A technology developed by a team of researchers from Wayne State University and its biotech startup Advaita Bioinformatics makes it possible to distinguish between aggressive and less aggressive types of disease. Partially funded by a grant from the National Science Foundation and the Robert J. Sokol MD Endowment, this research combines multiple types of data in a single analysis to ultimately reduce the number of patients who do not receive necessary treatments, while also avoiding unnecessary treatments.

WSU’s research was sparked by a 2012 report by The New York Times, which revealed that over the past 30 years, more than 1.4 million women have unnecessarily undergone surgery, chemotherapy or radiation. These treatments cost nearly $23,000 per patient, resulting in a societal cost of $32.2 billion, while there are still patients who may relapse and die because they do not receive necessary treatments.

“It’s critically important that we align each subtype of disease with the appropriate treatment,” said lead researcher Sorin Drăghici, professor of computer science, associate dean for innovation and entrepreneurship, and director of the James and Patricia Anderson Engineering Ventures Institute. “Patients who really need an aggressive treatment will be identified early and treated aggressively, while patients who do not need such treatments will be spared the suffering and cost, for a total savings to the society estimated in tens of billions [of dollars].”

Drăghici added that Wayne State’s technology can also be used by pharmaceutical companies to distinguish between patients who will and will not respond to a given drug, thus increasing the success of clinical trials and allowing more drugs to reach the market. The framework has been validated on thousands of cancer samples using gene expression, DNA methylation, non-coding microRNA and copy number variation data available from the Gene Expression Omnibus, the Broad Institute, The Cancer Genome Atlas and the European Genome-phenome Archive.