Revisiting blood-brain barrier: A chromatographic approach

Abstract

Drugs designed to reach a pharmacological CNS target must be effectively transported across the blood-brain barrier (BBB), a thin monolayer of endothelial cells tightly attached together between the blood and the brain parenchyma. Because of the lipidic nature of the BBB, several physicochemical partition models have been studied as surrogates for the passive permeation of potential drug candidates across the BBB (octanol-water, alkane-water, PAMPA...). In the last years, biopartition chromatography is gaining importance as a noncellular system for the estimation of biological properties in early stages of drug development. Microemulsions (ME) are suitable mobile phases, because of their ease of formulation, stability and adjustability to a large number of compositions mimicking biological structures. In the present work, several microemulsion liquid chromatographic (MELC) systems have been characterized by means of the Abraham's solvation parameter model, in order to assess their suitability as BBB distribution or permeability surrogates. In terms of similarity between BBB and MELC systems (dispersion forces arising from solute non-bonded electrons, dipolarity/polarizability, hydrogen-bond acidity and basicity, and molecular volume), the passive permeability surface area product (log PS) for neutral (including zwitterions), fully and partially ionized drugs was found to be well correlated with the ME made of 3.3% SDS (w/v; surfactant) 0.8% heptane (w/v; oil phase) and 6.6% 1-butanol (w/v; co-surfactant) in 50mM aqueous phosphate buffer, pH 7.4.

PerMM: A Web Tool and Database for Analysis of Passive Membrane Permeability and Translocation Pathways of Bioactive Molecules

“…Currently, quantitative structure–permeability relationship (QSPR) models are the primary tools for ADME optimization and selection of potential drug candidates in the early stages of drug development. These models use experimentally and computationally derived properties of organic molecules to predict their oral bioavailability, intestinal absorption, and permeability through black lipid membranes (BLM), the blood–brain barrier (BBB), the gut epithelium, or skin multilayered membranes. − Statistics-based models for prediction of various ADME properties have been combined into state-of-the-art publicly or commercially available web tools, such as admetSAR, pkCSM, SwissADME, or QikProp (Schrödinger, LLC).…”

Linear free energy relationship models for the retention of partially ionized acid-base compounds in reversed-phase liquid chromatography

“…The correlation obtained is presented in Eq. (24). The 123 solutes comprise 15 anions, 15 cations and 93 of the 94 neutral solutes (5fluorouracil was excluded because k < 0.10).…”

Combining SILCS and Artificial Intelligence for High-Throughput Prediction of Drug Molecule Passive Permeability

“…Since these experimental methods are cost and time intensive, there has been considerable interest in developing in-silico methods for predicting drug permeability. Initially, methods based on the physical properties of compounds [22][23][24][25][26] were used to rapidly evaluate the permeability of molecules. Though these methods enable screening on large datasets, they are of limited accuracy and are unable to capture atomistic details of the permeability process.…”