Learning how to use IAM chromatography for predicting permeability

The interest for IAM (Immobilized Artificial Membranes) chromatography in the prediction of drug permeability is increasing. Here we firstly set-up a dataset of 253 molecules including neutral and ionized drugs and few organic compounds for which we either measured or retrieved from the literature IAM.PC.DD2 log KwIAM data. Then we applied block relevance (BR) analysis to extract from PLS models the relative contribution of intermolecular forces governing log KwIAM and Δlog KwIAM (a combined descriptor calculated from log KwIAM). Finally, the relationship between log KwIAM, Δlog KwIAM and passive permeability determined in both PAMPA and MDCK-LE systems was looked for. Models provided the basis for a rational application of IAM chromatography in permeability prediction. [Display omitted]