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Computational Software Development to Advance Translational Research for Infectious Diseases

Description:

Fast-Track proposals will be accepted. Number of anticipated awards: 3-4 Budget (total costs):
Phase I: $225,000 for up to 1 year
Phase II: $1,500,000 for up to 3 years
Background
There is a critical need to develop new and improved vaccines and therapeutics for high priority pathogens such as influenza, Mycobacterium tuberculosis (Mtb), and HIV. Research investments in sequencing these pathogens have resulted in an explosion of publicly available genomic data, creating a need for intuitive and efficient software tools to analyze massive amounts of data and enable prediction and/or identification of new targets and control strategies for treatment and prevention. This solicitation will support software development in two specific and separate areas (one area per proposal):
1.
Non-Coding RNA: Although non-coding RNAs (ncRNAs) have been identified as promising biomarkers and therapeutic targets for a number of human diseases, translational efforts in the infectious disease field are largely lacking. A critical barrier to translation is our lack of understanding of the functional roles of ncRNAs in infectious disease. The development of software packages to analyze existing ncRNA data sets will assist researchers in

identifying the most promising ncRNAs for future mechanistic studies, helping to overcome this barrier and move the field forward from discovery to translation.
2.
Influenza vaccines: Public databases now contain genomic sequences for tens of thousands of influenza viruses as well as associated in vitro, in vivo, and in some cases clinical data. Engaging the software industry in the development of predictive software linking genetic sequencing information with other types of data such as antigenicity, protein structure, viral fitness and/or vaccine efficacy, is anticipated to bring a new dimension to the annual influenza vaccine strain selection process and vaccine development, decreasing the likelihood of vaccine strain mismatch and leading to more effective influenza vaccines.
Project Goal
The goal of this project is the development of computational software that provides sensitive tools to enable translational research on high priority infectious disease pathogens by analyzing massive amounts of existing data. Use of novel cognitive computational strategies that combine large complex data sets and machine learning algorithms is encouraged to translate information into knowledge that can help drive more informed decision-making. The scope of software development is limited to two priority areas:
 Analyzing large-scale ncRNA data to identify expression patterns associated with influenza, Mtb, or HIV infection and/or disease progression to guide future mechanistic and translational studies (e.g., algorithms/analytics that enable target prediction/identification, structure analysis, functionality determination, quantification of ncRNA expression levels, etc.).
 Predicting influenza virus evolution to improve vaccine strain selection and vaccine efficacy.
Phase I activities can include but are not limited to:
 Develop a functional software prototype.
 Demonstrate capability of the software to: (1) analyze large-scale ncRNA data to identify expression patterns associated with influenza, Mtb, or HIV infection and/or disease progression (Area 1); or (2) link influenza genetic sequencing information with other types of data such as antigenicity, protein structure, viral fitness and/or vaccine efficacy to predict influenza virus evolution and improve vaccine strain selection and vaccine efficacy (Area 2).
Phase II activities can include but are not limited to:
 Evaluate, revise, and enhance the software prototype.
 Perform beta testing of the software with relevant end users.
 Incorporate user feedback from beta tests.
 Develop user support and instructional guides to facilitate commercialization.
This SBIR will not support:
 The design and conduct of clinical trials (see http://www.niaid.nih.gov/researchfunding/glossary/pages/c.aspx#clintrial for the NIH definition of a clinical trial). For clinical trial support, please refer to the NIAID SBIR Phase II Clinical Trial Implementation Cooperative Agreement program announcement or the NIAID Investigator-Initiated Clinical Trial Resources webpage.
 Use of novel or non-publicly available datasets to develop and demonstrate the utility of the computational software and tools.

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