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Temperature dependence of skin permeability to hydrophilic and hydrophobic solutes
NOTES Temperature Dependence of Skin Permeability to Hydrophilic and Hydrophobic Solutes SAMIR MITRAGOTRI Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, California 93106
Received 28 February 2006; revised 10 May 2006; accepted 6 September 2006 Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/jps.20793
ABSTRACT: A number of studies have reported on the activation energies of skin permeability. In this article, I summarize the literature data on activation energies and analyze their dependence on solute molecular properties, namely radius and lipophilicity. Theoretical equations are also presented to facilitate interpretation of the dependence of activation energy on molecular properties of the solute. ß 2006 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 96:1832–1839, 2007
Keywords:
skin; transdermal; activation; temperature; hydrophilic; hydrophobic
INTRODUCTION Dependence of stratum corneum (SC) permeability on temperature has been experimentally measured for several solutes and the activation energies of SC permeabilization have been calculated.1–4 Activation energies reflect the nature of the transport barrier of the SC and hence have received significant attention in the past. This topic was first discussed in the pioneering studies of Scheuplein and Blank2 and Roberts et al.1 Using aliphatic and aromatic hydroxyl compounds, they showed that the activation energies of hydrophobic solutes are smaller than those of hydrophilic solutes. Several additional values of activation energies have since been reported. In this study, I summarize the literature values of activation energies and present my interpretation of their dependence on solute molecular properties. Theoretical equations are also preCorrespondence to: Samir Mitragotri (Telephone: 805-8937532; Fax: 805-893-4731; E-mail: [email protected]) Journal of Pharmaceutical Sciences, Vol. 96, 1832–1839 (2007) ß 2006 Wiley-Liss, Inc. and the American Pharmacists Association
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sented to describe the activation energies of SC permeability.
THEORY Hydrophobic Solutes Hydrophobic solutes diffuse largely through the intercellular lipid bilayers in the SC.5 Skin permeability to hydrophobic solutes has been previously described using the following equation.6 KP ¼
0:7 Ko=w Do expðAr2 Þ
L
ð1Þ
where, Do is the solute diffusion coefficient in a model isotropic solvent, r is the van der Waal’s ˚ , A is a constant whose value is solute radius in A related to the structure of lipid chains in the SC,7 * is the tortuosity of the intercellular lipids and L is the SC thickness. Note that SC lipids are highly anisotropic and hence diffusion and partition coefficients in SC lipids exhibit stronger size dependence than Do and Ko/w. The size dependence of solute diffusion and partition
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coefficients in SC lipids is captured in A. Equations that separately describe solute partition and diffusion coefficients in SC lipids are described in Ref. 8. The effect of temperature on KP can be described by differentiating Eq. (1) as follows: @ðln KP Þ @A ¼ r2 @ð1=TÞ @ð1=TÞ ð2Þ @ðln Ko=w Þ @ðln Do Þ þ þ 0:7 @ð1=TÞ @ð1=TÞ While deriving Eq. (2), it is implicitly assumed that KP is a continuous function of T, an assumption that is valid away from the phase transition temperature of the SC lipids. The most prominent phase transition in the SC lipids takes place at a temperature around 60–658C.9 Accordingly, Eq. (2) is valid at temperatures below 608C. It is also assumed that SC thickness, L and tortuosity t* are not influenced by temperature. The left hand side of Eq. (2) is the activation energy of skin permeability, E/R where, E is the activation energy and R is the universal gas constant. Hence, Eq. (2) can be rewritten as follows: ED o
EK o=w
E @A ¼ r2 þ þ 0:7 R @ð1=TÞ R R
ð3Þ
where ED o is the activation energy of solute diffusion in an isotropic solvent and EK o=w is the activation energy of solute octanol–water partition coefficient. Activation energies of partition coefficients in organic solvents have typically been found to be small and hence are neglected in the model. The first term on the right hand side in Eq. (3) originates from thermal expansion of lipid bilayers. Equation 3 leads to a prediction that the activation energy of hydrophobic solutes increases with r2.
Highly Hydrophilic Solutes
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the transport across the lipid bilayers. However, studies performed with single lipid bilayers have shown that highly hydrophilic solutes such as mannitol show extremely low transport across intact lipid bilayers. If all lipid bilayers in the SC were intact and if mannitol were required to diffuse across all of them, it would have negligible skin permeability. How is it then that these solutes cross the SC? It has been proposed that permeation of highly hydrophilic solutes can be modeled using a porous pathway model.3,11,12 This model assumes that solute permeation can be modeled as transport through a porous membrane. The advantage of this model is that it offers equations for describing solute transport without requiring detailed information about skin structure. The limitation of the model is that it is not based on the physical structure of the SC. Hence, physical interpretation of model parameters is difficult. The general expression for the permeability coefficient, KP, of a hydrophilic permeant diffusing through a porous membrane is given by:13 KP ¼
eD1 p HðlÞ L
ð4Þ
where e, , and L are the porosity, tortuosity, and thickness of the SC, respectively. D1 p is the solute diffusion coefficient under infinite dilution conditions and H(l) is the hindrance factor where l is the ratio of the hydrodynamic radius of the permeant, rh, and the effective pore radius of the membrane, rp (i.e., l ¼ rh/rp). H(l) has been related to l by the following equation for small solutes HðlÞ ¼ ð1 lÞ2 ð1 2:1l þ 2:09l3 0:95l5 Þ.13 Eq. (4) can be differentiated to obtain the following: @ðln D1 @ðln KP Þ @ lnðe=Þ p Þ ¼ þ @ð1=TÞ @ð1=TÞ @ð1=TÞ ð5Þ @ ln HðlÞ þ @ð1=TÞ The left hand side of Eq. (5) is equal to E/R. To simplify Eq. (5), we assume that an increase in skin temperature does not increase skin’s porosity or tortuosity. This approximation implicitly states that elevation of temperature does not induce new transport pathways in the skin. Equation 5 then reduces to the following.
