ABSTRACT
The parallel artificial membrane permeability assay (PAMPA) is widely used for estimating biomembrane permeabilities of experimental drugs in pharmaceutical research. However, there are few reports of studies using PAMPA to measure membrane permeabilities of chemicals of environmental concern (CECs) outside the pharmaceutical domain, many of which differ substantially from drugs in their physicochemical properties. We applied PAMPA methods simulating gastrointestinal (PAMPA-GIT) and blood-brain barrier (PAMPA-BBB) membranes under consistent conditions to 51 CECs, including some pharmaceuticals. A backward stepwise multivariate linear regression was implemented to explore the correlation between the differences of measured permeabilities from PAMPA-GIT and PAMPA-BBB and Abraham solute descriptors. In addition, a previously reported in silico model was evaluated by comparing predicted and measured permeability results. PAMPA-GIT and PAMPA-BBB experimental permeability results agreed relatively well. The backward stepwise multivariate linear regression identified excess molar refraction and polarizability to be significant at the 0.10 level in predicting the differences between PAMPA-GIT and PAMPA-BBB. The in silico model performed well - with predicted permeability of most compounds within two-fold of experimentally measured values. We found that CECs pose experimental challenges to the PAMPA method in terms of having lower solubility and lower stability compared to most drugs.
