Prediction of Drug Exposure in the Brain from the Chemical Structure

Abstract

The level of drug exposure in the brain is long known to relate to the physicochemical properties of the drug. The study of this relationship has attracted much attention through the years as it holds a promise that this drug property can be predicted in silico from the chemical drug structure. Various in vivo methodologies have been used to define and quantify drug exposure in the brain, the most commonly used parameter being logBB, which is the brain-to-blood ratio of the total drug concentrations. From datasets of logBB, it has been inferred that drug exposure in the brain is promoted by the lipophilicity, i.e. lipid solubility, of the drug and restricted by its hydrogen bonding potential. Recent work with the K_p,uu,brain parameter, representing a pharmacologically relevant brain-to-blood ratio of unbound drug concentrations, has confirmed the limiting effect of hydrogen bonding on drug exposure in the brain but also indicated no dependence on lipophilicity. The challenges associated with obtaining high predictivity models for K_p,uu,brain confirm the contemporary view of the blood-brain barrier as being not only physical and passive in nature but also involving specific carrier-mediated processes. It follows that in silico approaches need to compliment and merge with experimental methodologies to advance the field of brain exposure predictions.