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 (CACO-2 and MDCK), cell-free model systems like parallel artificial membrane permeability assay (PAMPA) mimicking, e.g., gastrointestinal epithelia or the skin, as well as the black lipid membrane (BLM) and submicrometer 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. Four experimental and two computational methods were evaluated. It was shown that repeatability of the reported permeability measurement is not great even for the same method. For the PAMPA method, two different permeabilities are reported: intrinsic and apparent. They can vary in degrees of magnitude; thus, we suggest being extra cautious using literature data on permeability. When we compared data for the same molecules using different methods, the best agreement was between cell-based methods and between BLM and computational methods. Existence of unstirred water layer (UWL) permeability limits the data agreement between cell-based methods (and apparent PAMPA) with data that are not limited by UWL permeability (computational methods, BLM, intrinsic PAMPA). Therefore, different methods have different limitations. Cell-based methods provide results only in a small range of permeabilities (-8 to -4 in cm/s), and computational methods can predict a wider range of permeabilities beyond physical limitations, but their precision is therefore limited. BLM with liposomes can be used for both fast and slow permeating molecules, but its usage is more complicated than standard transwell techniques. To sum up, when working with in-house measured or published permeability data, we recommend caution in interpreting and combining them.