Permeation routes of highly hydrophilic solutes (Ko/w < 0.1) are not completely understood. Studies have shown that some small hydrophilic solutes, specifically water, can easily diffuse in the corneocytes and are likely to permeate the skin via the transcellular route; but the rate limiting step is still permeation across the lipids.10 Transport pathways of larger hydrophilic solutes, for example, mannitol are more complex. It is likely that they can diffuse in the corneocytes rapidly and hence the rate-limiting step is again
where, ED w is the activation energy of solute diffusion in water. Estimation of E requires
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E ¼ ED wR
@ ln HðlÞ @ð1=TÞ
ð6Þ
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knowledge of thermal expansion coefficient of pores, that is, @l=@ð1=TÞ. However, since no specific structure can be assigned to the pores, determination of @l=@ð1=TÞfrom the first principles is difficult. Typical pore radii in the skin ˚ ,11 a number have been found to be 20–30 A significantly larger than the solute radii considered in this study (Tab. 1). Hence, reduction in hindrance due to pore expansion will be small even if the pores were to expand substantially. For the sake of calculations, let us assume that the pore radius doubles for every 108C increase in skin temperature. For this case, the average magnitude of the final term in Eq. (6) for a typical ˚ ) is less than 2 kJ/mole, a small solute (r ¼ 4 A number very small compared to the experimentally measured activation energies (see Tab. 1). Accordingly, it can be assumed that the contribution of the final term in Eq. (6) can be neglected and the activation energy of hydrophilic solutes can be approximated by the following equation. E ED W
ð7Þ
Typical values of ED W for small hydrophilic solutes, for example, water are on the order of 20 kJ/mole.
RESULTS The model makes two predictions: (i) the activation energy for hydrophobic solutes is greater than that for hydrophilic solutes and (ii) the activation energy for hydrophobic solutes increases with increasing solute size. These predictions were tested against available experimental data compiled from the literature (Tab. 1). Solute classification into hydrophilic and hydrophobic was done based on their Ko/w. In the most simplistic way, hydrophobic solutes can be defined as those with Ko/w > 1. Based on this classification, data in Table 1 showed that the difference between activation energies of hydrophilic and hydrophobic solutes is not significant (p ¼ 0.13, t-test). However, this definition of hydrophobicity is arbitrary since it is not clear that the permeation route changes from intercellular lipids to porous pathway at Ko/w ¼ 1. To probe this matter in detail, we redefined solute hydrophobicity as follows; hydrophilic (Ko/w < 0.1), intermediate (0.1 < Ko/w < 10), hydrophobic (10 < Ko/w < 1000), and highly hydrophobic (Ko/w > 1000). This classification brought out the differences in a better JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 96, NO. 7, JULY 2007
way. Specifically, this analysis showed that activation energies of hydrophilic solutes are smaller than intermediate, hydrophobic, and highly hydrophobic solutes (see Tab. 2 for a summary of p values for pairwise comparisons between all groups). The analysis also showed that the activation energies of highly hydrophobic solutes are higher than any other group. The comparison between intermediate and hydrophobic solutes, however, did not agree with the model. Specifically, the activation energies of hydrophobic solutes are smaller than intermediate solutes, a conclusion inconsistent with the model but consistent with that made by Roberts et al. Note that the model presented here does not suggest that the activation energy is a continuous function of Ko/w. Hence, assumption of a continuous trend is discouraged. The only prediction made by the model is that the activation energies of hydrophobic solutes in general are greater than those of hydrophilic solutes. This conclusion is supported by the statistical analysis in Table 2 except in one case (intermediate vs. hydrophobic). The model also predicts that the activation energy of hydrophobic solutes increases with solute radius (Eq. 3). Dependence of activation energy on solute radius was evaluated separately for hydrophilic, intermediate, hydrophobic, and highly hydrophobic solutes (Fig. 1). The trends were in agreement with the model for extreme cases (hydrophilic and highly hydrophobic). Specifically, no correlation between activation energy and solute size was found for hydrophilic solutes as expected (r ¼ 0.2) and a good correlation was found between the same for highly hydrophobic solutes (r ¼ 0.8). The trends were not significant for the remaining two categories (intermediate and hydrophobic, r ¼ 0.5 and 0.4, respectively).
DISCUSSION Activation energy of transdermal permeation has received significant attention, especially in light of its relevance to elucidating the permeation pathways. Early foundation was provided by the data of Roberts et al.1 and Scheuplein and Blank2 who suggested that activation energy is lower for relatively hydrophobic solutes. These conclusions were reached based on the permeability data for aliphatic alcohols and phenolic compounds. However, Peck et al.3 showed that the activation energies of highly hydrophilic compounds such as DOI 10.1002/jps
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TEMPERATURE DEPENDENCE OF SKIN PERMEABILITY
Table 1. Literature Data on Activation Energies of Skin Permeability to Various Solutes
No.
