Metabolism is the only biological system that can be fully modeled at genome-14 scale. As a result, metabolic models have been increasingly used to study the 15 molecular mechanisms of various diseases. Hypoxia, a low-oxygen tension, is 16 a well-known characteristic of many cancer cells. Pyruvate dehydrogenase 17 controls the flux of metabolites between glycolysis and the tricarboxylic acid 18 cycle and is a key enzyme in metabolic reprogramming in cancer metabolism. 19 Here, we develop and manually curate a constraint-based metabolic model to 20 investigate the mechanism of pyruvate dehydrogenase under hypoxia. Our 21 results characterize the activity of pyruvate dehydrogenase and its decline 22 during hypoxia. This results in lactate accumulation, consistent with recent 23 hypoxia studies and a well-known feature in cancer metabolism. We apply 24 machine-learning techniques on the flux datasets to identify reactions that 25 drive variations. We also identify distinct features on the structure of the 26 variable and individual components. Our results provide a framework for 27 future studies by integrating multi-omics data to predict condition-specific 28 metabolic phenotypes under hypoxia.