Pharmacokinetic models, biologically based

Connally, R. and Anderson, M. (1991). Biologically based pharmacokinetic models Tools for toxicological research risk assessment. Annu. Rev. Pharmacol. Toxicol. 31 503-523. 

Urinary and fecal elimination can be nonlinear because of active elimination processes. Biologically based pharmacokinetic models are useful for predicting these nonlinear behaviors because they are based on first principles instead of being strictly empirical. 

Figure 6.1 Schematic of a simple biologically based pharmacokinetic model showing five well-stirred compartments, each with arterial and venous blood flow signified by the arrows. Chemioal flux is shown as an input to the skin compartment, and metabolism Is shown as a loss from the liver compartment.

Tardif et al. (1997) developed a physiologically based pharmacokinetic model for zneio-xylene in rats and humans. They also simulated interactions between weto-xylene, toluene and ethylbenzene, and showed that for exposures at air concentrations remaining within the permissible range for a mixture, biologically significant interactions at the pharmacokinetic level would not occur. 

Much of the research efforts in risk assessment are therefore aimed at reducing the need to use these default uncertainty factors, although the risk assessor is limited by data quality of the chemical of interest. With sufficient data and the advent of sophisticated and validated physiologically based pharmacokinetic models and biologically based dose-response models (Conolly and Butterworth, 1995), these default values can be replaced with science-based factors. In some instances there may be sufficient data to be able to obtain distributions rather than point estimates. 

Liao KH. 2004. Development and validation of a hybrid reaction network/physiologically based pharmacokinetic model of benzo[a]pyrene and its metabolites. PhD dissertation, Department of Chemical and Biological Engineering, Colorado State University, Fort Collins (CO). 

Perbellini L, Mozzo P, Olivato D, Brugnone F. Dynamic biological exposure indexes for n-hexane and 2,5-hexanedione, suggested by a physiologically based pharmacokinetic model. Am Ind Hyg Assoc J 1990 51 356-62. 

McDougal JN, Zheng Y, Zhang Q, Conolly R. Biologically based pharmacokinetic and pharmacodynamic models of skin. In Riviere JE, editor, Dermal absorption models in toxicology and pharmacology. New York Taylor and Francis, 2006. p. 89-112. 

Biologically Based Pharmacokinetic and Pharmacodynamic Models of the Skin... 

In summary, biologically based pharmacokinetic and pharmacodynamic models have tremendous potential to help solve problems in the skin. These models are especially useful for predicting pharmacokinetics and system responses that are nonUnear because they are based on first principles. They can also help design expraiments and develop and test hypotheses. Ultimately, these models can be used to improve risk assessments or develop prophylactic or therapentic approaches. 

Physiologically Based Pharmacokinetic (PBPK) Model—is comprised of a series of compartments representing organs or tissue groups with realistic weights and blood flows. These models require a variety of physiological information tissue volumes, blood flow rates to tissues, cardiac output, alveolar ventilation rates and, possibly membrane permeabilities. The models also utilize biochemical information such as air/blood partition coefficients, and metabolic parameters. PBPK models are also called biologically based tissue dosimetry models. 

Risk Assessment. This model successfully described the disposition of chloroform in rats, mice and humans following various exposure scenarios and developed dose surrogates more closely related to toxicity response. With regard to target tissue dosimetry, the Corley model predicts the relative order of susceptibility to chloroform toxicity consequent to binding to macromolecules (MMB) to be mouse > rat > human. Linking the pharmacokinetic parameters of this model to the pharmacodynamic cancer model of Reitz et al. (1990) provides a biologically based risk assessment model for chloroform. 

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