Visually driven disease variant analysis empowering real time clinical research

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R41HG009629-01
Agency Tracking Number: R41HG009629
Amount: $256,443.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: NHGRI
Solicitation Number: PA16-303
Solicitation Year: 2016
Award Year: 2017
Award Start Date (Proposal Award Date): 2017-09-04
Award End Date (Contract End Date): 2019-02-28
Small Business Information
724 E 4TH AVE, Salt Lake City, UT, 84103-3444
DUNS: 079748783
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 (617) 319-1357
Business Contact
Phone: (617) 319-1357
Research Institution
 75 SOUTH 2000 EAST
SALT LAKE CITY, UT, 84112-8930
 Nonprofit college or university
Project Summary Identifying disease causing genetic variants is a complex process that requires experts from multiple fields including bioinformatics IT systems administration and disease pathology to work closely together The size of sequencing data files also adds the requirement for large computational resources As a result performing genomic analyses is an expensive and lengthy process and is only fully adopted in large research institutions This proposal aims to simplify this process enabling medical professionals including genetic counselors physicians and diagnostic clinicians to perform powerful analyses quickly and on their own laptop The proposed product will be an intuitive web based app built on a cloud infrastructure that will direct an analyst through a predefined state of the art analysis pipeline Intelligent quality control will be performed on all input data to ensure that the conclusions reached are valid and comprehensive The product will be built on the IOBIO platform that has been developed by the applicant team Currently available apps built on this platform perform analysis in real time using visualizations to drive the analysis and are already popular in the community indeed they have been integrated into a number of large public projects to solve data visualization problems These IOBIO apps will be expanded providing new features necessary for clinical use and consolidated into a single living report from which the entire analysis will be performed shared and managed Core IOBIO infrastructure will be improved for commercial deployment including support for massively parallel processing on the cloud maintaining real time analysis across large data sets The objective of this proposal is to develop a commercially viable product to significantly decrease the cost and expertize burden associated with clinical genomic analysis This will ultimately result in an increase in the number of diagnosed patients and help minimize the diagnostic odyssey that they can often undergo Project narrative Diagnosing sick patients using DNA sequencing data is a complex and costly process requiring experts from many disparate fields including computer science bioinformatics and varied medical and biological disciplines This project will develop a web based intuitive application to put analysis in the hands of medical experts significantly reducing the cost of analysis and increasing the rate at which DNA information can be used to diagnose diseases

* Information listed above is at the time of submission. *

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