University of Southern California

Research

RFA-AR-19-027: HEAL Initiative: Back Pain Consortium (BACPAC) Research Program Data Integration, Algorithm Development and Operations Management Center (U24 Clinical Trial Not Allowed)

Slots:                                                     1                             

Internal Deadline:                           Contact the Office of Research if interested.

LOI:                                                        February 20, 2019           

External Deadline:                          March 20, 2019, 5pm PT

Award Information:                        Type: Cooperative Agreement

Estimated Number of Awards: 1 – 2

Anticipated Amount: up to $6 million

Cost Sharing:                                     For grantees from a for-profit organization, this FOA does require cost sharing, as defined in the NIH Grants Policy Statement.  More information on cost matching requirements is in Section IV.2 R&R or Modular Budget

Submission Process:                     PIs must submit their application as a Limited Submission through the Office of Research Application Portal: https://app.wizehive.com/webform/USCgrants

Materials to submit:

Link to Award:                                  https://grants.nih.gov/grants/guide/rfa-files/RFA-AR-19-027.html  

Who May Serve as PI:                    Standard NIH eligibility requirements.

Purpose:

The BACPAC Research Program consists of four primary components that will work collaboratively to achieve the overarching goals. This call refers to a Data Integration, Algorithm Development and Operations Management Center (DAC). This Center will guide and coordinate all activities of the consortium and ensure communications, interactions, synergies and accountability. It will manage a core as a Consortium-wide registry, including patient reported outcomes and preferences. The DAC will include the BACPAC Systems Biology and Bioinformatics Group (SBG) to provide system level analysis for BACPAC generated multidimensional datasets to produce an integrated model of LBP. Using data from clinical studies across the Consortium, this Center will develop patient-centered algorithms for prediction of optimized therapeutic interventions.

Areas of responsibility include:

  1. Clinical Registry, Data Integration and Coordination

Areas of responsibility include:

  1. Algorithm Development, Testing and Validation

The DAC will conduct de novo modeling, using systems and machine learning approaches to improve current diagnostic and treatment algorithms. Areas of responsibility include:

  1. Operations Management

Areas of responsibility include:

Visit our Institutionally Limited Submission webpage for updates and other announcements.