Human permeability coefficients, hairless mouse

Table A1 lists and Figure 15.1 shows 144 permeability coefficient values for 83 eompounds (83 fully validated and 61 excluded data points 45 fully validated compounds) measured in hairless mouse skin. All of the measurements excluded from this database were more than 90% ionized. Etorphine is distinguished on this figure because Vecchia and Bunge (2002b) used the fact that the human permeability coefficient is larger than the hairless mouse permeability coefficient to support exclusion of the measurement from the fully validated database for human skin. Notice that the hairless mouse permeability coefficient of etorphine is consistent with measurements for other cations, which was not the case with the human permeability coefficient for etorphine (Vecchia and Bimge, 2002b).

There are fewer extremely low (i.e., logP < -4.0) permeability coefficient values in hairless mouse skin than in human skin. 

Figure 15.7 shows the permeability coefficient regression equations for skin from human (EquationT15.1-l), hairless mouse (EquationT15.1-2), hairless rat (Equation T15.1-3), rat (Equation T15.1-6), and shed snake (Equation T15.1-7) plotted as a function of log for relatively small molecules MW = 100) and larger molecules MW = 300). The regression equations for human, hairless mouse, and shed snake skin are most relevant because these databases are the largest and most diverse. Permeability coefficients in all species increase linearly with log... 

As illnstrated in Fignre 15.7, differences between species in the dependence of permeability coefficients can cause the relative order of penetration rates to change with For example, for a chemical with MW = 100 and log = 4, the predicted order for the permeability coefficients is snake > hairless mouse > human for a chemical with MW = 100 and log = -2.0, the predicted order is hairless mouse > human > snake. However, when MW = 300, the relative order among these three species is predicted to be independent of log These plots show clearly that relative rankings of permeability coefficients in different species may depend on chemical properties of the penetrant. 

Figure 15.7 Permeability coefficient regressions for human, hairless mouse (HLMouse), hairless rat (HLRat), rat, and shed snake skin plotted as a function of log K at (a) MW = 100 and (b) MW = 300 human (solid), satisfactory correlation (long dashes), limited correlation (short dashes).

Figure 15.9 Ratios of average permeability coefficients for 31 compounds common to the validated hairless mouse and human databases compared to the average ratio of 3.1 (solid horizontal line) and to the difference behveen the regressions developed from the hairless mouse database and the fully validated human databases (a) plotted as a function of log K tor MW= 100 (short dashes) and MW = 300 (long dashes) (b) plotted as a function of MW for log K =2 (short dashes) and log = 4 (long dashes).

Dermal absorption in different animal species has many qualitative similarities to dermal absorption in humans that can be observed through examination of permeability coefficients. However, for the purpose of estimating dermal absorption in humans, the large numbers of permeability coefficient values determined in animal skins are of limited use until quantitative relationships to human skin are established. Based on the data collected so far, we have developed regression equations of permeability coefficients as functions of log and MW for several animal species (hairless mouse, hairless rat, rat, and snake). The regression equation from hairless mouse skin is similar to an equation of the same form for human skin. On average, hairless mouse skin is 3.1 times more permeable than human skin this ratio appears to be independent of but may increase weakly for higher MW compounds. 

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