Helena Castañé, Celina Spangenberger, Isisdoris Rodrigues de Souza, Theodora Kristoforus, Lisa Lazarevski, John Yim, Madalena Cipriano, Sara Toftegaard Hjuler, Abdulkadir Ozkan, Timothy Petrie, Qianru Jin, Peter Loskill
Adipose tissue is increasingly recognised as a central regulator of systemic metabolism. Beyond energy storage, adipose tissue integrates nutrient sensing, endocrine signalling, and immune responses, and actively communicates with other organs to coordinate metabolic homeostasis. This functional complexity arises from the coordinated activity of adipocytes and stromal cells, whose interactions dynamically regulate both physiological and pathological states. Most in vitro experimental models used in drug development and mechanistic research have simplified this complexity, whereas in vivo models integrate systemic physiology but lack human specificity. This mismatch limits the ability to predict adipose-specific drug effects, particularly for compounds targeting metabolic pathways, inflammation, or inter-organ signalling. In pharmacological contexts this limitation is particularly relevant because adipose tissue not only acts as a therapeutic target but also influences drug distribution, bioavailability, and efficacy through lipid partitioning, endocrine signalling, and immune modulation. Models that fail to capture these features risk overlooking key mechanisms of action or mispredicting therapeutic outcomes. Microphysiological systems that reconstruct adipose tissue complexity offer a framework to bridge this gap. By integrating multiple adipose-relevant cell types, such as mature adipocytes and stromal vascular fraction cells, along with physiological perfusion and controllable microenvironments, these systems could help address how cell-cell interactions shape metabolic function and pharmacological responses. As such, they represent a translational platform to interrogate drug mechanisms, evaluate tissue-specific efficacy, and could become tools to predict systemic pharmacological effects in metabolically relevant human settings.