papersSEP 10 04:00 UTC
Explainable ML Framework Predicts Blood-Brain Barrier Permeability from Molecular Descriptors
A new arXiv paper presents an explainable machine learning framework that predicts blood-brain barrier permeability using molecular descriptors. Since this barrier determines whether central nervous system drug candidates can reach targets in the brain, the approach could support earlier screening in drug development. Its explainable design is intended to reveal which molecular features drive the model's predictions.