokinetic using

Absorption, distribution, biotransformation, and excretion of chemical compounds have been discussed as separate phenomena. In reality all these processes occur simultaneously, and are integrated processes, i.e., they all affect each other. In order to understand the movements of chemicals in the body, and for the delineation of the duration of action of a chemical m the organism, it is important to be able to quantify these toxicokinetic phases. For this purpose various models are used, of which the most widely utilized are the one-compartment, two-compartment, and various physiologically based pharmacokinetic models. These models resemble models used in ventilation engineering to characterize air exchange. [Pg.270]

What are called physiologically based pharmacokinetic (PBPK) and pharmacodynamic (PBPD) models are more mechanistically complex and often include more compartments, more parameters, and more detailed expressions of rates and fluxes and contain more mechanistic representation. This type of model is reviewed in more detail in Section 22.5. Here, we merely classify such models and note several characteristics. PBPK models have more parameters, are more mechanistic, can exploit a wider range of data, often represent the whole body, and can be used both to describe and interpolate as well as to predict and extrapolate. Complexity of such models ranges from moderate to high. They typically contain 10 or more compartments, and can range to hundreds. The increase in the number of flux relationships between compartments and the related parameters is often more than proportional to compartment count. [Pg.537]

Clewell HJ 3rd, Gentry PR, Covington TR, Gearhart JM. Development of a physiologically based pharmacokinetic model of trichloroethylene and its metabolites for use in risk assessment. Environ Health Perspect 2000 May 108 Suppl 2 283-305. [Pg.551]

Cronin WJ, Oswald EJ, Shelley ML, et al. 1995. A trichloroethylene risk assessment using a Monte Carlo analysis of parameter uncertainty in conjunction with physiologically-based pharmacokinetic modeling. Risk Anal 15 555-565. [Pg.259]

Geary RS, Wall CM, Miller MA, et al. 1994. Partition coefficient measurements of diisopropyl methylphosphonate (DIMP) and trichloroethylene in rats using microdialysis and incorporated in physiologically-based pharmacokinetic (PBPK) modelling [Abstract], Society of Toxicology 33rd Annual Meeting, Dallas, TX 13-17 March, 1994. Paper No. 82. [Pg.148]

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. [Pg.75]

RS Thomas, WE Lytle, TJ Keefe, AA Constan, RSH Yang. Incorporating Monte Carlo simulation into physiologically based pharmacokinetic models using advanced continuous simulation language (ACSL) A computational method. Fundam Appl Toxicol 31 19-28, 1996. [Pg.102]

Other major early contributions of biochemical engineering have been in the development of the artificial kidney and physiologically based pharmacokinetic models. The artificial kidney has been literally a lifesaver. Pharmacokinetic models divide the body of an animal or human into various compartments that act as bioreactors. These mathematical models have been used very successfully in developing therapeutic strategies for the optimal delivery of chemotherapeutic drugs and in assessing risk from exposure to toxins. [Pg.102]

Levitt, D.G., The use of a physiologically based pharmacokinetic model to evaluate deconvolution measurements of systemic absorption, BMC Clin. Pharmacol, 3,1, 2003. [Pg.373]

Clewell HJ III, Andersen ME. 1985. Risk assessment extrapolations using physiologically-based pharmacokinetic modeling. Toxicol Ind Health 1 111-131. [Pg.258]

Reitz RH, Mendrala AL, Corley RA, et al. 1990. Estimating the risk of liver cancer associated with human exposures to chloroform using physiologically based pharmacokinetic modeling. Toxicol Appl Pharmacol 105 443-459. [Pg.283]

The newer physiologically based pharmacokinetic (PBPK) models take nonlinearity of physiological processes such as chemical metabolism and excretion into consideration. At the high dose levels used in animal experiments, these mechanisms become saturated with the result that the tissues may be exposed to a different composition of pure compound and metabolites than at the low dose levels encountered in real-life human exposure. [Pg.107]

If physiologically based pharmacokinetic (PBPK) models cannot be used, interspecies extrapolation is best undertaken by means of scaling according to basal metabolic rate, see Section 5.3.2.3. A second aspect, interspecies variability, should be considered in cases where a higher than average level of safety (achieved by consideration of a higher percentile of the substances) is desired. [Pg.223]

Physiologically Based Toxicokinetic (PBTK) models are derived similarly to Physiologically Based Pharmacokinetic (PBPK) models, which have been used for a number of years in the development of medicinal drugs. They describe the rat or man as a set of tissue compartments, i.e., liver, adipose tissues, poorly perfused tissues, and richly perfused tissues along with a description of metabolism in the liver. In case of volatile organic compounds a description of gas exchange at the level of the lung is included, see also Section 4.3.6. [Pg.377]

Reitz RH, Mendrala AL, Guengerich FP In vitro metabolism of methylene chloride in human and animal tissues Use in physiologically based pharmacokinetic models. Toxicol Appl Pharmacol 91 2h0-2A6, 1989... [Pg.474]

Poulin, P. and Theil, E.P. (2000) A priori prediction of tissue plasma partition coefficients of drugs to facilitate the use of physiologically-based pharmacokinetic models in drug discovery. Journal of Pharmaceutical Sciences, 89, 16-35. [Pg.239]


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