AUTHOR=Huff Lindsey K. , Amurgis Charles M. , Kokai Lauren E. , Abbott Rosalyn D. TITLE=Optimization and validation of a fat-on-a-chip model for non-invasive therapeutic drug discovery JOURNAL=Frontiers in Bioengineering and Biotechnology VOLUME=Volume 12 - 2024 YEAR=2024 URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2024.1404327 DOI=10.3389/fbioe.2024.1404327 ISSN=2296-4185 ABSTRACT=Obesity is a significant public health concern that is closely associated with various comorbidities such as heart disease, stroke, type II diabetes (T2D), and certain cancers. Due to the central role of adipose tissue in many disease etiologies and the pervasive nature in the body, engineered adipose tissue models are essential for drug discovery and studying, disease progression, and personalized medicine. Additionally, patient demographics such as age, gender, ethnicity, and medical history are known to affect the phenotype and behavior of adipose tissue. This study validates a fat-on-a-chip (FOAC) n engineered adipose tissue model that can account for patient specificderived from primary mature adipocytes adipose tissue responses using an organ-on-a-chip (OOC) platform. Our fat-on-achip (FOAC) model uses mature human adipose tissue in a Micronit perfusion device and introduces a novel approach for collecting continuous data for FOAC models by using two non-invasive readout techniques, resazurin and glucose uptake. The Micronit platform proved to be a reproducible model that can effectively maintain adipocyte viability, metabolic activity, and basic functionality, and is capable of mimicking physiologically relevant responses such as adipocyte hypertrophy and insulinmediated glucose uptake. Importantly, we demonstrate that adipocyte size is highly dependent on extracellular matrix properties, as adipocytes derived from different patients with variable starting lipid areas equilibrate to the same size in the hyaluronic acid hydrogel. This model can be used to study T2D and allow for monitoring of adipocyte responses to insulin for longitudinally tracking drug efficacy and assessing therapeutic efficacy of novel drugs or drug combinations in patient specific adipose models.