Solute
1 2 3 4
Acetylsalicylic acid AZT Betahistine Butanol (n-butanol)
MW Da
Log Ko/w
180 267 300 74
1.19 0.05 0.68 0.88
5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
Butanone (2-butanone) Butyl paraben p-Bromophenol Caffeine Carbon disulfide Chlorocresol o-Chlorophenol Corticosterone m-Cresol o-Cresol p-Cresol 1,1-Dichloropropanone Ethyl ether Estradiol Ethanol
72 194 173 194 76 143 128 346 108 108 108 126 74 272 46
0.29 3.57 2.59 0.02 1.94 3.1 2.15 1.94 1.96 1.95 1.95 1.18 0.89 3.86 0.31
20 21
Ethoxy ethanol 5-Fluorouracil
90 200
0.28 0.89
22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46
Glycopyrrolate Heptanol (n-heptanol) Hexanol (n-hexanol) Ibuprofen Imipramine hydrochloride Indomethacin Ion conductivity Ketoprofen Mannitol Methanol Methyl paraben Methylsalicylic acid b-Naphthol m-Nitrophenol Octanol (n-octanol) Oxygen Pentanol Phenol Propanol Propionic acid Resorcinol Sarin Tetraethylammonium ion Thiourea Thymol
398 116 102 206 280 360 23 254 180 32 152 152 144 139 130 32 88 94 60 74 110 140 134 76 150
1.2 2.34 2.03 3.5 2.5 4.27 — 3.12 3.1 0.71 1.96 2.55 2.84 2 3.15 0.65 1.34 1.46 0.3 0.33 0.8 0.3 — 1.05 3.34
Activation Energy kJ/mole 85 85 98 71 69.9 67.2 85 36.8 53 70.9 43.1 40.2 97 56.9 53.6 57.4 47 67.2 115 82 68.7 84 98 86 73.9 41.4 98 45.6 173 88 146 186 17 120a 36.7 77 65 57.4 41 55.7 71 42 44 69.1 60.3 69.1 47 74.5 70.9 34.8 67.7 52.8
Classification Hydrophobic Intermediate Intermediate Intermediate Intermediate Intermediate Highly hydrophobic Hydrophobic Intermediate Hydrophobic Highly hydrophobic Hydrophobic Hydrophobic Hydrophobic Hydrophobic Hydrophobic Hydrophobic Intermediate Highly hydrophobic Intermediate Intermediate Intermediate Intermediate Intermediate Hydrophilic Hydrophobic Hydrophobic Hydrophobic Hydrophobic Hydrophobic Highly hydrophobic Highly hydrophobic Hydrophilic Highly hydrophobic Hydrophilic Intermediate Hydrophobic Hydrophobic Hydrophobic Hydrophobic Highly hydrophobic Hydrophobic Intermediate Hydrophobic Hydrophobic Intermediate Intermediate Intermediate Intermediate Hydrophilic Hydrophilic Highly hydrophobic
References 2 17 18 4 1 2 19 1 19 2 1 1 3 1 1 1 20 2 18 4 1 2 21 22 2 1 4 1 23 24 18 23 25 26 3 4 19 2 1 1 4 2 27 1 1 1 28 1 2 3 2 1
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Table 1. (Continued)
No.
Solute
47 48 49 50
2,4,6-Trichlorophenol 1,1,1-Trichloropropanone Urea Water
MW Da
Log Ko/w
Activation Energy kJ/mole
197 160 60 18 18 18
3.69 1.75 2.11 1.38 1.38 1.38
38.1 51 29.6 57 71 61
Classification
References 1
Highly hydrophobic Hydrophobic Hydrophilic Hydrophilic Hydrophilic Hydrophilic
20 3 29 30 2
These data correspond to experiments performed on a variety of experimental model systems. Data from all experimental systems are collected and analyzed together. a Recalculated from published data; partition coefficients obtained from Log Ko/w databank or determined using ChemSW software.
sugars and urea are much lower than those for hydrophobic solutes. Theoretical analyses of activation energies have also been performed to gain insights into this issue. Models describing skin permeation based on free volume type of approaches have been developed; and these models implicitly account for the temperature dependence of skin permeability.14–16 Kasting et al.14 compared a free volume type equation for skin permeability (P exp[aV] where a represents free volume in SC lipid bilayers and V is solute volume) and the Arrhenius equation (P exp[E/RT], where E is the activation energy) and estimated the activation energies of skin permeability. Their analysis led to the conclusion that activation energies estimated this way are five- to tenfold lower than experimentally observed values.14 However, this analysis was based on transdermal fluxes and not permeabilities. Nevertheless, analysis of Kasting et al. makes a direct case for the existence of sizedependent activation energies based on a qualitative comparison of the exponents. The equations presented here allow a detailed analysis of activation energies across a wide range of solute properties. The prediction of the model
that hydrophobic solutes have higher activation energies than hydrophilic solutes is supported by the data with once exception (Tab. 2). The high activation energies of hydrophobic solutes are a direct consequence of a strong dependence of their permeability on molecular size. Volumes of hydrophobic solutes in Table 1 are comparable to the mean free volumes in lipid bilayers.8 Hence, thermal expansion of lipid bilayers, which increases the free volume, makes significant contributions to activation energies. The prediction that activation energy of hydrophobic solutes increases with solute size is in agreement with data for highly hydrophobic solutes (Fig. 1d) but not for relatively less hydrophobic solutes (Fig. 1c). The reason behind this is not clear. A closer look at Eq. (3) reveals that it does not show a classical Arrhenius behavior. The first term on the right hand side is temperature-dependent, thereby making E temperature-dependent. The extent of departure from the Arrhenius behavior is determined by the temperature dependence of A. A formal expression for A has been derived in Ref.8. A depends primarily on the free area in the SC lipid bilayers, af, and order parameters of lipid chains. A first order approximation of A (see Eq. 16 in Ref.8)
Table 2. Summary of p Values (Sudent’s t-Test) for Comparison of Activation Energies between Different Groups of Solutes (Hydrophilic, Intermediate, Hydrophobic, and Highly Hydrophobic)
Solute Classes Based on Ko/w Hydrophilic Ko/w < 0.1 Intermediate 0.1 < Ko/w < 10 Hydrophobic 10 < Ko/w < 1000 Highly hydrophobic Ko/w > 1000
Hydrophilic Ko/w < 0.1
Intermediate 0.1 < Ko/w < 10
Hydrophobic 10 < Ko/w < 1000
Highly Hydrophobic Ko/w > 1000
NA 0.001 0.08 0.011
NA 0.017a 0.038
NA 0.0047
NA
The matrix is symmetric and values only on one side of the diagonal are reported. a Activation energies of hydrophobic solutes are smaller than those for intermediate solutes. All other p values confirm the hypothesis suggested by the model, that is, activation energy increases with increasing hydrophobicity. JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 96, NO. 7, JULY 2007
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Figure 1. Dependence of activation energy on solute radius, assessed separately for (a) hydrophilic (Ko/w < 0.1), (b) intermediate (0.1 < Ko/w < 10), (c) hydrophobic (1000 > Ko/w > 10), and (d) highly hydrophobic (Ko/w > 1000) solutes. The data are taken from Table 1. The regression coefficients for linear fits are (a) 0.2, (b) 0.5, (c) 0.4, and (d) 0.8.
