Centre of Biomedicine and Global Health, School of Applied Sciences, Sighthill Campus, Edinburgh Napier University, 9 Sighthill Ct, Edinburgh EH11 4BN, United Kingdom.
Department of Chemistry, University of Helsinki, A.I. Virtasen aukio 1, P. O. Box 55 00014, Finland.
J Chromatogr A. 2024 Oct 11;1734:465286. doi: 10.1016/j.chroma.2024.465286. Epub 2024 Aug 18.
This study pioneers a comparison of the application of biomimetic techniques, immobilised artificial membrane liquid chromatography (IAM LC) and liposome electrokinetic capillary chromatography (LEKC), for the prediction of pulmonary drug permeability. The pulmonary absorption profiles of 26 structurally unrelated drug-like molecules were evaluated using their IAM hydrophobicity index (CHI IAM) measured in IAM LC, and the logarithm of distribution constants (log K) derived from the LEKC experiments. Lipophilicity (phospholipids) parameters obtained from IAM LC and most LEKC analyses were linearly related to the n-octanol/water partitioning coefficients of the neutral forms (i.e., log P values) to a moderate extent. However, the relationship with distribution coefficients at the experimental pH (7.4) (i.e., log D) were weaker overall for IAM LC data and sigmoidal for some liposome compositions (phosphatidyl choline (PC): phosphatidyl inositol (PI) 85:15 mol% and 90:10 mol%) and concentrations (4 mM) in LEKC. This suggests that phospholipid partitioning supports both hydrophobic and electrostatic interactions occurring between ionised drugs and charged phospholipid moieties. The latter interactions are original when compared to those taking place in the more established n-octanol/water partitioning systems. A stronger correlation (R > 0.65) was identified between the LEKC retention parameters, and the experimental apparent lung permeability (i.e., log P values) as opposed to the values obtained by IAM LC. Therefore, LEKC offers unprecedented advantages over IAM LC in simulating cell membrane partitioning processes in the pulmonary delivery of drugs. Although LEKC has the advantage of more effectively simulating the electrostatic and hydrophobic forces in drug/pulmonary membrane interactions in vitro, the technique is unsuitable for analysing highly hydrophilic neutral or anionic compounds at the experimental pH. Conversely, IAM LC is useful for analysing compounds spanning a wider range of lipophilicity. Its simpler and more robust implementation, and propensity for high-throughput automation make it a favourable choice for researchers in drug development and pharmacological studies.
本研究开创性地比较了仿生技术在预测肺部药物渗透性方面的应用，包括固定化人工膜液相色谱（IAM LC）和脂质体电动毛细管色谱（LEKC）。使用在 IAM LC 中测量的 IAM 疏水性指数（CHI IAM）和从 LEKC 实验中得出的分配常数（log K）评估了 26 种结构上无关的类药分子的肺部吸收谱。从 IAM LC 和大多数 LEKC 分析中获得的亲脂性（磷脂）参数与中性形式的正辛醇/水分配系数（即 log P 值）呈中等程度的线性关系。然而，对于 IAM LC 数据，与在实验 pH（7.4）下的分配系数（即 log D）的关系总体上较弱，而对于某些脂质体组成（磷脂酰胆碱（PC）：磷脂酰肌醇（PI）85:15 mol%和 90:10 mol%）和浓度（4 mM）的 LEKC 呈 sigmoidal 关系。这表明磷脂分配支持离子化药物与带电磷脂部分之间发生的疏水和静电相互作用。与更成熟的正辛醇/水分配系统相比，后者的相互作用是原始的。LEKC 保留参数与实验表观肺渗透性（即 log P 值）之间的相关性更强（R > 0.65），而不是与 IAM LC 获得的值之间的相关性。因此，与 IAM LC 相比，LEKC 在模拟药物肺部传递中的细胞膜分配过程方面具有前所未有的优势。尽管 LEKC 具有在体外更有效地模拟药物/肺膜相互作用中的静电和疏水作用力的优势，但该技术不适合在实验 pH 下分析高度亲水的中性或阴离子化合物。相反，IAM LC 适用于分析跨越更广泛亲脂性范围的化合物。其更简单、更稳健的实现以及高通量自动化的倾向使其成为药物开发和药理学研究人员的首选。
