Physiological pharmacokinetics distribution, volume

The three estimates of distribution volume that we have encountered have slightly different properties (24). Of the three, Vd(ss) has the strongest physiologic rationale for multicompartment systems of drug distribution. It is independent of the rate of both drug distribution and elimination, and is the volume that is referred to in Equations 3.1 and 3.2. On the other hand, estimates of V ( area) most useful in clinical pharmacokinetics, since it is this volume that links elimination clearance to elimination half-life in the equation... 

Half-life has little value as an indicator of the processes involved in either drug elimination or distribution. Yet, early studies of drug pharmacokinetics in disease states have relied on drug half-life as the sole measure of alteration in drug disposition. Disease states can affect the physiologically related parameters, volume of distribution and clearance thus, the derived parameter, half-life, will not necessarily reflect the expected change in drug elimination. 

An extensive retrospective analysis [11] examined various scahng approaches to the prediction of clinical pharmacokinetic parameters. In this analysis the most successful predictions of volume of distribution were achieved by calculating unbound fraction in tissues (/(,) of animals and assuming this would be similar in man. Volume of distribution was then calculated using measured plasma protein binding values and standard values for physiological parameters such as extracellular fluid and plasma volumes. The equation used was as follows ... 

It is possible to predict what happens to Vd when fu or fur changes as a result of physiological or disease processes in the body that change plasma and/or tissue protein concentrations. For example, Vd can increase with increased unbound toxicant in plasma or with a decrease in unbound toxicant tissue concentrations. The preceding equation explains why because of both plasma and tissue binding, some Vd values rarely correspond to a real volume such as plasma volume, extracellular space, or total body water. Finally interspecies differences in Vd values can be due to differences in body composition of body fat and protein, organ size, and blood flow as alluded to earlier in this section. The reader should also be aware that in addition to Vd, there are volumes of distribution that can be obtained from pharmacokinetic analysis of a given data set. These include the volume of distribution at steady state (Vd]SS), volume of the central compartment (Vc), and the volume of distribution that is operative over the elimination phase (Vd ea). The reader is advised to consult other relevant texts for a more detailed description of these parameters and when it is appropriate to use these parameters. 

In pharmacokinetics empirical models are for example compartment models where the body is sub-divided into one or more compartments and the drug is assumed to distribute and be eliminated with first-order rate constants. Typical model parameters are the rate constants and the volumes of the compartments. The compartmental models reflect the physiological reality only to a very limited degree. Despite this limitation compartment models are essential in drug development and have received considerable attention and showed huge utility and impact on the labeling of drugs on the market [4]. 

The PPK approach estimates the joint distribution of population specific pharmacokinetic model parameters for a given drug. Fixed effect parameters quantify the relationship e.g. of clearance to individual physiology like function of liver, kidney, or heart. The volume of distribution is typically related to body size. Random effect parameters quantify the inter-subject variability which remains after the fixed effects have been taken into account. Then the observed concentrations will still be randomly distributed around the concentration time course predicted by the model for an individual subject. This last error term called residual variability... 

Poulin and Theil have developed a mechanistic model for estimating the Vd based on physiologically based pharmacokinetics (PBPK). For this method, the tissue plasma partition coefficient for each organ of the body is calculated by consideration of the volume fraction of neutral and phospholipids and water found in the tissues of a particular organ. For example, the volume fraction of neutral lipids in human adipose tissue is 0.79 whereas the volume fraction of neutral lipids in cardiac tissue is 0.0115. By contrast the volume fraction of water in adipose and heart are 0.18 and 0.76 respectively. Combined with the P, these volume fractions are used to estimate the distribution of a drag molecule into each tissue. Summation of the product of tissue volume and tissue/plasma partition coefficient produces the estimate of Vd. ... 

EXHIBIT A Anatomical and Physiological Considerations Unique to Children. differences in anatomy. allometric scaling factors (e.g. increased surface area-to-volume ratio) cardiovascular status permeability of the pediatric blood-brain barrier (BBB). dermatologic factors (e.g. increased cutaneous blood flow) (Fluhr et al., 2000 Simonen et al, 1997). increased skin pH (Fluhr et al., 2004 Behrendt and Green, 1958) plasma protein binding volume of distribution (V ) organ size and maturity pharmacokinetic maturity (e.g. metabolic differences) (Fairley and Rasmussen, 1983)... 

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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