Permeability coefficients (Pm) across planar egg lecithin/decane bilayers and bulk hydrocarbon/water partition coefficients (Kw-->hc) have been measured for 24 solutes with molecular volumes, V, varying by a factor of 22 and Pm values varying by a factor of 10(7) to explore the chemical nature of the bilayer barrier and the effects of permeant size on permeability. A proper bulk solvent which correctly mimics the microenvironment of the barrier domain was sought. Changes in Pm/Kw-->hc were then ascribed to size-dependent partitioning and/or size-dependent diffusivity. The diffusion coefficient-size dependency was described by Dbarrier = Do/Vn. When n-decane was used as a reference solvent, the correlation between log Pm/Kw-->hc and log V was poor (r = 0.56) with most of the lipophilic (hydrophilic) permeants lying below (above) the regression line. Correlations improved significantly (r = 0.87 and 0.90, respectively) with more polarizable solvents, 1-hexadecene and 1,9-decadiene. Values of the size selectivity parameter n were sensitive to the reference solvent (n = 0.8 +/- 0.3, 1.2 +/- 0.1 and 1.4 +/- 0.2, respectively, for decane, hexadecene, and decadiene). Decadiene was selected as the most suitable reference solvent. The value for n in bilayer transport is higher than that for bulk diffusion in decane (n = 0.74 +/- 0.10), confirming the steep dependence of bilayer permeability on molecular size. Statistical mechanical theory recently developed by the authors suggests that a component of this steep size dependence may reside in size-dependent solute partitioning into the ordered chain region of bilayers. This theory, combined with the above diffusion model, yielded the relationship, Pm/Kw-->hc = D(o)exp(-alpha V)Vn. A fit of the experimental data to this model gave the best fit (r = 0.93) with alpha = 0.0053 +/- 0.0021 and n = 0.8 +/- 0.3, suggesting that both diffusion and partitioning mechanisms may play a role in determining the size dependence of lipid bilayer permeabilities.

The effects of lipid chain packing and permeant size and shape on permeability across lipid bilayers have been investigated in gel and liquid crystalline dipalmitoylphosphatidylcholine (DPPC) bilayers by a combined NMR line-broadening/dynamic light scattering method using seven short-chain monocarboxylic acids (formic acid, acetic acid, propionic acid, butyric acid, valeric acid, isovaleric acid, and trimethylacetic acid) as permeants. The experimental permeability coefficients are compared with the predictions of a bulk solubility diffusion model in which the bilayer membrane is represented as a slab of bulk hexadecane. Deviations of the observed permeability coefficients (Pm) from the values predicted from solubility diffusion theory (Po) lead to the determination of a correction factor, the permeability decrement f (= Pm/Po), to account for the effects of chain ordering. The natural logarithm of f has been found to correlate linearly with the inverse of the bilayer free surface area with slopes of 25 +/- 2, 36 +/- 3, 45 +/- 8, 32 +/- 12, 33 +/- 4, 49 +/- 12, and 75 +/- 6 A2 for formic acid, acetic acid, propionic acid, butyric acid, valeric acid, isovaleric acid, and trimethylacetic acid, respectively. The slope, which measures the sensitivity of the permeability coefficient of a given permeant to bilayer chain packing, exhibits an excellent linear correlation (r = 0.94) with the minimum cross-sectional area of the permeant and a poor correlation (r = 0.59) with molecular volume, suggesting that in the bilayer interior the permeants prefer to move with their long principal axis along the bilayer normal. Based on these studies, a permeability model combining the effects of bilayer chain packing and permeant size and shape on permeability across lipid membranes is developed.

Solubility-diffusion theory, which treats the lipid bilayer membrane as a bulk lipid solvent into which permeants must partition and diffuse across, fails to account for the effects of lipid bilayer chain order on the permeability coefficient of any given permeant. This study addresses the scaling factor that must be applied to predictions from solubility-diffusion theory to correct for chain ordering. The effects of bilayer chemical composition, temperature, and phase structure on the permeability coefficient (Pm) of acetic acid were investigated in large unilamellar vesicles by a combined method of NMR line broadening and dynamic light scattering. Permeability values were obtained in distearoylphosphatidylcholine, dipalmitoylphosphatidylcholine, dimyristoylphosphatidylcholine, and dilauroylphosphatidylcholine bilayers, and their mixtures with cholesterol, at various temperatures both above and below the gel-->liquid-crystalline phase transition temperatures (Tm). A new scaling factor, the permeability decrement f, is introduced to account for the decrease in permeability coefficient from that predicted by solubility-diffusion theory owing to chain ordering in lipid bilayers. Values of f were obtained by division of the observed Pm by the permeability coefficient predicted from a bulk solubility-diffusion model. In liquid-crystalline phases, a strong correlation (r = 0.94) between f and the normalized surface density sigma was obtained: in f = 5.3 - 10.6 sigma. Activation energies (Ea) for the permeability of acetic acid decreased with decreasing phospholipid chain length and correlated with the sensitivity of chain ordering to temperature, [symbol: see text] sigma/[symbol: see text](1/T), as chain length was varied. Pm values decreased abruptly at temperatures below the main phase transition temperatures in pure dipalmitoylphosphatidylcholine and dimyristoylphosphatidylcholine bilayers (30-60-fold) and below the pretransition in dipalmitoylphosphatidylcholine bilayers (8-fold), and the linear relationship between in f and sigma established for liquid-crystalline bilayers was no longer followed. However, in both gel and liquid-crystalline phases in f was found to exhibit an inverse correlation with free surface area (in f = -0.31 - 29.1/af, where af is the average free area (in square angstroms) per lipid molecule). Thus, the lipid bilayer permeability of acetic acid can be predicted from the relevant chain-packing properties in the bilayer (free surface area), regardless of whether chain ordering is varied by changes in temperature, lipid chain length, cholesterol concentration, or bilayer phase structure, provided that temperature effects on permeant dehydration and diffusion and the chain-length effects on bilayer barrier thickness are properly taken into account.

Dynamic dialysis is one of the most common methods for the determination of release kinetics from nanoparticle drug delivery systems. Drug appearance in the "sink" receiver compartment is a consequence of release from the nanoparticles into the dialysis chamber followed by diffusion across the dialysis membrane. This dual barrier nature inherent in the method complicates data interpretation and may lead to incorrect conclusions regarding nanoparticle release half-lives. Although the need to consider the barrier properties of the dialysis membrane has long been recognized, there is insufficient quantitative appreciation for the role of the driving force for drug transport across that membrane. Reversible nanocarrier binding of the released drug reduces the driving force for drug transport across the dialysis membrane leading to a slower overall apparent release rate. This may lead to the conclusion that a given nanoparticle system will provide a sustained release in vivo when it will not. This study demonstrates these phenomena using model lipophilic drug-loaded liposomes varying in lipid composition to provide variations in bilayer permeability and membrane binding affinities. Model simulations of liposomal transport as measured by dynamic dialysis were conducted to illustrate the interplay between the liposome concentration, membrane/water partition coefficient, and the apparent release rate. Reliable determination of intrinsic liposomal bilayer permeability coefficients for lipophilic drugs by dynamic dialysis requires validation of drug release kinetics at varying nanoparticle concentration and the determination of membrane binding coefficients along with appropriate mechanism-based mathematical modeling to ensure the reliability and proper interpretation of the data.

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