Alzheimer’s disease is an incurable disorder that causes brain cells to gradually deteriorate and die, leading to severe dementia. The condition is hypothesized to be driven by the accumulation of amyloid-beta plaques and tau protein tangles at synapses and axons in neurons. This project, created by Ratan Shankar (Grade 12, Greenwood High,Bangalore, India) and Sripad Sureshbabu (San Jose, California), first used a machine learning linear regression model to identify key volumetric changes in the brain during Alzheimer’s disease development. This was paired with a computational model that demonstrated the activity of both tau and amyloid proteins on a 100x100x100 matrix of cells using protein modeling equations derived from 8 clinical studies. When tested, it had >90% correlation with clinical data, indicating that it is an accurate predictor for Alzheimer’s development. The model was then presented at the Boston University Poster Symposium held on August 9th, 2019.