Engineering human brain microphysiological systems for alzheimer's disease (AD) and chronic traumatic encephalopathy (CTE) modeling and drug testing: translational promise, limitations, and future directions

This review examines the emerging role of human brain microphysiological systems (HBMPS) in recapitulating diseases and evaluating their translational potential and limitations for Alzheimer's disease (AD) and chronic traumatic encephalopathy (CTE). Both disorders differ in underlying cause, but converge on shared downstream pathophysiology such as tau pathology, neuroinflammation, and blood-brain barrier (BBB) dysfunction. We review the critical pathophysiological features relevant to modeling AD and CTE and introduce HBMPS platforms/validation strategies as potential tools for evaluating therapeutic compounds as well as drug-delivery approaches. We also provide a systematic comparison of the relative advantages and disadvantages of 2D, HBMPS, Xenograft, and animal models and discuss the future potential of HBMPS's drug-testing platform. We further discuss current challenges of HBMPS related to drug testing, engineering extracellular matrix for tissue chips, and BBB penetration in AD and CTE. We suggest future integration of organoid xenografts and AI-assisted frameworks to enhance pathophysiological fidelity/drug predictive capability and to bridge the gap between HBMPS and animal models. In summary, this paper reviews HBMPS technologies as future translation platforms' direction for drug screening and delivery, while providing current limitations and challenges including model validation, reproducibility, and standardized regulatory bases required for preclinical success for HBMPS use. Rather than comparing biological complexity with translational validity, this review applies a decision-oriented framework that distinguishes mechanistic fidelity, comparative candidate ranking, predictive validation, investigational new drug (IND)-supporting use, and replacement of a defined animal test. For each use, we identify quantitative transport, exposure-response, pharmacodynamic, safety, and reproducibility evidence required to support an advance, redesign, or go/stop decision.