The parallel artificial membrane permeability assay (PAMPA), a non-cellular lab-based assay, is extensively used to measure the permeability of pharmaceutical compounds. PAMPA experiments provide a working mimic of a molecule passing through cells and PAMPA values are widely used to estimate drug absorption parameters. There is an increased interest in developing computational methods to predict PAMPA permeability values. We developed an in silico model to predict the permeability of compounds based on the PAMPA assay. We used the three-dimensional reference interaction site model (3D-RISM) theory with the Kovalenko–Hirata (KH) closure to calculate the excess chemical potentials of a large set of compounds and predicted their apparent permeability with good accuracy (mean absolute error or MAE = 0.69 units) when compared to a published experimental data set. Furthermore, our in silico PAMPA protocol performed very well in the binary prediction of 288 compounds as being permeable or impermeable (precision = 94%, accuracy = 93%). This suggests that our in silico protocol can mimic the PAMPA assay and could aid in the rapid discovery or screening of potentially therapeutic drug leads that can be delivered to a desired tissue.

平行人工膜渗透性测定 (PAMPA) 是一种基于非细胞实验室的测定，广泛用于测量药物化合物的渗透性。PAMPA 实验提供了分子通过细胞的工作模拟，PAMPA 值被广泛用于估计药物吸收参数。开发计算方法来预测 PAMPA 渗透率值的兴趣越来越大。我们开发了一种基于 PAMPA 分析的计算机模型来预测化合物的渗透性。我们使用三维参考相互作用位点模型 (3D-RISM) 理论和 Kovalenko – Hirata (KH) 闭合来计算大量化合物的过量化学势，并以良好的准确度（平均绝对误差或MAE = 0。69 个单位）与已发布的实验数据集相比。此外，我们的 in silico PAMPA 协议在 288 种化合物的可渗透或不可渗透的二元预测中表现非常好（精度 = 94%，准确度 = 93%）。这表明我们的 in silico 协议可以模拟 PAMPA 检测，并且可以帮助快速发现或筛选可以输送到所需组织的潜在治疗药物。