This study finds accurate membrane permeability predictions in Caco-2 and MDCK cells, suggesting HDM-PAMPA can enhance high-throughput screening methods.
Reliable membrane permeability data are essential in early drug development. Therefore, there is a strong need for robust experimental high-throughput screening methods, or ideally, accurate predictive tools, to assess membrane permeability. In a previous study, we demonstrated that the solubility-diffusion model can successfully predict passive permeability across biological Caco-2 and MDCK membranes, provided accurate hexadecane/water partition coefficients (Khex/w) are available. In this study, we investigated the HDM-PAMPA method for determining Khex/w. We measured our own data (64 compounds) using this assay and compared the results with established methods such as black lipid membrane (BLM) experiments and classical two-phase systems. Our results show good agreement across methods, with both our data and literature values aligning closely. Using these experimentally determined Khex/w values, we achieved accurate predictions of permeability in Caco-2 and MDCK cell membranes (RMSE = 0.8, n = 29) based on a previously calibrated equation. We further evaluated the in silico prediction of Khex/w using the UFZ-LSER database and the software COSMOtherm. COSMOtherm performed nearly as well as experimental measurements (RMSE = 1.20, n = 29), while the LSER approach (RMSE = 1.63, n = 29) is best applied when experimental descriptors are available or as a complement to COSMOtherm. This work highlights the practical utility of Khex/w in high-throughput permeability estimation, which can support efficient screening and prioritization of drug candidates in pharmaceutical research.
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Dahley et al. (2025) studied this question.
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