shows that A 1/af. af, in turn, increases proportionately with temperature away from the phase transition temperature. Hence, the term @A/@(1/T) is independent of temperature to a first approximation. Accurate estimation of @A/@(1/T) for SC lipid bilayers cannot be performed since af for SC lipid bilayers and its dependence on temperature are not known. However, these parameters are known for dipalmitoyl phosphatidylcholine bilayers (DPPC) and calculations based on experimentally measured thermal expansion coefficients
of DPPC bilayers lead to @A/@(1/T) between 300 ˚ 2. This implies that the contribution of and 500 K/A the size-dependent term to the activation energy ˚ (the for a solute with radius between 4 and 5 A largest hydrophobic solute in this study) is between 50 and 80 kJ/mole, which is 25–45% of the total activation energy for that solute. The prediction of the model that activation energies of hydrophilic solutes are insensitive to solute size (Eq. 7) is supported by experimental data (Fig. 1a). Mechanistic origins of this
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MITRAGOTRI
dependence can be found in the equations of the porous pathway model. This model assumes that highly hydrophilic solutes diffuse through permeable pores distributed in an impermeable matrix. No precise structure can be associated with these pores, although structural defects in the skin have been thought to constitute the porous pathway.6 Although precise interpretation of the porous pathway model is debatable, the most important parameter for this study is the pore radius. The pore radii necessary to explain the permeation of hydrophilic solutes in Table 1 are in the range of ˚ ,11 a number significantly greater than the 20–30 A radii of solutes reported in Table 1. Thus, thermal expansion of pores, if any, does not contribute significantly to the enhanced permeability at higher temperatures. This leads to lower activation energies. This study provides a theoretical platform to analyze the activation energies of skin permeability to hydrophilic and hydrophobic solutes. The study also provides a compilation of the literature data on this topic. While interpreting the model and its conclusions, the underlying assumptions must be kept in mind. Specifically, the model assumes that SC is always the rate-limiting step in skin permeation. It is possible, especially if the SC is highly permeable, that the unstirred boundary layer or the epidermis may become an important contributor to permeation resistance.1 Robert et al. showed that such shifts in rate limiting steps can induce solute-dependent changes in activation energy. Similar situation will also arise should epidermis or appendages contribute significantly to permeation resistance. Such situation-dependent and solute-dependent changes in activation energy should be analyzed in future studies. The model also assumes that solute partition coefficient does not depend on temperature and that the permeation pathways do not change as a function of temperature. Several questions remain that require more analysis and experimentation. For example, data of Roberts et al. and Scheuplein and Blank show an inverse dependence of activation energies on lipophilicity. This trend can be seen in the data presented here as well. Specifically, Table 2 shows that activation energy of hydrophobic solutes is smaller than intermediate solutes (p ¼ 0.017), an observation that contradicts the model. It is not immediately clear why the model predictions are not in agreement with experimental data for these two categories. It is possible that some of the assumptions behind the model or the basic premise of the model are not applicable for
such solutes for reasons that are not apparent. Future research should focus on this aspect. Another consideration that needs further investigation is that the data presented here has been collected on human as well as animal skin. Further experiments are necessary to identify any speciesspecific trends. Additional studies searching for alternate interpretations of the data should also be pursued. It is also clear from Table 1 that relatively fewer data points are available on highly hydrophilic solutes and additional measurements will further facilitate the analysis presented in this study.
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REFERENCES 1. Roberts MS, Anderson RA, Swarbrick J, Moore DE. 1978. The percutaneous absorption of phenolic compounds: The mechanism of diffusion across the stratum corneum. J Pharm Pharmacol 30: 486–490. 2. Scheuplein RJ, Blank IH. 1971. Permeability of the skin. Physiol Rev 51:702–747. 3. Peck KD, Ghanem AH, Higuchi WI. 1995. The effect of temperature upon the permeation of polar and ionic solutes through human epidermal membrane. J Pharm Sci 84:975–982. 4. Durrheim H, Flynn GL, Higuchi WI, Behl CR. 1980. Permeation of Hairless Mouse Skin I: Experimental Methods and Comparison with Human Epidermal Permeation by Alkanols. J Pharm Sci 69:781–786. 5. Johnson ME, Blankschtein D, Lange R. 1997. Evaluation of solute permeation through the stratum corneum; lateral diffusion as the primary transport mechanism. J Pharm Sci 86(10):1162– 1172. 6. Mitragotri S. 2003. Modeling skin permeability to hydrophilic and hydrophobic solutes based on four permeation pathways. J Control Rel 86:69–92. 7. Mitragotri A. 2002. Theoretical Analysis of Permeation of Small Hydrophobic Solutes across the Stratum Corneum based on Scaled Particle Theory. J Pharm Sci 91:744–752. 8. Mitragotri S. 2002. A theoretical analysis of permeation of small hydrophobic solutes across the stratum corneum based on Scaled Particle Theory. J Pharm Sci 91:744–752. 9. Hatfield RM, Fung LW. 1995. Molecular Properties of a Stratum Cornuem Model Lipid System: Large Unilamellar Vesicles. Biophys J 68:196–207. 10. Kasting GB, Barai ND, Wang TF, Nitsche JM. 2003. Mobility of water in human stratum corneum. J Pharm Sci 92:2326–2340. 11. Tang H, Mitragotri S, Blankschtein D, Langer R. 2001. Theoretical description of transdermal
