Advancing Organ-on-a-Chip Technologies: A Review on the Multi-Organ Approach for Precision Disease Modeling and Drug Screening

Abstract

Organ-on-a-chip (OOC) technology has emerged as a transformative approach for recreating human tissue physiology by integrating microfluidics, biomaterials, tissue engineering, and stem cell biology into physiologically relevant microenvironments. Compared with conventional two-dimensional cell cultures and animal models, OOC platforms more faithfully reproduce tissue architecture, dynamic biochemical signaling, mechanical cues, and multicellular interactions, improving the predictive value of disease models and preclinical drug evaluation. This review examines the evolution of OOC technology from single-organ microphysiological systems to interconnected multi-organ platforms capable of reproducing systemic physiology, pharmacokinetics, and inter-organ communication. Representative organ-specific models are discussed to illustrate how advances in device design and biomimetic microenvironments have expanded applications in disease modeling, toxicology, regenerative medicine, and drug screening. Beyond recent biological developments, particular emphasis is placed on the challenges that continue to limit widespread implementation, including physiological scaling, material selection, manufacturing reproducibility, standardization, and regulatory translation. The review further explores the growing integration of artificial intelligence with OOC platforms, highlighting emerging applications in automated image analysis, biosensor interpretation, predictive modeling, digital twins, and adaptive experimental control. Finally, a practical roadmap is proposed that identifies standardized validation strategies, quantitative performance metrics, and interdisciplinary collaboration as key priorities for accelerating clinical and industrial adoption. By bringing together biological, technological, and computational perspectives, this article provides a comprehensive overview of current progress while outlining the advances needed to establish OOC platforms as reliable tools for precision disease modeling and next-generation drug discovery.