SBIR Phase II: Rapid Pathogen Diagnostics and Biosurveillance using Multiplexed High-throughput Sequencing

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The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve our ability to fight infectious diseases that negatively impact agricultural yields and reduce the efficiency of global food production and distribution systems. This innovation will enhance scientific and technological understanding by leveraging the power of high-throughput sequencing and bioinformatics to provide a pathogen identification and surveillance tool with demonstrated efficacy against known and unknown infectious agents. This platform is fast, sensitive, and cost-effective, and can be used for any animal sample to detect virtually all possible microbes even microbes that have never before been characterized. Hundreds of samples can be rapidly screened without relying upon known genetic/genomic data of microbes. The global molecular diagnostics market is expected to grow at a compound annual growth rate (CAGR) of over 14% from 2012 to 2017, with infectious disease testing being the leading application at 26% share, therefore the commercial opportunity of this project is vast.The proposed project follows up on the validation of the diagnostic platform (SBIR Phase I) and delves deeper into improving virus detection and genetic data generation. In addition, this proposal seeks to develop a basal informatics infrastructure that together with sample preparation improvements will be conducive of scalable, high-throughput analysis of several samples. Current diagnostic methods rely on what is already known about target microbe genetics, and provide limited information in the form of presence/absence of a known target sequence. The SBIR Phase I was instrumental to lowering the technical risks associated with a high-throughput unbiased pathogen detection platform based on DNA sequencing and Bayesian statistics. In the pursue of standardizing and validating our metagenomics pathogen identification platform, this project proposes to: 1) improve viral detection capabilities and accuracy, 2) develop new functionalities, and 3) incorporate Phase I and Phase II advances into an integrated in-house web-accessible interface.