Tissue partitioning

Other important determinants of the effects of compounds, especially solvents, are their partition coefficients, e.g., blood-tissue partition coefficients, which determine the distribution of the compound in the body. The air-blood partition coefficient is also important for the absorption of a compound because it determines how quickly the compound can be absorbed from the airspace of the lungs into the circulation. An example of a compound that has a high air-blood partition coefficient is trichloroethane (low blood solubility) whereas most organic solvents (e.g., benzene analogues) have low air-blood partition coefficients (high blood solubility). 

Perhaps in light of the mechanism-based side effects, the therapeutic potential of SCD inhibitors has not been fully evaluated. The possibility exists that at least some of the chronic effects of SCD inhibition might be prevented by coadministration of fish oils or potentially a Toll4 antagonist [20]. However, coformulation of an SCD inhibitor with fish oil has not been reported. Another possibility is that SCD inhibitors with appropriate PK and tissue partitioning properties may limit mechanism-based side effects. 

However, others maintain that adipose tissue is an important contributor to VD. Bjorkman showed that adipose and muscle tissue partitioning are the two tissues that yield the best predictions of VDSS and that such data obtained in other tissues did not offer more accuracy [27]. (Note that the tissue partitioning data used to predict human VDSS were from rat or rabbit ex vivo measurements.) The emphasis on both adipose and muscle was also advocated by Poulin and Thiel in their prediction method that uses solvent/water partition coefficients [28] (see below). 

Physiological parameters for volumes and blood flow of the compartments are listed in Table 2-4. Physiologic constants (compartment volume, blood flows, etc) were taken from published values. Values for the solubility of n-hexanc in blood and tissues (partition coefficients) are taken from human tissue (Perbellini et al. 1985). Rate constants (Table 2-4, Figure 2-5) were estimated from animal and human data and are all assumed to be first-order. 

Gearhart JM, Seckel C, Vinegar A. 1993. In vivo metabolism of chloroform in B6C3Fi mice determined by the method of gas uptake the effects of body temperature on tissue partition coefficients and metabolism. Toxicol Appl Pharmacol 119(2) 258-66. 

Clearly, the mechanistic contributors to the extent of plasma and tissue binding are numerous, and the VD term represents a simplistic picture of potentially hundreds, maybe thousands, of individual tissue binding interactions. Despite this possible complexity, there may be a few individual types of tissue binding that are mostly responsible for tissue partitioning, and as described elsewhere in this chapter, this phenomena may be more related to non-specific interactions that are a function of gross physicochemical properties of the drug than specific binding interactions. 

In a first stage, distribution was predicted with tissue composition-based equations and the estimated tissue partition coefficients were combined with clearance estimated by direct scaling of hepatocyte intrinsic clearance in a PBPK model as described earlier. 

The inhalational anesthetics have distinctly different solubility (affinity) characteristics in blood as well as in other tissues. These solubility differences are usually expressed as coefficients and indicate the number of volumes of a particular agent distributed in one phase, as compared with another, when the partial pressure is at equilibrium (Table 25.3). For example, isoflurane has a blood-to-gas partition coefficient (often referred to as the Ostwald solubility coefficient) of approximately 1.4. Thus, when the partial pressure has reached equilibrium, blood will contain 1.4 times as much isoflurane as an equal volume of alveolar air. The volume of the various anesthetics required to saturate blood is similar to that needed to saturate other body tissues (Table 25.3) that is, the blood-tissue partition coefficient is usually not more than 4 (that of adipose tissue is higher). 

Gaigas et al. (1995) have developed a physiological toxicokinetic model of acrylonitrile in rats which includes the behaviour of CEO. In-vitro kinetic studies of the metabolism of both acrylonitrile and CEO showed that epoxidation to CEO is saturable, while glutathione conjugation of acrylonitrile follows first-order kinetics. The model combines these kinetic parameters with tissue partition data to allow simulation of the urinary excretion of acrylonitrile metabolites and the fonnation of haemoglobin adducts (see below). The model has been further refined by Kedderis et al. (1996) to predict the behaviour of acrylonitrile and CEO after inhalation exposure to acrylonitrile. 

The thickness of the tissue, partition coefficient, and the diffusion coefficient are properties of the mucosa and cannot be altered. Designing appropriate formulations that heed the necessary conditions can vary the surface area for delivery of the drug, time of contact, and the free drug concentration. The partitioning of the drug into the membrane will depend on... 

Thrall, K.D., R.A. Gies, J. Muniz, A.D. Woodstock, and G. Higgins. 2002. Route-of-entry and brain tissue partition coefficients for common superfund contaminants. J. Toxicol. Environ. Health A. 65(24) 2075-2086. 

Needham et al. (1991) also showed that human adipose tissue concentrations of CDDs may be correlated with blood serum levels after adjusting for total lipid content. On a lipid basis, total CDD/CDFs are higher in blood than adipose tissue. Partitioning is not identical in these tissues 2,3,7,8-TCDD levels are almost identical in blood and adipose tissues, but OCDD levels are higher in blood. However, the presence of OCDD at levels of 5,000-10,000 pg/person when concentrations in food are generally in the low pg/g level suggests that the contribution of food to the OCDD body burden in humans requires further study (Rappe 1993). 

