NIH awards Geospiza phase II SBIR grant to develop new DNA variant application for GeneSifter platform

Geospiza, Inc. the market leading developer of the GeneSifter® software platform for genetic analysis, today announced that the National Human Genome Research Institute of the National Institutes of Health has awarded the company a phase II SBIR grant to collaborate with researchers at Weil Cornell Medical College, Mayo Clinic to develop a new application that quickly identifies and visualizes DNA sequence variations found when comparing normal and cancer tissues using Geospiza's GeneSifter cloud computing platform.

“The new sequencing technologies are letting us probe cancer biology in ways we've never contemplated before”

"Through this funding, we will be able to attack the biggest challenges researchers face when attempting to develop cancer tests," explains Todd Smith, Geospiza's Chief Technology Officer. "There are substantial DNA variations between normal and cancer tissue. Researchers wanting to develop a new cancer test need to figure out those differences and put them in a biological context. This process requires easy to use visual presentation of millions of data points to see those differences. GeneSifter is the ideal platform to deliver this exciting new application."

Christopher Mason, assistant professor at Weil Cornell Medical College in New York, New York said, "I am thrilled to be participating in this important work. For several years I have been working with the new DNA sequencing technologies to understand the genetic basis of gene expression and to discern the mutational dynamics of a single person's genome during disease." Mason continues, "In my opinion, integrating high-quality data from different assays with public information in ways that can add biological context is the next frontier in genetics and genomics research, and essential for clinical applications."

"The new sequencing technologies are letting us probe cancer biology in ways we've never contemplated before," adds David Smith, Professor at the Mayo Clinic in Rochester Minnesota. "It's clear that the next generation of diagnostic tests can only be made by effectively combining whole transcriptome analysis with genome sequences on a per patient per sample basis. The numbers of combinations are daunting. The application developed through this work will be well suited for translating research observations to actionable clinical tests."