NHGRI awards Geospiza a SBIR grant to develop software systems for detecting rare mutations

Oct 7 2009

Geospiza, Inc., the market leading developer of genetic analysis software, today announced the receipt of a Phase I SBIR grant for “Software Systems for Detecting Rare Mutations” from the National Human Genome Research Institute (1R43HG005297-01).

Specifically, this project will focus on improving methods for detecting rare mutations that define cancer types and determine how a cancer cell may grow and respond to or resist treatment. This software will not only improve cancer research and diagnostics, but will also move next generation sequencing closer to clinical applications, with general use for any application where DNA sequencing is used to understand the genetic basis of human health, disease, and response to drug therapies.

Current understanding of next generation sequencing errors and methods to completely characterize next gen datasets, with respect to their potential to deliver high quality, actionable information has progressed rapidly, but is still incomplete. Through this project, Geospiza and collaborators at leading institutions, such as the Mayo Clinic, will remove many of the obstacles that keep this vision of cancer diagnostics from becoming reality.

“This SBIR award further validates that Geospiza is working on the right kinds of problems,” said Todd Smith, Ph.D., CSO of Geospiza. “New sequencing technologies are advancing at a significant pace and the instrument vendors are making tremendous progress in developing a wide range of applications that will change how we examine gene expression and study variations in DNA sequences that cause disease and impact health.”

Smith added, “At the same time, biologists are more challenged then ever when it comes to working with the data and underutilizing these technologies outside of genome centers. In gene expression analysis, GeneSifter is a leading edge platform that eliminates bioinformatics bottlenecks. This award will help us conduct important research to develop new methods to support resequencing applications.”