Organoids are three-dimensional (3D) miniature tissue structures that recapitulate organ developmental processes and bio-functions in vitro , while significantly reducing the costs of traditional animal experiments. Organoids are serving as a promising platform for drug screening, toxicity testing, and personalized medicine. Matrigel, a biomaterial derived from mouse tumors, has long been used as a conventional substrate for organoid culture. However, its ill-defined composition, batch-to-batch variability, and inability to reconstruct tissue-specific microenvironment, compounded by manual operations of traditional Matrigel-based protocols, have severely limited the physiological relevance, reproducibility, and scalable production of organoids. Other bulk hydrogel alternatives with defined chemical composition and structure, similarly struggle with limited mass transport and inadequate space for organoid growth. As defined alternatives, microgels, beyond inheriting the favorable properties of bulk hydrogel, offer the additional advantages of particulate materials including tunable size, designable mechanical properties, customizable functionality, and high-throughput production, which are emerging as ideal alternative matrices for organoid culture. To date, increasingly microgel-based strategies for organoid construction have been developed by either optimizing microgel materials (e.g., loading signaling factors, tuning mechanical properties) or improving organoid preparation methods (e.g., combining microfluidic technology or 3D bio-printing). In this review, we outline the microgel-based organoid methodologies reported in recent years and systematically summarize them into four core demands confronting traditional Matrigel-dominated bulk hydrogel approaches: (i) precise regulation of biochemical signals; (ii) proper matching of mechanical properties; (iii) recapitulation of tissue-specific microenvironments; (iv) normalized and scalable fabrication of organoids.
No takes yet. Share an insight, caveat, or question.
Jian et al. (2026) studied this question.