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transport of hydrophilic permeants: Application to low-frequency sonophoresis. J Pharm Sci 90:545– 568. Tezel A, Sens A, Mitragotri S. 2003. Description of transdermal transport of hydrophilic solutes during low-frequency sonophoresis based on a modified porous pathway model. J Pharm Sci 92:381–393. Deen W. 1987. Hindered transport of large molecules in liquid-filled pores. AIChE J 33:1409–1425. Kasting GB, Smith RL, Cooper ER. 1987. Effect of lipid solubility and molecular size on percutaneous absorption. Pharmacol Skin 1:138–153. Potts RO, Guy RH. 1995. A predictive algorithm for skin permeability: The effects of molecular size and hydrogen bond activity. Pharm Res 12:1628–1633. Potts RO, Guy RH. 1992. Predicting skin permeability. Pharm Res 9:663–669. Narishetty ST, Panchagnula R. 2004. Transdermal delivery of zidovudine: Effect of terpenes and their mechanism of action. J Control Rel 95:367–379. Ogiso T, Ogiso H, Paku T, Iwaki M. 1996. Phase Transitions of Rat Stratum Corneum Lipids by an Electron Paramagnetic Resonance Study and Relationship of Phase States to Drug Penetration. Biochim Biophys Acta 1301:97–104. Akomeah F, Nazir T, Martin GP, Brown MB. 2004. Effect of heat on the percutaneous absorption and skin retention of three model penetrants. Eur J Pharm Sci 21:337–345. Xu X, Weisel CP. 2005. Dermal uptake of chloroform and haloketones during bathing. J Expo Anal Environ Epidemiol 15:289–296. Meidan VM, Walmsley AD, Docker MF, Irwin WJ. 1999. Ultrasound-enhanced diffusion into coupling
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gel during phonophoresis of 5-fluorouracil. Int J Pharm 185:205–213. Cornwell PA, Barry BW. 1994. Sesquiterpene components of volatile oils as skin penetration enhancers for the hydrophilic permeant 5-fluorouracil. J Pharm Pharmacol 46:261–269. Ito Y, Ogiso T, Iwaki M. 1988. Thermodynamic Study on Enhancement of Percutaneous Penetration of Drugs by Azone. J Pharmacobio-Dyn 11: 749–757. Jain AK, Panchagnula R. 2003. Effect of temperature on imipramine hydrochloride permeation: Role of lipid bilayer arrangement and chemical composition of rat skin. Int J Pharm 250:287–293. Cornwell PA, Barry BW. 1993. The routes of penetration of ions and -fluorouracil across human skin and the mechanisms of action of terpene skin penetration enhancers. Int J Pharm 94:189–194. Ohara N, Takayama K, Machida Y, Nagai T. 1994. Combined effect of d-limonene and temperature on the skin permeation of ketoprofen. Int J Pharm 105:31–38. Hatcher ME, Plachy WZ. 1993. Dioxygen diffusion in the stratum corneum; an EPR SPin Label Study. Biochim Biophys Acta 1149:73–78. Liron Z, Cohen S. 1984. Percutaneous absorption of alkanoic acids I: A study of operational conditions. J Pharm Sci 73:534–537. Potts R, Francoeur ML. 1990. Lipid biophysics of water loss through the skin. Proc Natl Acad Sci 87:3871–3873. Golden G, et al. 1987. Stratum cornuem lipid phase transisitions and Water Barrier Properties. Biochemistry 26:2382–2388.
JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 96, NO. 7, JULY 2007
Received 28 February 2006; revised 10 May 2006; accepted 6 September 2006 Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/jps.20793
ABSTRACT: A number of studies have reported on the activation energies of skin permeability. In this article, I summarize the literature data on activation energies and analyze their dependence on solute molecular properties, namely radius and lipophilicity. Theoretical equations are also presented to facilitate interpretation of the dependence of activation energy on molecular properties of the solute. ß 2006 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 96:1832–1839, 2007
Keywords:
skin; transdermal; activation; temperature; hydrophilic; hydrophobic
INTRODUCTION Dependence of stratum corneum (SC) permeability on temperature has been experimentally measured for several solutes and the activation energies of SC permeabilization have been calculated.1–4 Activation energies reflect the nature of the transport barrier of the SC and hence have received significant attention in the past. This topic was first discussed in the pioneering studies of Scheuplein and Blank2 and Roberts et al.1 Using aliphatic and aromatic hydroxyl compounds, they showed that the activation energies of hydrophobic solutes are smaller than those of hydrophilic solutes. Several additional values of activation energies have since been reported. In this study, I summarize the literature values of activation energies and present my interpretation of their dependence on solute molecular properties. Theoretical equations are also preCorrespondence to: Samir Mitragotri (Telephone: 805-8937532; Fax: 805-893-4731; E-mail: [email protected]) Journal of Pharmaceutical Sciences, Vol. 96, 1832–1839 (2007) ß 2006 Wiley-Liss, Inc. and the American Pharmacists Association
1832
sented to describe the activation energies of SC permeability.
THEORY Hydrophobic Solutes Hydrophobic solutes diffuse largely through the intercellular lipid bilayers in the SC.5 Skin permeability to hydrophobic solutes has been previously described using the following equation.6 KP ¼
0:7 Ko=w Do expðAr2 Þ
L
ð1Þ
where, Do is the solute diffusion coefficient in a model isotropic solvent, r is the van der Waal’s ˚ , A is a constant whose value is solute radius in A related to the structure of lipid chains in the SC,7 * is the tortuosity of the intercellular lipids and L is the SC thickness. Note that SC lipids are highly anisotropic and hence diffusion and partition coefficients in SC lipids exhibit stronger size dependence than Do and Ko/w. The size dependence of solute diffusion and partition
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coefficients in SC lipids is captured in A. Equations that separately describe solute partition and diffusion coefficients in SC lipids are described in Ref. 8. The effect of temperature on KP can be described by differentiating Eq. (1) as follows: @ðln KP Þ @A ¼ r2 @ð1=TÞ @ð1=TÞ ð2Þ @ðln Ko=w Þ @ðln Do Þ þ þ 0:7 @ð1=TÞ @ð1=TÞ While deriving Eq. (2), it is implicitly assumed that KP is a continuous function of T, an assumption that is valid away from the phase transition temperature of the SC lipids. The most prominent phase transition in the SC lipids takes place at a temperature around 60–658C.9 Accordingly, Eq. (2) is valid at temperatures below 608C. It is also assumed that SC thickness, L and tortuosity t* are not influenced by temperature. The left hand side of Eq. (2) is the activation energy of skin permeability, E/R where, E is the activation energy and R is the universal gas constant. Hence, Eq. (2) can be rewritten as follows: ED o
EK o=w
E @A ¼ r2 þ þ 0:7 R @ð1=TÞ R R
ð3Þ
where ED o is the activation energy of solute diffusion in an isotropic solvent and EK o=w is the activation energy of solute octanol–water partition coefficient. Activation energies of partition coefficients in organic solvents have typically been found to be small and hence are neglected in the model. The first term on the right hand side in Eq. (3) originates from thermal expansion of lipid bilayers. Equation 3 leads to a prediction that the activation energy of hydrophobic solutes increases with r2.
