SBIR Phase I: Technical R&D for cloud-based high-information mass spectrometry data extraction commercialization

Prime Labs Inc, Greenough MT

Investigators

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to establish faster, less expensive, more accurate ways of determining the contents of biological samples leading to novel medical diagnostics, new drugs, and other new products beyond the reach of the current scientific methods that employ mass spectrometry. The project will develop technology that enables better software for mass spectrometry, and will make mass spectrometry-based sample analysis more accessible to a broader segment of academic and industrial scientists, disrupting a $100M market. Advanced software is required to transform raw experimental data into the lists of molecules and quantities needed to create new drugs, discover diseases and increase food production. The successful completion of the aims of this proposal will enable the development of software built for the next generation of mass spectrometry, providing user-friendly, fast cloud software built on advanced, high-information algorithms. This SBIR Phase I project proposes to develop novel, high-information software technology for mass spectrometry data processing. The proposed work in Phase I will provide proof-of-concept for prototype development and testing in Phase II. The research will address three critical technical hurdles that are prerequisites to prototype development: 1) A mass spectrometry data storage and retrieval architecture sufficient to handle significantly more information from the hundreds of files in a typical study, 2) cloud-optimized versions of mass spectrometry information extraction algorithms, and 3) a cloud-based model-view controller framework that overcomes web-specific challenges for mass spectrometry data processing. The goal is to allow more experiments in the same amount of time without increasing costs, identifying more molecules than existing methods from the same experiment, and detecting molecules that are less abundant and go undetected by current methods. 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.