Organoid models through the lens of metabolomics: a systematic review of experimental applications and analytical approaches.

Organoid models have transformed experimental biology by enabling three-dimensional systems that recapitulate tissue architecture, cellular heterogeneity, and metabolic activity patterns more faithfully than conventional in vitro cultures. In parallel, metabolomics has emerged as a systems-level approach to interrogate the biochemical processes integrating genetic programs, environmental cues, and phenotypic outcomes. Despite this promise, the application of metabolomics to organoids remains analytically fragile, challenged by low sample biomass, complex extracellular matrices, heterogeneous culture conditions, and substantial variability in experimental and computational workflows. This systematic review critically examines metabolomics and lipidomics applications across intestinal, hepatic, renal, cerebral, vascular, and tumor-derived organoids, spanning development, disease modeling, toxicology, and drug response. We synthesize how metabolic profiling provides functional insights often inaccessible to transcriptomic or morphological analyses alone. Particular emphasis is placed on analytical design and quality control, highlighting how matrix-aware strategies, normalization choices, and QC-driven preprocessing critically shape metabolite recovery, reproducibility, and biological interpretability. By comparing targeted and untargeted approaches, mass spectrometry- and NMR-based platforms, and extracellular matrix mitigation strategies, we identify recurring sources of analytical variability and interpretative bias. We further propose a minimal, context-aware QC framework tailored to the specific constraints of organoid-based metabolomics. Collectively, this work provides a critical analytical reference to strengthen reproducibility, comparability, and translational robustness in 3D organoid metabolomics.