Review highlights progress in multi-organ-on-a-chip platforms for drug screening, indicating that artificial intelligence and standardized validation will drive clinical translation.
Key Points
To review advancements in single- and multi-organ-on-a-chip platforms, their translational challenges, and their integration with artificial intelligence for disease modeling and drug discovery.
Synthesized literature on microfluidics, biomimetic tissue engineering, and stem cell biology across single- and multi-organ platforms.
Evaluated systemic physiological modeling, pharmacokinetics, and technical bottlenecks including scaling, materials, and standardization.
Analyzed the integration of artificial intelligence for biosensor interpretation, automated image analysis, and predictive digital twins.
Interconnected multi-organ systems more faithfully capture dynamic biochemical signaling, inter-organ communication, and systemic pharmacokinetics than 2D cultures or animal models.
Key translational barriers persist around physiological scaling, material compatibility, manufacturing reproducibility, and standardized regulatory qualification.
Incorporating machine learning and digital twins enhances real-time biosensing, predictive toxicity modeling, and adaptive experimental control.