SBIR Phase I: Semantic Link Association Prediction for Phenotypic Drug Discovery

Data2discovery Inc, Bloomington IN

Investigators

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is the development of a first-in-class Predictive Phenotypic Profiler (PPP) software tool that will improve the efficiency and effectiveness of the pre-clinical drug discovery process. A recent study of drugs approved by the FDA between 1998 and 2008 shows that a majority of first-in-class drugs are now derived from phenotypic screens rather than traditional target-based screens. However, there is currently a severe lack of computational and data tools that can bridge the vast amounts of traditional molecular-based data with the equally vast amounts of phenotypic data now being generated. The PPP tool integrates and interprets this complex and multi-faceted data to greatly enhance the ability of pharmaceutical companies to find new and effective drugs. The estimated cost per new prescription drug approval is $2.56 billion - the economic impact of reducing the pre-clinical drug discovery process by just one week is estimated to result in a $108 million cost savings for the pharmaceutical industry, creating a large financial opportunity. This tool aims to enhance the number and quality of drugs that enter clinical trials, resulting in more economically priced medicines available to the population. This SBIR Phase I project proposes to develop a proof-of-concept PPP software tool that brings together a variety of publicly available molecular and phenotypic data sources into a graphical user interface, allowing for the discovery of novel mechanisms of action, and the identification of target(s) from phenotypic assays. The major hurdles of this project will be the integration of these highly heterogeneous datasets and the identification of evidence based path patterns. Semantic technologies and domain expertise will be applied to this application to surmount these data integration and prediction challenges. The plan to reach the goal of a prototype PPP tool includes: 1) Creating a semantic graph for phenotypic data sources, 2) finding evidence-based path patterns in phenotypic data, 3) applying predictive algorithms for phenotypic data analysis, and 4) developing a graphical user interface for evaluation and verification. Phase I success will result in a tool that can be used by pharmaceutical companies for evaluation and product feedback.