Cryptosporidium parasites inflict a major health burden as a leading cause of diarrheal disease. Unfortunately, there are no effective therapeutics for vulnerable patients, like children. I use a combined computational and experimental approach to identify drug targets shared by all human pathogenic Cryptosporidium species. Specifically, I use genome-scale metabolic network models, clinical data, and multiple experimental systems to identify metabolic enzymes that are essential for parasite survival. This project is funded by a seed grant from the University’s Engineering-in-Medicine program.