SBIR Phase I: HEPbaseTM: Specialized Software for Storage, Retrieval and Linkage of Hepatitis Data

This Small Business Innovation Research (SBIR) Phase I project will support the development of software which will modernize the way that researchers of the hepatitis epidemic manage and analyze their data. This project will provide a solution for the hepatitis C virologist initially, and will expand to accommodate data from other hepatitis virus strains during Phase II funding and beyond. Scientists need new tools to maximize the value of their collected information. The company will develop software that contains 1) unique applications for integrating multiple sources of disparate data into an automated high-dimensional warehouse, 2) applications that perform repetitious tasks common to HCV genetic research projects, 3) tools that provide novel data annotation capabilities and ultimately new querying methods 4) a specialized alignment tool for automatic alignment of HCV protein sequences and 5) the ability to link HCV protein sequences with host microarray expression data. The result will be software that greatly improves analysis capabilities and reduces data processing time. The NSF recognizes that management and analysis of data are critical success factors. If successful the proposed solution will be marketable to hepatitis researchers worldwide in academics, biotechnology, and the pharmaceutical marketplace. The initial focus, hepatitis C (HCV) infection is a serious concern because it is distributed globally, is a chronic manifestation, and is a common co- infection with HIV. HCV infection becomes acute within 20-years post-infection; as HIV infected individuals are living longer because of better medications, HCV co-infection of the HIV patient has become a serious problem. By the year 2005, an estimated 100,000 liver transplants will be needed in the US alone. The importance of tracking the epidemic, both genetically and experimentally, is becoming increasingly important and exceedingly difficult. Understanding the genetic variation in HCV is important because it is implicated in virus-host interactions, severity of infection, sensitivity to infection, and treatment. The proposed solution will dramatically increase the efficiency and productivity of HCV researchers by providing analytical and organizational power specifically designed to address their unique needs.