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 K-w(IAM) data. Then we applied block relevance (BR) analysis to extract from PLS models the relative contribution of intermolecular forces governing log K-w(IAM) and Delta log K-w(IAM) (a combined descriptor calculated from log K-w(IAM)). Finally, the relationship between log K-w (IAM),Delta log K-w(IAM) 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.