Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran.
Pharm Res. 2013 Jan;30(1):41-59. doi: 10.1007/s11095-012-0847-9. Epub 2012 Oct 2.
To determine the outward permeability of retina-choroid-sclera (RCS) layer for different ophthalmic drugs and to develop correlations between drug physicochemical properties and RCS permeability.
A finite volume model was developed to simulate pharmacokinetics in the eye following drug administration by intravitreal injection. The RCS permeability was determined for 32 compounds by best fitting the drug concentration-time profile obtained by simulation with previously reported experimental data. Multiple linear regression was then used to develop correlations between best fit RCS permeability and drugs physicochemical properties.
The RCS drug permeabilities had values that ranged over 3 × 10(-6) m/s. Regression analysis for hydrophilic compounds showed that more than 92% of the variation in permeability values can be explained by correlative models of drug properties that include logarithm of the octanol-water partition coefficient (LogP), protein binding (PB), number of hydrogen bond acceptors (HBA), hydrogen bond donors (HBD), polar surface area (PSA) and dissociation constant (pKa) as independent variables. Regression analysis for lipophilic compounds showed that no significant correlation can be found between just physicochemical properties and RCS permeability.
Using the RCS permeability obtained from this study for different drugs, one can predict pharmacokinetics of intravitreal drug delivery systems such as solid implants or colloidal systems. Furthermore, the developed correlations between RCS permeability and physicochemical properties of drugs are useful in early drug development by predicting RCS permeability and drug concentration in the vitreous without experimental data.
确定视网膜脉络膜巩膜（RCS）层对不同眼科药物的外向渗透性，并建立药物物理化学性质与 RCS 渗透性之间的相关性。
开发了一个有限体积模型，以模拟通过玻璃体内注射给药后眼睛内的药代动力学。通过将模拟获得的药物浓度-时间曲线与先前报道的实验数据最佳拟合，确定了 32 种化合物的 RCS 渗透性。然后，使用多元线性回归建立最佳拟合 RCS 渗透性与药物物理化学性质之间的相关性。
RCS 药物渗透性的值范围在 3×10(-6) m/s 之间。亲水化合物的回归分析表明，渗透率值的变化超过 92%可以用包括药物性质的相关模型来解释，这些模型包括辛醇-水分配系数（LogP）的对数、蛋白结合（PB）、氢键受体（HBA）的数量、氢键供体（HBD）、极性表面积（PSA）和离解常数（pKa）作为独立变量。亲脂性化合物的回归分析表明，仅仅通过物理化学性质与 RCS 渗透性之间没有显著的相关性。
使用本研究中获得的不同药物的 RCS 渗透性，可以预测玻璃体内药物输送系统（如固体植入物或胶体系统）的药代动力学。此外，所建立的药物 RCS 渗透性与物理化学性质之间的相关性对于早期药物开发非常有用，可以在没有实验数据的情况下预测 RCS 渗透性和玻璃体内的药物浓度。
