Pharmacokinetic models compartmental

Rates of hydroquinone glucuronidation in human liver microsomes showed a two- to three-fold variation between individual liver samples they were somewhat higher than in the rat, and lower than in the mouse liver (Seaton et al., 1995). A compartmental pharmacokinetic model was derived to describe the pharmacokinetics of hydroquinone in vivo in humans, rats and mice, incorporating hydroquinone glucuronidation rates sulfation of hydroquinone was not included in this model. NAD(P)H quinone acceptor oxidoreductases protect against reactive quinones by reducing them to the hydroquinone this enzyme seems to be absent in some individuals, which will lead to loss of such protection and make them more sensitive to hydroquinone toxicity (Ross, 1996). 

A simple compartmental pharmacokinetic model was proposed by Seaton et al. (1995) to describe the phannacokinetics of hydroquinone in mice, rats and humans. The model did not include hydroquinone sulfation, which does occur in rats and possibly in mice, although glucuronidation is the major reaction. Phenol and hydroquinone may mutually inhibit their sulfation if both are present simultaneously in the rat (Legathe etal., 1994). 

A liquid chromatography/tandem mass spectrometry (LC/MS/MS) method was developed [33] and validated for the determination of donepezil in human plasma samples. Diphenhydramine was used as the IS. The collision-induced transition m/z 380 > 91 was used to analyze donepezil in selected reaction monitoring mode. The signal intensity of the m/z 380 —> 91 transition was found to relate linearly with donepezil concentrations in plasma from 0.1 to 20.0 ng/ml. The lower limit of quantification of the LC/MS/MS method was 0.1 ng/ml. The intra- and inter-day precisions were below 10.2% and the accuracy was between 2.3% and +2.8%. The validated LC/MS/MS method was applied to a pharmacokinetic study in which healthy Chinese volunteers each received a single oral dose of 5 mg donepezil hydrochloride. The non-compartmental pharmacokinetic model was used to fit the donepezil plasma concentration-time curve. Maximum plasma concentration was... 

When the dose of a drug is administered as an intravenous bolus, the volume of distribution at steady-state (Vd(ss)) can be calculated. This parameter represents the volume in which a drug would appear to be distributed during steady-state if the drug existed throughout that volume at the same concentration as in the measured fluid (plasma or blood). The volume of distribution at steady-state is generally calculated by a non-compartmental method, which is based on the use of areas (Benet Galeazzi, 1979) and does not require the application of a compartmental pharmacokinetic model or mathematical description of the disposition curve ... 

The advantages of using non-compartmental methods for calculating pharmacokinetic parameters, such as systemic clearance (CZg), volume of distribution (Vd(area))/ systemic availability (F) and mean residence time (MRT), are that they can be applied to any route of administration and do not entail the selection of a compartmental pharmacokinetic model. The important assumption made, however, is that the absorption and disposition processes for the drug being studied obey first-order (linear) pharmacokinetic behaviour. The first-order elimination rate constant (and half-life) of the drug can be calculated by regression analysis of the terminal four to six measured plasma... 

Fig. 3.2 Analogue computer-generated curves showing the levels (as fraction of the intravenous dose) of benzylpenicillin in the central (serum) and peripheral (tissue) compartments of the two-compartment pharmacokinetic model and the cumulative amount excreted unchanged in the urine as a function of time. The curves are based on the first-order rate constants (k12, k21, kel) associated with the compartmental pharmacokinetic model. Note...

Figure 24.3 Compartmental pharmacokinetic model linking skin absorption determined in an in vitro model to a systemic model to predict plasma concentration time profiles in vivo.

Stirred tank models have been widely used in pharmaceutical research. They form the basis of the compartmental models of traditional and physiological pharmacokinetics and have also been used to describe drug bioconversion in the liver [1,2], drug absorption from the gastrointestinal tract [3], and the production of recombinant proteins in continuous flow fermenters [4], In this book, a more detailed development of stirred tank models can be found in Chapter 3, in which pharmacokinetic models are discussed by Dr. James Gallo. The conceptual and mathematical simplicity of stirred tank models ensures their continued use in pharmacokinetics and in other systems of pharmaceutical interest in which spatially uniform concentrations exist or can be assumed. 

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. 

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... 

There are several approaches to pharmacokinetic modelling. These include empirical, compartmental, clearance-based and physiological models. In the latter full physiological models of blood flow to and from all major organs and tissues in the body are considered. Such models can be used to study concentration-time profiles in the individual organs and e. g. in the plasma [57-60]. Further progress in this area may result in better PK predictions in humans [61]... 

Non-compartmental or model-independent approaches to pharmacokinetics Pharmacodynamics of drug action Pharmacokinetic-pharmacodynamic models INTRODUCTION... 

This definition remains model-dependent, but VDSS can be calculated using a non-compartmental approach, which does not require any assumptions about the pharmacokinetic model concerned (see below). 