Highly Hydrophilic Solutes
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the transport across the lipid bilayers. However, studies performed with single lipid bilayers have shown that highly hydrophilic solutes such as mannitol show extremely low transport across intact lipid bilayers. If all lipid bilayers in the SC were intact and if mannitol were required to diffuse across all of them, it would have negligible skin permeability. How is it then that these solutes cross the SC? It has been proposed that permeation of highly hydrophilic solutes can be modeled using a porous pathway model.3,11,12 This model assumes that solute permeation can be modeled as transport through a porous membrane. The advantage of this model is that it offers equations for describing solute transport without requiring detailed information about skin structure. The limitation of the model is that it is not based on the physical structure of the SC. Hence, physical interpretation of model parameters is difficult. The general expression for the permeability coefficient, KP, of a hydrophilic permeant diffusing through a porous membrane is given by:13 KP ¼
eD1 p HðlÞ L
ð4Þ
where e, , and L are the porosity, tortuosity, and thickness of the SC, respectively. D1 p is the solute diffusion coefficient under infinite dilution conditions and H(l) is the hindrance factor where l is the ratio of the hydrodynamic radius of the permeant, rh, and the effective pore radius of the membrane, rp (i.e., l ¼ rh/rp). H(l) has been related to l by the following equation for small solutes HðlÞ ¼ ð1 lÞ2 ð1 2:1l þ 2:09l3 0:95l5 Þ.13 Eq. (4) can be differentiated to obtain the following: @ðln D1 @ðln KP Þ @ lnðe=Þ p Þ ¼ þ @ð1=TÞ @ð1=TÞ @ð1=TÞ ð5Þ @ ln HðlÞ þ @ð1=TÞ The left hand side of Eq. (5) is equal to E/R. To simplify Eq. (5), we assume that an increase in skin temperature does not increase skin’s porosity or tortuosity. This approximation implicitly states that elevation of temperature does not induce new transport pathways in the skin. Equation 5 then reduces to the following.
Permeation routes of highly hydrophilic solutes (Ko/w < 0.1) are not completely understood. Studies have shown that some small hydrophilic solutes, specifically water, can easily diffuse in the corneocytes and are likely to permeate the skin via the transcellular route; but the rate limiting step is still permeation across the lipids.10 Transport pathways of larger hydrophilic solutes, for example, mannitol are more complex. It is likely that they can diffuse in the corneocytes rapidly and hence the rate-limiting step is again
where, ED w is the activation energy of solute diffusion in water. Estimation of E requires
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E ¼ ED wR
@ ln HðlÞ @ð1=TÞ
ð6Þ
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knowledge of thermal expansion coefficient of pores, that is, @l=@ð1=TÞ. However, since no specific structure can be assigned to the pores, determination of @l=@ð1=TÞfrom the first principles is difficult. Typical pore radii in the skin ˚ ,11 a number have been found to be 20–30 A significantly larger than the solute radii considered in this study (Tab. 1). Hence, reduction in hindrance due to pore expansion will be small even if the pores were to expand substantially. For the sake of calculations, let us assume that the pore radius doubles for every 108C increase in skin temperature. For this case, the average magnitude of the final term in Eq. (6) for a typical ˚ ) is less than 2 kJ/mole, a small solute (r ¼ 4 A number very small compared to the experimentally measured activation energies (see Tab. 1). Accordingly, it can be assumed that the contribution of the final term in Eq. (6) can be neglected and the activation energy of hydrophilic solutes can be approximated by the following equation. E ED W
ð7Þ
Typical values of ED W for small hydrophilic solutes, for example, water are on the order of 20 kJ/mole.
RESULTS The model makes two predictions: (i) the activation energy for hydrophobic solutes is greater than that for hydrophilic solutes and (ii) the activation energy for hydrophobic solutes increases with increasing solute size. These predictions were tested against available experimental data compiled from the literature (Tab. 1). Solute classification into hydrophilic and hydrophobic was done based on their Ko/w. In the most simplistic way, hydrophobic solutes can be defined as those with Ko/w > 1. Based on this classification, data in Table 1 showed that the difference between activation energies of hydrophilic and hydrophobic solutes is not significant (p ¼ 0.13, t-test). However, this definition of hydrophobicity is arbitrary since it is not clear that the permeation route changes from intercellular lipids to porous pathway at Ko/w ¼ 1. To probe this matter in detail, we redefined solute hydrophobicity as follows; hydrophilic (Ko/w < 0.1), intermediate (0.1 < Ko/w < 10), hydrophobic (10 < Ko/w < 1000), and highly hydrophobic (Ko/w > 1000). This classification brought out the differences in a better JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 96, NO. 7, JULY 2007
way. Specifically, this analysis showed that activation energies of hydrophilic solutes are smaller than intermediate, hydrophobic, and highly hydrophobic solutes (see Tab. 2 for a summary of p values for pairwise comparisons between all groups). The analysis also showed that the activation energies of highly hydrophobic solutes are higher than any other group. The comparison between intermediate and hydrophobic solutes, however, did not agree with the model. Specifically, the activation energies of hydrophobic solutes are smaller than intermediate solutes, a conclusion inconsistent with the model but consistent with that made by Roberts et al. Note that the model presented here does not suggest that the activation energy is a continuous function of Ko/w. Hence, assumption of a continuous trend is discouraged. The only prediction made by the model is that the activation energies of hydrophobic solutes in general are greater than those of hydrophilic solutes. This conclusion is supported by the statistical analysis in Table 2 except in one case (intermediate vs. hydrophobic). The model also predicts that the activation energy of hydrophobic solutes increases with solute radius (Eq. 3). Dependence of activation energy on solute radius was evaluated separately for hydrophilic, intermediate, hydrophobic, and highly hydrophobic solutes (Fig. 1). The trends were in agreement with the model for extreme cases (hydrophilic and highly hydrophobic). Specifically, no correlation between activation energy and solute size was found for hydrophilic solutes as expected (r ¼ 0.2) and a good correlation was found between the same for highly hydrophobic solutes (r ¼ 0.8). The trends were not significant for the remaining two categories (intermediate and hydrophobic, r ¼ 0.5 and 0.4, respectively).
