SBIR Phase I: A Learning Drug Discovery Platform in the Cloud

This Small Business Innovation Research (SBIR) Phase I project proposes to develop a web-based learning software platform for collaborative drug discovery and optimization. Current drug discovery software tools do not support the sophisticated data management that is needed for iterative and adaptive drug discovery, learning, and collaboration. This project aims to change this by building a web-based drug discovery platform with three main objectives: (1) provide novel insightful graphical feedback on binding properties, (2) provide simple virtual screening over millions of vendor compounds, and (3) keep track of past assay results in order to iteratively refine prediction models and to continuously improve accuracy. The challenges in this project include (1) scalable data management to support hundreds of users and large numbers of compounds and models, (2) data encryption for the protection of proprietary information, and (3) a simple pharmacologist-oriented user interface. The outcome of the project will be a web-based tool that can be used across pharma/biotech research groups and across labs for effective collaborative drug discovery and optimization. The broader impact/commercial potential of this project, if successful, will be the potential for novel visualizations that will significantly improve the understanding of molecular binding properties. It will result in novel data mining and analysis algorithms that can operate directly on encrypted data, with far-reaching impact on other areas that require data safe-keeping (e.g., electronic health record management). In addition, the project will offer insights into interface design for pharmacologists, biologists, and chemists and how to better foster collaboration among them. On a larger scale, the project will aid in the discovery of novel leads for pressing healthcare needs. Especially for difficult drug targets without much structural information, such as Alzheimer's disease targets or cancer targets, the proposed platform can identify novel drug-leads with fewer side effects and higher efficacy. This ultimately may result in a much faster time-to-market for such drugs. For pharma/biotech companies using the platform developed in this project, this could mean a significant commercial advantage.