Meta-analysis of permeability literature data shows possibilities and limitations of popular methods

Permeability is an important molecular property in drug discovery, as it co-determines pharmacokinetics whenever a drug crosses the phospholipid bilayer, e.g., into the cell, in the gastrointestinal tract or across the blood-brain barrier. Many methods for the determination of permeability have been developed, including cell line assays, cell-free model systems like PAMPA mimicking, e.g., gastrointestinal epithelia or the skin, as well as the Black lipid membrane (BLM) and sub-micrometer liposomes. Furthermore, many in silico approaches have been developed for permeability prediction. Meta-analysis of publicly available databases for permeability data (MolMeDB and ChEMBL) was performed to establish their usability. Firstly, experimental data can only be measured between thresholds for the lowest and highest permeation rate obtainable within physical boundaries. These thresholds vary strongly between methods. Secondly, computed data do not obey these thresholds but, on the other hand, can produce incorrect results. Thirdly, even for the same method and molecule, there is often a strong discrepancy between individual measured values. These differences are based not only on the statistics but also on the varying approaches and evaluation of the measured data. Thus, when working with in-house measured or published permeability data, we recommend to be cautious with their interpretation.