Case Western Reserve University and NeoProteomics Inc. have announced the university's licensing of four software programs designed to improve understanding of biology at a complex molecular level for improved treatment of cancers and various other diseases.
NeoProteomics, a developer and distributor of novel bioinformatics software products, was founded in 2006 as a research spin-off from Case Western Reserve's School of Medicine. The company, with offices in Cleveland, focuses on protein biomarker identification and validation and seeks development of unique and improved analysis tools. Proteomics is an increasingly vital part of research involving the amounts and structures of protein in biological systems.
NeoProteomics has also won a Small Business Innovation Research (SBIR) grant from the National Institutes of Health to further develop the licensed software for commercially viable applications. The SBIR award, $300,000 over two years, will cover a significant portion of the development costs.
"These two milestones represent goals the company has been working on for quite some time," said John L.H. Schenkel Jr., NeoProteomics president and chief executive officer. "We are grateful for and appreciate CWRU's partnership and look forward to developing products and services which will have significant impact in disease research across the global research-and-development community."
Mark R. Chance, NeoProteomics co-founder and chief scientific officer, said the licensing agreement recognizes proliferation of computational sciences in the medical field. He said the NIH and the research community is recognizing the importance of the licensed software.
Chance is interim chair of the Department of Genetics at Case Western Reserve's School of Medicine. He is a professor within the Department of General Medical Sciences and directs the Center for Proteomics and Bioinformatics (http://proteomics.case.edu/).
"The new fields of systems biology and bioinformatics are growing rapidly, as we have to deal with more data of greater complexity," Chance said. "In the future, the use of novel software tools is going to be more integral in the lab as well as clinical settings. We are just beginning to discover how important software is to the detection and cure of human disease."
Research teams internationally partner with NeoProteomics to develop and discover new biomarkers for disease, validate existing biomarkers for clinical relevance, gain a better understanding of the functional interaction of disease proteins, analyze experimental data to drive results, and design experiments.
"NeoProteomics will use the license, which includes computer code developed at CWRU, to make a set of products that help diagnose disease, predict progression of disease, and predict response to treatment of disease," Chance said.
NeoProteomics (http://www.neoproteomics.net/) was founded by Chance, Schenkel and Steven Chance. Rod Nibbe has recently joined the executive team as director of product development and senior scientist.
"Understanding the molecular mechanisms of complex biology inherent to many cancers and other diseases, such as Alzheimer's, and the related efforts to discover new drug targets are time consuming and expensive," said Nibbe, who serves as principal investigator for the SBIR grant. "Our software is intended to help academic and industrial researchers unravel the biological complexity, and by doing so lower the cost and shorten the time to development of new therapeutic agents."
The license agreement is for 20 years. NeoProteomics controls exclusively distribution of the licensed Case Western Reserve technology. The university, in lieu of payment, receives a 15 percent share in the company, which will pay a royalty to Case Western Reserve for every sale. Schenkel said royalty payments vary and are dependent upon the transaction type.
Schenkel expects that the company, with the benefit of the licensing agreement, will see significant growth.
Mark Chance said the software licensed to the company is an example of personalized medicine and permits an analysis of genetic and proteomic data from a patient that specifically can indicate risk of a disease progressing or whether the patient will respond well to a particular course of treatment. Such crucial information can help with clinical trials.
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