Brain organoids represent a promising technology in neurosciences, due to their capability of resembling salient human brain structural and functional features in vitro. For this reason, they are successfully employed for gaining hitherto insights in human brain. Several brain pathologies – among all, Parkinson’s Disease - are linked to metabolic alterations. However, the ground truth for measuring metabolism in vitro - i.e., platforms such as the Seahorse Analyzer - monitors nutrient consumption at a bulk level, without locally mapping concentration changes. This approach cannot provide an exhaustive metabolic characterization of 3D cellular constructs (e.g., organoids), whose metabolism is known to be driven by spatial chemical gradients. In this context, the aim of our study was to establish a pipeline for rigorously characterizing brain organoid metabolism. To this end, oxygen concentration on the surface and in the inner core of brain organoids was locally recorded over time until the steady state was reached, using commercial needle-type sensors based on oxygen quenching. A previously developed algorithm was then purposely customized for estimating the construct metabolism from this concentration difference, defined as its stationary oxygen consumption rate. The developed pipeline was tested on brain organoids derived from human pluripotent stem cells of healthy donors. Future developments will include the use of the pipeline to measure the metabolism of organoids derived from patients affected by neuropathies characterized by metabolic dysfunctions (e.g., Parkinson’s disease), to better characterize the pathologic mechanisms underlying the disease evolution.