Intervertebral Disc Organoids: Engineering Strategies, Disease Recapitulation, and Translational Perspectives
Yuliang Xie, Hongtao Hu, Hongshang Chu, Junyou Li, Hanqiang Liu, Jianwei Sun, Aijun Yang, Huancai Liu, Sheng WangIntervertebral disc (IVD) degeneration is a major contributor to low back pain and is closely linked to structural failure, inflammatory activation, extracellular matrix loss, and endplate-associated changes. Conventional experimental models, such as two-dimensional cell culture and animal studies, do not fully capture the structural complexity, multicellular interactions, and biomechanical environment of the human IVD. In recent years, advanced three-dimensional (3D) culture systems have emerged as promising platforms for studying disc biology and degeneration. While frequently grouped under the umbrella term “organoids,” the field currently lacks a widely accepted, experimentally validated true IVD organoid that spontaneously self-organizes to replicate the full macroscopic and microscopic complexity of the native joint. Instead, current progress relies heavily on engineered microtissues, spheroids, bioprinted constructs, and microphysiological organ-on-a-chip platforms. In this review, we establish an operational definition to distinguish these models and summarize current strategies for constructing them, with an emphasis on isolated and combined nucleus pulposus, annulus fibrosus, and cartilaginous endplate components. We critically evaluate their current capacity to recapitulate key pathological features of disc degeneration, including inflammation, catabolism, oxidative stress, and matrix remodeling. We further discuss their future aspirational applications in drug screening and personalized medicine, highlighting critical limitations related to structural fidelity, reproducibility, and translational scalability. While advanced 3D models represent a rapidly evolving field with substantial potential, a balanced assessment indicates that further rigorous validation is required before they can serve as established platforms for mechanistic discovery. We therefore introduce an intended-use evaluation method that assigns measurable evidence tiers and prespecified gate, major, supportive, or not-applicable weights, allowing models to be judged within—not across—their declared purpose.