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.