Precision targeting and regenerative therapies in articular cartilage diseases with AI-driven theranostics

Arthrochondral disorders affect the cartilage within joints, leading to symptoms such as discomfort, stiffness, and restricted movement. The barrier characteristics, such as the dense, negatively charged extracellular matrix (ECM) and limited vascular pathways, restrict the penetration, retention, and therapeutic performance of intra-articular nanomedicines. This review examines the design of cartilage-specific targeted delivery systems and integrated nanotheranostic systems and critically evaluates the extent to which artificial intelligence (AI) can support nanocarrier formulation, toxicity prediction, imaging analysis, and treatment stratification. This review discusses and analyzes existing research on AI-assisted nanotheranostics for AC diseases following the "barrier-design-validation-transformation" framework, while focusing on current experimental advancements, limitations of existing AI applications, and challenges in clinical implementation. It cannot be denied that AI-assisted nanotheranostic technologies represent a promising approach, but they remain in the emerging stage. Therefore, the evaluation of the clinical value of AI-assisted nanotheranostic technologies depends on standardized datasets, prospective validation, reproducible manufacturing processes, and a robust regulatory framework.

Abstract from PubMed (PMID 43021361). This entry was added automatically by our daily literature monitor because it matches the topics we follow; read the full paper at the original source.