We built a pipeline based on AI to minimize the time it takes to identify drugs for testing. The pipeline does this by identifying molecules which bind with specific proteins using computational biology. The pipeline then runs the results through an AI engine capable of predicting absorption, metabolism, excretion, toxicity, and distribution to identify the best candidates from over 250 Million small molecules. These molecules are then used for wet lab work to develop actual drugs. This process reduces drug identification timelines by over 50%