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 KwIAMdata. Then we applied block relevance (BR) analysis to extract from PLS models the relative contribution of intermolecular forces governing log KwIAMand Δlog KwIAM(a combined descriptor calculated from log KwIAM). Finally, the relationship between log KwIAM, Δlog KwIAMand 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.

Learning how to use IAM chromatography for predicting permeability

Ermondi, Giuseppe
First
;
Vallaro, Maura;Caron, Giulia
Last
2018-01-01

Abstract

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 KwIAMdata. Then we applied block relevance (BR) analysis to extract from PLS models the relative contribution of intermolecular forces governing log KwIAMand Δlog KwIAM(a combined descriptor calculated from log KwIAM). Finally, the relationship between log KwIAM, Δlog KwIAMand 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.
2018
114
385
390
BR Analysis; Chromatography; IAM; MDCK-LE; PAMPA; Permeability; VolSurf+
Ermondi, Giuseppe; Vallaro, Maura; Caron, Giulia
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1660453
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