DISCUSSION Activation energy of transdermal permeation has received significant attention, especially in light of its relevance to elucidating the permeation pathways. Early foundation was provided by the data of Roberts et al.1 and Scheuplein and Blank2 who suggested that activation energy is lower for relatively hydrophobic solutes. These conclusions were reached based on the permeability data for aliphatic alcohols and phenolic compounds. However, Peck et al.3 showed that the activation energies of highly hydrophilic compounds such as DOI 10.1002/jps
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TEMPERATURE DEPENDENCE OF SKIN PERMEABILITY
Table 1. Literature Data on Activation Energies of Skin Permeability to Various Solutes
No.
Solute
1 2 3 4
Acetylsalicylic acid AZT Betahistine Butanol (n-butanol)
MW Da
Log Ko/w
180 267 300 74
1.19 0.05 0.68 0.88
5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
Butanone (2-butanone) Butyl paraben p-Bromophenol Caffeine Carbon disulfide Chlorocresol o-Chlorophenol Corticosterone m-Cresol o-Cresol p-Cresol 1,1-Dichloropropanone Ethyl ether Estradiol Ethanol
72 194 173 194 76 143 128 346 108 108 108 126 74 272 46
0.29 3.57 2.59 0.02 1.94 3.1 2.15 1.94 1.96 1.95 1.95 1.18 0.89 3.86 0.31
20 21
Ethoxy ethanol 5-Fluorouracil
90 200
0.28 0.89
22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46
Glycopyrrolate Heptanol (n-heptanol) Hexanol (n-hexanol) Ibuprofen Imipramine hydrochloride Indomethacin Ion conductivity Ketoprofen Mannitol Methanol Methyl paraben Methylsalicylic acid b-Naphthol m-Nitrophenol Octanol (n-octanol) Oxygen Pentanol Phenol Propanol Propionic acid Resorcinol Sarin Tetraethylammonium ion Thiourea Thymol
398 116 102 206 280 360 23 254 180 32 152 152 144 139 130 32 88 94 60 74 110 140 134 76 150
1.2 2.34 2.03 3.5 2.5 4.27 — 3.12 3.1 0.71 1.96 2.55 2.84 2 3.15 0.65 1.34 1.46 0.3 0.33 0.8 0.3 — 1.05 3.34
Activation Energy kJ/mole 85 85 98 71 69.9 67.2 85 36.8 53 70.9 43.1 40.2 97 56.9 53.6 57.4 47 67.2 115 82 68.7 84 98 86 73.9 41.4 98 45.6 173 88 146 186 17 120a 36.7 77 65 57.4 41 55.7 71 42 44 69.1 60.3 69.1 47 74.5 70.9 34.8 67.7 52.8
Classification Hydrophobic Intermediate Intermediate Intermediate Intermediate Intermediate Highly hydrophobic Hydrophobic Intermediate Hydrophobic Highly hydrophobic Hydrophobic Hydrophobic Hydrophobic Hydrophobic Hydrophobic Hydrophobic Intermediate Highly hydrophobic Intermediate Intermediate Intermediate Intermediate Intermediate Hydrophilic Hydrophobic Hydrophobic Hydrophobic Hydrophobic Hydrophobic Highly hydrophobic Highly hydrophobic Hydrophilic Highly hydrophobic Hydrophilic Intermediate Hydrophobic Hydrophobic Hydrophobic Hydrophobic Highly hydrophobic Hydrophobic Intermediate Hydrophobic Hydrophobic Intermediate Intermediate Intermediate Intermediate Hydrophilic Hydrophilic Highly hydrophobic
References 2 17 18 4 1 2 19 1 19 2 1 1 3 1 1 1 20 2 18 4 1 2 21 22 2 1 4 1 23 24 18 23 25 26 3 4 19 2 1 1 4 2 27 1 1 1 28 1 2 3 2 1
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Table 1. (Continued)
No.
Solute
47 48 49 50
2,4,6-Trichlorophenol 1,1,1-Trichloropropanone Urea Water
MW Da
Log Ko/w
Activation Energy kJ/mole
197 160 60 18 18 18
3.69 1.75 2.11 1.38 1.38 1.38
38.1 51 29.6 57 71 61
Classification
References 1
Highly hydrophobic Hydrophobic Hydrophilic Hydrophilic Hydrophilic Hydrophilic
20 3 29 30 2
These data correspond to experiments performed on a variety of experimental model systems. Data from all experimental systems are collected and analyzed together. a Recalculated from published data; partition coefficients obtained from Log Ko/w databank or determined using ChemSW software.
