SBIR Phase II: Developing Market-Ready Cloud-Based Software for Mass Spectrometry Data Processing

Prime Labs Inc, Greenough MT

Investigators

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to reduce the cost and increase the quality and throughput of mass spectrometry research through the development of advanced analytical software. Biomedical, biotech, agricultural, and chemical companies spend an estimated $15B per year on mass spectrometry because of the commercial value its measurements provide across a broad range of products and services. This value is highly dependent upon the quality of the software needed to render the experimental output into usable information. The successful completion of the proposed research will enable advancements in existing markets through faster, less expensive, and more accurate data processing, leading to novel medical diagnostics, new drugs, and other new products beyond the reach of the current state-of-the-art. This SBIR Phase II project will address the most pressing problems in mass spectrometry by developing analytical software that is improved in two ways: 1) it will cut user analysis time in half through readily customizable automation, interactive hypothesis testing, and fast intuitive interfaces, and 2) it will answer more experimental questions through flexible interfaces that allow users to leverage their domain expertise while intuitively exploring their data. These qualities require leveraging the proof-of-concept achieved in Phase I, where a cloud architecture was developed, onto novel interfaces and algorithms to be developed in Phase II. The principle project goals are to develop an application that allows users to more quickly complete both repetitive (through automation) and custom (through intuitive, flexible exploratory tools) analysis in half the time required by present methods. The time savings will result in much lower personnel cost while simultaneously increasing the number and type of experimental questions that can be answered compared to existing software. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.