Octanol is a partitioning medium just as water is a partitioning media. While there is nothing inherently special about octanol with respect to other organic liquids, the extent that an organic chemical partitions to octanol from water has become a standard for evaluating hydrophobicity (i.e., chemicals that partition more to octanol from water are more hydrophobic). Since HOPs that are more hydrophobic accumulate more in body tissues, partition more strongly to soils and sediments, and are typically more easily removed by adsorption from water, the extent that HOPs partition to octanol from water is a very important environmental indicator. 

A method for identifying chlorinated insecticide residues in fish tissue is described. Whereas electron capture gas chromatography guides the isolation procedures and provides tentative identification and quantitative estimation, positive identification is made on the basis of the infrared spectrum of isolated insectiQides. The procedure consists of hexane extraction of fish tissue, partition between hexane and acetonitrile, column adsorption and thin layer chromatography cleanup, and micro-infrared analysis in a potassium bromide disc. The practical limit of sensitivity needed to provide excellent infrared spectra of a number of the more common chlorinated insecticides is about 1 p.p.m. in the fish tissue concentrations as low as 0.25 p.p.m. have given informative infrared spectra. 

METHODOLOGIES TO PREDICT BLOOD AND TISSUE PARTITION COEFFICIENTS... 

Parameter Values Aside from the dependent and independent variables in the equations above, a variety of parameters must be specified. These include physiological parameters (e.g., ventilation rates, cardiac output, organ volumes and masses), physicochemical parameters (e.g., tissue partition coefficients, protein binding constants), and biochemical parameters (e.g., Km and Vmax). 

Different approaches have been published regarding the prediction of partition coefficients on the basis of physicochemical parameters of compounds [26-29], These authors described algorithms for the estimation of blood-air and tissue-blood partition coefficients. The most important descriptor for blood-tissue partitioning appears to be lipophilicity and can be described as a function of blood and tissue composition with regard to the lipid and water fractions. Charged molecules do not easily pass membranes passively however, weak bases appear to interact with the charges present at the hydrophilic moieties of phospholipids and can be transferred over the membranes in this way [28]. 

Once the structure of the PBPK model is formulated, the next step is specifying the model parameters. These can be classified into a chemical-independent set of parameters (such as physiological characteristics, tissue volumes, and blood flow rates) and a chemical-specific set (such as blood/tissue partition coefficients, and metabolic biotransformation parameters). Values for the chemical-independent parameters are usually obtained from the scientific literature and databases of physiological parameters. Specification of chemical-specific parameter values is generally more challenging. Values for one or more chemical-specific parameters may also be available in the literature and databases of biochemical and metabolic data. Values for parameters that are not expected to have substantial interspecies differences (e.g., tissue/blood partition coefficients) can be imputed based on parameter values in animals. Parameter values can also be estimated by conducting in vitro experiments with human tissue. Partitioning of a chemical between tissues can be obtained by vial equilibration or equilibrium dialysis studies, and metabolic parameters can be estimated from in vitro metabolic systems such as microsomal and isolated hepatocyte syterns. Parameters not available from the aforementioned sources can be estimated directly from in vivo data, as discussed in Section 43.4.5. 

Dixon et al. (2001) described a preliminary PB-PK model to predict JP-8 concentrations in Air Force fuel-cell maintenance workers. The model used data from PB-PK models of naphthalene inhalation in mice and rats and nonane inhalation in rats. In addition to inhalation, a pathway of dermal exposure and a skin compartment were included. For highly exposed people, the PB-PK model was generally in agreement with exhaled-air naphthalene concentrations however, predictions for the low-exposure scenarios were grossly underestimated, especially in female workers, by a factor of 10. The model did not predict blood and urinary concentrations. The major limitation of the Dixon et al. (2001) study was the lack of appropriate human data (e.g., metabolic measures, blood and tissue partition coefficients, and diffusion rates). The Dixon et al. (2001) model predicted a rapid decline in naphthalene concentrations in all compartments after exposure except liver, fat, and brain. The model predicted accumulation in liver, brain, and fat tissues for a 7-day period that included 4-hr exposures on 5 days. Competition for enzyme does not occur only from interactions of different inhaled compounds. Interactions can also occur between inhaled compounds and metabolites formed in the body that require similar enzymes for biotransformation. Detailed kinetic studies with both benzene and -hexane show inhibition of later metabolic steps, phenol to hydroquinone or methyl -butyl ketone to 2,5-hexane dione, by high concentrations of inhaled benzene or hexane, respectively (Medinsky et al. 1989 Andersen and Clewell 1984). 

Assay in body fluids and tissue (i) Sulphadimidine in bovine kidney, liver, muscle and fat tissue. Partition Bondapak C18 /Porasil B 2.5% isopropyl alcohol in phosphate buffer (pH 7.7)... 

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