Physiologically based pharmacokinetic parameters

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. 

Simulation methods have also been developed that include physiologically based pharmacokinetic modeling (PBPK) and methods such as Cloe PK, OMPPPlus, GastroPlus , SimCYP , and others [122] that are described elsewhere in this book. It is likely that the computational metabolism predictions could be integrated with these to assist in deriving more accurate predictions of human pharmacokinetic parameters. 

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. 

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. 

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. 

RP Brown, MD Delp, SL Lindstedt, LR Rhomberg, RP Beliles. Physiological parameter values for physiologically based pharmacokinetic models. Toxicol Ind Health 13 407-484, 1997. 

Absorbed lead is distributed in various tissue compartments. Several models of lead pharmacokinetics have been proposed to characterize such parameters as intercompartmental lead exchange rates, retention of lead in various pools, and relative rates of distribution among the tissue groups. See Section 2.3.5 for a discussion of the classical compartmental models and physiologically based pharmacokinetic models (PBPK) developed for lead risk assessments. 

Clewell HJ, Lee T, Carpenter RL. 1994. Sensitivity of physiologically based pharmacokinetic models to variation in model parameters methylene chloride. Risk Analysis 14 521-531. 

H. K., Uncertainties in physiologically based pharmacokinetic models caused by several input parameters, bit. Arch. Occup. Environ. Health 1999, 72, 247— 254. 

A physiologically based pharmacokinetic model for predicting ethylene dibromide kinetics and consequent toxicity, based on in-vitro metabolic parameters of rodents and humans and on the use of scaling factors, has been presented (Ploemen et al., 1997). Its most important prediction is that the GST pathway is significantly active even at low ethylene dibromide concentrations, which has important implications for risk assessment. 

CLEWELL, H.J., LEE, T.S. and CARPENTER, R.L. (1994). Sensitivity of physiologically-based pharmacokinetics models to variation in model parameters Methylene chloride, Risk Anal. 14, 533-554. 

Hattis D, Ginsberg G, Sonawane B, Smolenski S, Russ A, Kozlak M, Goble R (2003) Differences in pharmacokinetics between children and adults — II. Children s variability in drug elimination half-lives and in some parameters needed for physiologically-based pharmacokinetic modeling. Risk Anal, 23 117-142. 

Poulin and Krishnan (1995) developed a method to predict tissue blood PCs for incorporation into physiologically based pharmacokinetic (PBPK) models. Tissue blood partitioning was calculated as an additive function of partitioning into the water, neutral lipids and phospholipids constituent of individual tissues. These were calculated using published values for lipid and water content of tissues and the octanol-water PC of the compounds. Poulin and Krishnan (1998 1999) used this method to predict tissue blood PCs that were subsequently incorporated into a quantitative structure-toxicokinetic model. The prediction of tissue plasma PCs to describe distribution processes and as input parameters for PBPK models has been extensively researched by Poulin and coworkers a great deal of further information can be obtained from their references (Poulin and Theil, 2000 Poulin et al., 2001 Poulin and Theil, 2002a Poulin and Theil, 2002b). 

Exposures of newborns to PAHs depend on pharmacokinetic processes operating in the mother, and transfer through breast milk. Since it is difficult to characterize these pathways in humans, physiologically based pharmacokinetic (PBPK) and pharmacodynamic (PD) models need to be developed using appropriate animal models, and incorporating key parameters such as dose, exposure duration, and developmental stage (Dorman et al, 2001). Thus, development of PBPK and PBPD models for PAHs is an immediate need that will help in not only characterizing the dose-response relationship, but also extrapolation of results from animal studies to humans. 

As discussed in Chapter 30 and elsewhere (13), interspecies scaling is based upon allometry (an empirical approach) or physiology. Protein pharmacokinetic parameters such as volume of distribution (Pd), elimination half-life (b/2)/ and elimination clearance (CL) have been scaled across species using the standard allometric equation (14) ... 

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