sugars and urea are much lower than those for hydrophobic solutes. Theoretical analyses of activation energies have also been performed to gain insights into this issue. Models describing skin permeation based on free volume type of approaches have been developed; and these models implicitly account for the temperature dependence of skin permeability.14–16 Kasting et al.14 compared a free volume type equation for skin permeability (P exp[aV] where a represents free volume in SC lipid bilayers and V is solute volume) and the Arrhenius equation (P exp[E/RT], where E is the activation energy) and estimated the activation energies of skin permeability. Their analysis led to the conclusion that activation energies estimated this way are five- to tenfold lower than experimentally observed values.14 However, this analysis was based on transdermal fluxes and not permeabilities. Nevertheless, analysis of Kasting et al. makes a direct case for the existence of sizedependent activation energies based on a qualitative comparison of the exponents. The equations presented here allow a detailed analysis of activation energies across a wide range of solute properties. The prediction of the model
that hydrophobic solutes have higher activation energies than hydrophilic solutes is supported by the data with once exception (Tab. 2). The high activation energies of hydrophobic solutes are a direct consequence of a strong dependence of their permeability on molecular size. Volumes of hydrophobic solutes in Table 1 are comparable to the mean free volumes in lipid bilayers.8 Hence, thermal expansion of lipid bilayers, which increases the free volume, makes significant contributions to activation energies. The prediction that activation energy of hydrophobic solutes increases with solute size is in agreement with data for highly hydrophobic solutes (Fig. 1d) but not for relatively less hydrophobic solutes (Fig. 1c). The reason behind this is not clear. A closer look at Eq. (3) reveals that it does not show a classical Arrhenius behavior. The first term on the right hand side is temperature-dependent, thereby making E temperature-dependent. The extent of departure from the Arrhenius behavior is determined by the temperature dependence of A. A formal expression for A has been derived in Ref.8. A depends primarily on the free area in the SC lipid bilayers, af, and order parameters of lipid chains. A first order approximation of A (see Eq. 16 in Ref.8)
Table 2. Summary of p Values (Sudent’s t-Test) for Comparison of Activation Energies between Different Groups of Solutes (Hydrophilic, Intermediate, Hydrophobic, and Highly Hydrophobic)
Solute Classes Based on Ko/w Hydrophilic Ko/w < 0.1 Intermediate 0.1 < Ko/w < 10 Hydrophobic 10 < Ko/w < 1000 Highly hydrophobic Ko/w > 1000
Hydrophilic Ko/w < 0.1
Intermediate 0.1 < Ko/w < 10
Hydrophobic 10 < Ko/w < 1000
Highly Hydrophobic Ko/w > 1000
NA 0.001 0.08 0.011
NA 0.017a 0.038
NA 0.0047
NA
The matrix is symmetric and values only on one side of the diagonal are reported. a Activation energies of hydrophobic solutes are smaller than those for intermediate solutes. All other p values confirm the hypothesis suggested by the model, that is, activation energy increases with increasing hydrophobicity. JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 96, NO. 7, JULY 2007
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Figure 1. Dependence of activation energy on solute radius, assessed separately for (a) hydrophilic (Ko/w < 0.1), (b) intermediate (0.1 < Ko/w < 10), (c) hydrophobic (1000 > Ko/w > 10), and (d) highly hydrophobic (Ko/w > 1000) solutes. The data are taken from Table 1. The regression coefficients for linear fits are (a) 0.2, (b) 0.5, (c) 0.4, and (d) 0.8.
shows that A 1/af. af, in turn, increases proportionately with temperature away from the phase transition temperature. Hence, the term @A/@(1/T) is independent of temperature to a first approximation. Accurate estimation of @A/@(1/T) for SC lipid bilayers cannot be performed since af for SC lipid bilayers and its dependence on temperature are not known. However, these parameters are known for dipalmitoyl phosphatidylcholine bilayers (DPPC) and calculations based on experimentally measured thermal expansion coefficients
of DPPC bilayers lead to @A/@(1/T) between 300 ˚ 2. This implies that the contribution of and 500 K/A the size-dependent term to the activation energy ˚ (the for a solute with radius between 4 and 5 A largest hydrophobic solute in this study) is between 50 and 80 kJ/mole, which is 25–45% of the total activation energy for that solute. The prediction of the model that activation energies of hydrophilic solutes are insensitive to solute size (Eq. 7) is supported by experimental data (Fig. 1a). Mechanistic origins of this
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dependence can be found in the equations of the porous pathway model. This model assumes that highly hydrophilic solutes diffuse through permeable pores distributed in an impermeable matrix. No precise structure can be associated with these pores, although structural defects in the skin have been thought to constitute the porous pathway.6 Although precise interpretation of the porous pathway model is debatable, the most important parameter for this study is the pore radius. The pore radii necessary to explain the permeation of hydrophilic solutes in Table 1 are in the range of ˚ ,11 a number significantly greater than the 20–30 A radii of solutes reported in Table 1. Thus, thermal expansion of pores, if any, does not contribute significantly to the enhanced permeability at higher temperatures. This leads to lower activation energies. This study provides a theoretical platform to analyze the activation energies of skin permeability to hydrophilic and hydrophobic solutes. The study also provides a compilation of the literature data on this topic. While interpreting the model and its conclusions, the underlying assumptions must be kept in mind. Specifically, the model assumes that SC is always the rate-limiting step in skin permeation. It is possible, especially if the SC is highly permeable, that the unstirred boundary layer or the epidermis may become an important contributor to permeation resistance.1 Robert et al. showed that such shifts in rate limiting steps can induce solute-dependent changes in activation energy. Similar situation will also arise should epidermis or appendages contribute significantly to permeation resistance. Such situation-dependent and solute-dependent changes in activation energy should be analyzed in future studies. The model also assumes that solute partition coefficient does not depend on temperature and that the permeation pathways do not change as a function of temperature. Several questions remain that require more analysis and experimentation. For example, data of Roberts et al. and Scheuplein and Blank show an inverse dependence of activation energies on lipophilicity. This trend can be seen in the data presented here as well. Specifically, Table 2 shows that activation energy of hydrophobic solutes is smaller than intermediate solutes (p ¼ 0.017), an observation that contradicts the model. It is not immediately clear why the model predictions are not in agreement with experimental data for these two categories. It is possible that some of the assumptions behind the model or the basic premise of the model are not applicable for
such solutes for reasons that are not apparent. Future research should focus on this aspect. Another consideration that needs further investigation is that the data presented here has been collected on human as well as animal skin. Further experiments are necessary to identify any speciesspecific trends. Additional studies searching for alternate interpretations of the data should also be pursued. It is also clear from Table 1 that relatively fewer data points are available on highly hydrophilic solutes and additional measurements will further facilitate the analysis presented in this study.
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