This review explores programmable biomaterials to enhance tissue regeneration in musculoskeletal disorders, suggesting improved therapeutic strategies.
Musculoskeletal disorders (MSDs), encompassing a variety of degenerative and inflammatory conditions, are frequently associated with immune dysregulation. This dysregulation can result in significant pathological changes within the tissue microenvironment, including abnormal inflammatory responses, biochemical and biophysical imbalances, and epigenetic modifications. Such alterations can serve as endogenous stimuli for targeted therapeutic interventions in MSDs. This review introduces the innovative concept of programmable biomaterials, which are designed to respond dynamically to specific endogenous signals within the tissue microenvironment. A comprehensive overview of the pathogenesis of several key MSDs is provided, detailing the disease-specific endogenous signals that can be exploited to enhance the functionality of programmable biomaterials. Central to the discussion is the importance of spatiotemporal immunomodulation in the treatment of various MSDs. Programmable biomaterials are categorized based on their mechanisms of endogenous responsiveness, highlighting their potential applications in clinical settings. Future directions for the design of advanced programmable biomaterials are explored, emphasizing their capacity to transform existing therapeutic strategies for MSDs. This emerging field holds great promise for improving patient outcomes by tailoring treatment approaches to the intricate biological cues present in musculoskeletal tissues. • Introduces programmable biomaterials that dynamically respond to endogenous signals in musculoskeletal disorders. • Explores the role of internal stimuli-responsive materials in modulating inflammation and promoting tissue repair. • Emphasizes the importance of spatiotemporal immunomodulation for effective therapeutic interventions in MSDs. • Discusses future directions for enhancing biomaterial design to improve patient outcomes through tailored treatments.
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Liang et al. (2026) studied this question.
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