This document discusses how the Discovery Bus manages the QSAR process by applying different modelling approaches and algorithms to generate many model paths from data in an automated way. It handles tasks like selecting descriptors, splitting data, building models using methods like linear regression and neural networks, and adding results to a database. This allows industrial-scale QSAR to be performed by generating over 750,000 models from 10,000 datasets in 3 weeks using cloud computing resources. The goal of the Discovery Bus is to significantly improve drug discovery productivity by performing the work independently without human involvement.