Engineering the blood–brain barrier on chip: advances in preclinical drug penetration and disease modeling
Year: 2026
Type: review
Abstract: The blood-brain barrier (BBB) remains the single most significant obstacle to the successful delivery of therapeutics to the central nervous system (CNS), with over 98% of small-molecule drugs failing to penetrate the brain parenchyma. Conventional preclinical models ranging from static Transwell® assays to healthy animal surrogates, frequently fail to predict human pharmacokinetic profiles due to species-specific differences and a lack of physiological complexity. This review examines the emergence of BBB-on-chip technologies as a transformative solution to bridge this translational gap. We detail the bioengineering strategies enabling the reconstitution of the human neurovascular unit in vitro, including the integration of induced pluripotent stem cell (iPSC)-derived cellular components, physiological shear stress, and 3D extracellular matrices. We critically evaluate the application of these microphysiological systems (MPS) in assessing diverse therapeutic modalities, from small molecules and antibodies exploiting receptor-mediated transcytosis to complex nanocarriers. Furthermore, we highlight a paradigm shift in preclinical testing: moving beyond healthy baselines to model pathological BBB phenotypes associated with neurodegenerative diseases, brain tumors, and acute injuries. By capturing disease-specific defects such as barrier leakage and transporter dysregulation, these "disease-tuned" platforms offer unprecedented mechanistic insight into drug delivery under compromised conditions. Finally, we discuss current translational hurdles, including material limitations and validation standards, and propose a future development where high-fidelity in vitro data are integrated with physiologically based pharmacokinetic (PBPK) modeling to enable robust in silico-in vitro extrapolation (IVIVE) for clinical prediction.
Source: Advanced Drug Delivery Reviews
Language: English
Subfield: Neurology
Field: Neuroscience
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $5,550
OpenAlex ID: W7156909976