I-Corps: A data capture and management technology to transform data access, structure, and security

Information

  • NSF Award
  • 2017857
Owner
  • Award Id
    2017857
  • Award Effective Date
    5/15/2020 - 4 years ago
  • Award Expiration Date
    10/31/2020 - 4 years ago
  • Award Amount
    $ 50,000.00
  • Award Instrument
    Standard Grant

I-Corps: A data capture and management technology to transform data access, structure, and security

The broader impact/commercial potential of this I-Corps project investigates applications of technologies describing health and wellness data. Researchers conducting clinical trials can use this technology to capture real-world patient data and streamline large-scale late phase trials, accelerating the development of new pharmaceuticals and treatment modalities. Life scientists could use this technology to accelerate basic science discovery and facilitate translation of these findings from the bench to bedside. Human resources personnel could better track, manage, and act on data generated in employee wellness programming toward fewer sick days, more productivity, and higher employee satisfaction. Health program coordinators could potentially facilitate public health interventions and perform research. Care managers and clinicians could deploy and manage remote management services to chronic disease populations, preventing unnecessary hospitalizations, improving health outcomes, and lowering the cost of care management. <br/><br/>This I-Corps project explores the trade space of a data capture and management technology to transform data access, structure, and security. This technology consists of several core components, including (1) A universal wrapper application program interface (API) that scales with existing and future hardware, software, and other data sources; (2) A data normalization algorithm and entity relationship model to structure data and affiliate it with the data source; (3) Security and privacy controls to protect data source privacy and end-user regulatory compliance; (4) Machine learning and predictive analytics using data in different modalities to translate data into actionable insights for a variety of commercial uses.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

  • Program Officer
    Ruth Shuman
  • Min Amd Letter Date
    5/8/2020 - 4 years ago
  • Max Amd Letter Date
    5/8/2020 - 4 years ago
  • ARRA Amount

Institutions

  • Name
    University of Scranton
  • City
    Scranton
  • State
    PA
  • Country
    United States
  • Address
    800 Linden Street
  • Postal Code
    185102429
  • Phone Number
    5709416362

Investigators

  • First Name
    Ahmed
  • Last Name
    Gomaa
  • Email Address
    ahmed.gomaa@scranton.edu
  • Start Date
    5/8/2020 12:00:00 AM

Program Element

  • Text
    I-Corps
  • Code
    8023