In SilicoTools for Predicting Brain Exposure of Drugs
Hongming Chen, Susanne Winiwarter, Ola Engkvist · 2015
This chapter critically reviews recent in silico blood–brain barrier (BBB) penetration models available in the literature, including considerations on the experimental data used. Important molecular physicochemical properties which influence the brain exposure are highlighted. The chapter further discusses potential future directions for developing improved in silico BBB penetration prediction tools. One of the challenges for in silico modeling of brain exposure is the choice of the modeling end point. Currently there are quite a few parameters reported in the literature as characterizing brain penetration. All these parameters reflect different aspects of brain penetration, logBB still being the most widely used measure. Combining several QSAR models in a consensus model has been proven to be highly beneficial. Developing consensus models from models built on different descriptor sets and algorithms can be another way to further improve the accuracy of Kp,uu,brain models.