Physiological pharmacokinetics estimation

HSG Chen, JF Gross. Estimation of tissue-to-plasma partition coefficients used in physiological pharmacokinetic models. J Pharmacokin Biopharm 7 117-125, 1979. 

JM Gallo, FC Lam, DG Perrier. Moment method for the estimation of mass transfer coefficients for physiological pharmacokinetic models. Biopharm Drug Dispos 12 127-137, 1991. 

Evans, M.V. Simmons, J.E. (1996) Physiologically based pharmacokinetic estimated metabolic constants and hepatotoxicity of carbon tetrachloride after methanol pretreatment in rats. Toxicol, appl. Pharmacol., 140, 245-25,3... 

Of the various methods that may be used to determine bioavailability for ASOs, the best refer to tissue levels as the most relevant metric for calculating an estimate of absolute bioavailability. As mentioned in Chapter 4, ASOs distribute rapidly to the tissues, with an extremely slow transfer rate back into the central circulation. In addition, the elimination of ASOs occurs predominantly by nucleases in the tissue compartment. Thus, bioavailability based on plasma concentrations does not provide an accurate estimate of absolute bioavailability for ASOs if plasma concentrations cannot be quantified at extremely low concentrations for a prolonged period of time to adequately assess systemic exposure. The direct use of tissue levels in combination with physiologic pharmacokinetic modeling, however, may allow the accurate determination of bioavailability for ASOs. 

Recent advances in the field of physiological pharmacokinetics, in which organ blood flows, volumes, and drug clearances are considered, have been useful in estimating drug concentrations in a specific organ. These models have been applied for the most part to antitumor agents. 

Leung 1993). PBPK models for a particular substance require estimates of the chemical substance-specific physicochemical parameters, and species-specific physiological and biological parameters. The numerical estimates of these model parameters are incorporated within a set of differential and algebraic equations that describe the pharmacokinetic processes. Solving these differential and algebraic equations provides the predictions of tissue dose. Computers then provide process simulations based on these solutions. 

PBPK and classical pharmacokinetic models both have valid applications in lead risk assessment. Both approaches can incorporate capacity-limited or nonlinear kinetic behavior in parameter estimates. An advantage of classical pharmacokinetic models is that, because the kinetic characteristics of the compartments of which they are composed are not constrained, a best possible fit to empirical data can be arrived at by varying the values of the parameters (O Flaherty 1987). However, such models are not readily extrapolated to other species because the parameters do not have precise physiological correlates. Compartmental models developed to date also do not simulate changes in bone metabolism, tissue volumes, blood flow rates, and enzyme activities associated with pregnancy, adverse nutritional states, aging, or osteoporotic diseases. Therefore, extrapolation of classical compartmental model simulations... 

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. 

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