Brain shuttle peptides: From permeability assay toolbox to data-driven discovery

The blood-brain barrier (BBB) is a highly selective transport interface that protects the central nervous system (CNS), but its complex cellular and molecular architecture presents a major challenge for drug delivery to the brain. Peptides have emerged as promising brain shuttles due to their selectivity, ease of synthesis, and ability to engage endogenous transport mechanisms such as receptor- or adsorptive-mediated transcytosis. We provide an overview of in vitro and in vivo models, ranging from artificial membranes, dynamic BBB-on-a-chip systems and mass-based quantification techniques to brain perfusion and molecular imaging. Particular emphasis is placed on how these approaches are selected and combined to assess BBB permeability, transport mechanisms, and brain distribution of peptide shuttles. Recently, machine learning methods have been increasingly used to identify peptide sequences with BBB-crossing potential. By highlighting recent examples and key methodological considerations, this chapter aims to guide researchers in selecting appropriate tools and strategies for studying peptide transport across the BBB.