DETERMINATION OF IN VITRO AND IN SILICO INDEXES FOR THE MODELLING OF BLOOD-BRAIN BARRIER PARTITIONING OF DRUGS VIA MICELLAR AND IMMOBILIZED ARTIFICIAL MEMBRANE LIQUID CHROMATOGRAPHY

In the present work, 79 structurally unrelated analytes were taken into account and their chromatographic retention coefficients, measured by Immobilized Artificial Membrane Liquid Chromatography (IAM-LC), and by Micellar Liquid Chromatography (MLC) employing sodium dodecyl sulfate (SDS) as surfactant, were determined. Such indexes were subsequently used for the development of Blood-Brain Barrier passage-predictive statistical models using partial least square (PLS) regression along with topological and physico-chemical parameters, calculated in silico. Highly significant relationships were observed either using IAM (r2 (n-1) = 0.78) or MLC (r2 (n-1) = 0.83) derived indexes along with in silico descriptors. This hybrid approach proved fast and effective in the development of highly predictive BBB passage oriented models and, therefore, it can be of interest for pharmaceutical industries as a high-throughput BBB penetration oriented screening method. Finally, it offered interesting insights into the molecular mechanism actually involved in the BBB permeation of drugs.