The discussion above provides a brief qualitative introduction to the transport and fate of chemicals in the environment. The goal of most fate chemists and engineers is to translate this qualitative picture into a conceptual model and ultimately into a quantitative description that can be used to predict or reconstruct the fate of a chemical in the environment (Figure 27.1). This quantitative description usually takes the form of a mass balance model. The idea is to compartmentalize the environment into defined units (control volumes) and to write a mathematical expression for the mass balance within the compartment. As with pharmacokinetic models, transfer between compartments can be included as the complexity of the model increases. There is a great deal of subjectivity to assembling a mass balance model. However, each decision to include or exclude a process or compartment is based on one or more assumptions—most of which can be tested at some level. Over time the applicability of various assumptions for particular chemicals and environmental conditions become known and model standardization becomes possible. 

Pharmacokinetic models. An important advance in risk assessment for hazardous chemicals has been the application of pharmacokinetic models to interpret dose-response data in rodents and humans (EPA, 1996a Leung and Paustenbach, 1995 NAS/NRC, 1989 Ramsey and Andersen, 1984). Pharmacokinetic models can be divided into two categories compartmental or physiological. A compartmental model attempts to fit data on the concentration of a parent chemical or its metabolite in blood over time to a nonlinear exponential model that is a function of the administered dose of the parent. The model can be rationalized to correspond to different compartments within the body (Gibaldi and Perrier, 1982). 

Although, during the early applications of therapeutic mAbs, pharmacokinetic modeling was rarely applied, a variety of analytical techniques has been used over the years to characterize the pharmacokinetics of this class of compounds. The application and information derived from three different methods of noncompart-mental analysis, individual compartmental analysis, and population analysis will be discussed in the following sections. 

Due to its compartmental nature, the CAT model can be easily coupled with the disposition of drug in the body using classical pharmacokinetic modeling. In this respect the CAT model has been used to interpret the saturable small-intestinal absorption of cefatrizine in humans [175]. 

PBPK model Physiologically based pharmacokinetic model. Physiologically based compartmental model used to characterize pharmacokinetic behavior of a chemical. Available data on blood flow rates, and metabolic and other processes, which the chemical undergoes within each compartment are used to construct a mass-balance framework for the PBPK model. 

BeUnier and Dougherty have recently reported a preliminary pharmacokinetic study of fV Photofrin (PF) in patients. These researchers determined that their data, taken from a 19 patient study involving the administration of 1 mg PF/kg, for a three-compartmental pharmaeokinetic model. The a, fi and y half-hves were 16 h, 7.5 days, and 156 days, respectively. For more details, see ref. 203. The pK data obtained for BPD-MA was obtained by personal communication with David Mitchell, Director of Regulatory Affairs, QLT Phototherapeutics. 

Reaction rate parameters required for the distributed pharmacokinetic model generally come from independent experimental data. One source is the analysis of rates of metabolism of cells grown in culture. However, the parameters from this source are potentially subject to considerable artifact, since cofactors and cellular interactions may be absent in vitro that are present in vivo. Published enzyme activities are a second source, but these are even more subject to artifact. A third source is previous compartmental analysis of a tissue dosed uniformly by intravenous infusion. If a compartment in such a study can be closely identified with the organ or tissue later considered in distributed pharmacokinetic analysis, then its compartmental clearance constant can often be used to derive the required metabolic rate constant. 

The development of a successful pharmacokinetic model allows one to summarize large amounts of data into a few values that describe the whole data set. The general procedure used to develop a pharmacokinetic model is outlined in Table 10.1. Certain aspects of this procedure have been described previously in Chapters 3 and 8. For example, the technique of curve peeling" frequently is used to indicate the number of compartments that are included in a compartmental model. In any event, the eventual outcome should be a model that can be used to interpolate or extrapolate to other conditions. 

Other approaches have been used for more complex models. These include curve stripping or the method of residuals,either manually or using a computer program such as CSTRIP and ESTRIF. These techniques can separate a multiexponential curve into its component parts for initial estimates. Other techniques include deconvolution methods specific to the one and two compartment pharmacokinetic models. The objective of the deconvolution method is to mathematically subtract the results obtained after IV administration from the oral or extravascular data. This results in information about the input or absorption process alone. More general methods have been presented by various researchers that do not rely on a particular compartmental model. ... 

The principal parameter used to indicate the rate of drug absorption is Cmax, even though it is also influenced by the extent of absorption the observed fmaX is less reliable. Because of the uncertainty associated with Cmax, it has been suggested (Endrenyi Yan, 1993 Tozer, 1994) that Cmax/AUCo-loq/ where AUCo-loq is the area under the curve from time zero to the LOQ of the acceptable analytical method, may more reliably measure the rate of drug absorption, except when multiexponential decline is extensive. Estimation of the terms should be based on the observed (measured) plasma concentrationtime data and the use of non-compartmental methods rather than compart-mental pharmacokinetic models. MRTs, from time zero to the LOQ of the analytical method, for the test and reference products can be compared, assuming that first-order absorption and disposition of the drug apply (Jackson Chen, 1987). 

---