R01HG011799
Project Grant
Overview
Grant Description
Real-Time Genetic Diagnosis at the Point of Care - Summary
The burden on patients and caregivers when complex diseases arise creates a taxing toll for both families and healthcare systems. Multiple inpatient hospitalizations and various testing procedures often bring more unknowns and grief to an already difficult situation.
Hospital visits disrupt patient schedules and also place unnecessary burdens on a healthcare system whose purpose is to maximize the health outcomes of the patients. These complex diseases utilize extra visits and unnecessary testing. We want to develop a system that would identify patients who could benefit from accessing their existing genetic information.
Physicians may struggle to understand the correct time to order genetic testing, and with the rapid pace of change within the genetics field, many physicians are not utilizing the genetic testing that is available at an appropriate time. Genetic testing also requires hospital resources from a limited pool of workers, thus every patient that presents as a complex case may not be a suitable candidate for genetic testing.
Identifying which patients should be accessing their genetic information requires an innovative approach. At Geisinger, we have a cohort of 150,000 patients who have been sequenced and we currently have their genetic data. We propose starting with the patients' clinical presentations that are currently charted into an electronic health record to identify phenotype terms that would trigger genetic resources to be available. These genetic resources would include workflows that show optimal points of impact for the patients to improve healthcare outcomes.
To realize this vision, we have identified three areas that we would like to address. First, the identification of patients with a candidate condition in real time, followed by a concurrent bioinformatic analysis of the genomic sequence data. Finally, we want to address returning the genetic test result to the provider and patient so that both parties have the appropriate information to guide condition-specific care.
In order to address these three needs, we have developed three specific aims with the experts at Geisinger in mind for implementation.
Aim 1: Development of a High Impact Phenotype Identification System (HIPIS).
Aim 2: Develop Dynamic Virtual Genetic Panels (DVGP) for real-time genetic diagnosis.
Aim 3: Analysis of clinical workflows for optimal point of care integration of real-time genetic diagnosis.
Collaboration with Geisinger experts as well as experts in human phenotyping (Peter Robinson) will increase understanding about integrating genetic information into patient care. This transformation will allow the work of many experts in various fields to be sitting at the fingertips of primary care physicians while researching the best direction for complex diseases.
The burden on patients and caregivers when complex diseases arise creates a taxing toll for both families and healthcare systems. Multiple inpatient hospitalizations and various testing procedures often bring more unknowns and grief to an already difficult situation.
Hospital visits disrupt patient schedules and also place unnecessary burdens on a healthcare system whose purpose is to maximize the health outcomes of the patients. These complex diseases utilize extra visits and unnecessary testing. We want to develop a system that would identify patients who could benefit from accessing their existing genetic information.
Physicians may struggle to understand the correct time to order genetic testing, and with the rapid pace of change within the genetics field, many physicians are not utilizing the genetic testing that is available at an appropriate time. Genetic testing also requires hospital resources from a limited pool of workers, thus every patient that presents as a complex case may not be a suitable candidate for genetic testing.
Identifying which patients should be accessing their genetic information requires an innovative approach. At Geisinger, we have a cohort of 150,000 patients who have been sequenced and we currently have their genetic data. We propose starting with the patients' clinical presentations that are currently charted into an electronic health record to identify phenotype terms that would trigger genetic resources to be available. These genetic resources would include workflows that show optimal points of impact for the patients to improve healthcare outcomes.
To realize this vision, we have identified three areas that we would like to address. First, the identification of patients with a candidate condition in real time, followed by a concurrent bioinformatic analysis of the genomic sequence data. Finally, we want to address returning the genetic test result to the provider and patient so that both parties have the appropriate information to guide condition-specific care.
In order to address these three needs, we have developed three specific aims with the experts at Geisinger in mind for implementation.
Aim 1: Development of a High Impact Phenotype Identification System (HIPIS).
Aim 2: Develop Dynamic Virtual Genetic Panels (DVGP) for real-time genetic diagnosis.
Aim 3: Analysis of clinical workflows for optimal point of care integration of real-time genetic diagnosis.
Collaboration with Geisinger experts as well as experts in human phenotyping (Peter Robinson) will increase understanding about integrating genetic information into patient care. This transformation will allow the work of many experts in various fields to be sitting at the fingertips of primary care physicians while researching the best direction for complex diseases.
Awardee
Funding Goals
NHGRI SUPPORTS THE DEVELOPMENT OF RESOURCES AND TECHNOLOGIES THAT WILL ACCELERATE GENOME RESEARCH AND ITS APPLICATION TO HUMAN HEALTH AND GENOMIC MEDICINE. A CRITICAL PART OF THE NHGRI MISSION CONTINUES TO BE THE STUDY OF THE ETHICAL, LEGAL AND SOCIAL IMPLICATIONS (ELSI) OF GENOME RESEARCH. NHGRI ALSO SUPPORTS THE TRAINING AND CAREER DEVELOPMENT OF INVESTIGATORS AND THE DISSEMINATION OF GENOME INFORMATION TO THE PUBLIC AND TO HEALTH PROFESSIONALS. THE SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM IS USED TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, TO INCREASE SMALL BUSINESS PARTICIPATION IN FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION. THE SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM IS USED TO FOSTER SCIENTIFIC AND TECHNOLOGICAL INNOVATION THROUGH COOPERATIVE RESEARCH AND DEVELOPMENT CARRIED OUT BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO FOSTER TECHNOLOGY TRANSFER BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION.
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Danville,
Pennsylvania
178229800
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 373% from $975,703 to $4,619,886.
Geisinger Clinic was awarded
Real-Time Genetic Diagnosis for Improved Healthcare Outcomes
Project Grant R01HG011799
worth $4,619,886
from National Human Genome Research Institute in August 2021 with work to be completed primarily in Danville Pennsylvania United States.
The grant
has a duration of 4 years 9 months and
was awarded through assistance program 93.172 Human Genome Research.
The Project Grant was awarded through grant opportunity Advancing Genomic Medicine Research (Clinical Trial Optional) (R01).
Status
(Ongoing)
Last Modified 8/6/25
Period of Performance
8/10/21
Start Date
5/31/26
End Date
Funding Split
$4.6M
Federal Obligation
$0.0
Non-Federal Obligation
$4.6M
Total Obligated
Activity Timeline
Subgrant Awards
Disclosed subgrants for R01HG011799
Transaction History
Modifications to R01HG011799
Additional Detail
Award ID FAIN
R01HG011799
SAI Number
R01HG011799-106333183
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Nonprofit With 501(c)(3) IRS Status (Other Than An Institution Of Higher Education)
Awarding Office
75N400 NIH National Human Genome Research Institute
Funding Office
75N400 NIH National Human Genome Research Institute
Awardee UEI
JQH2GEMCAVN5
Awardee CAGE
3Q1X9
Performance District
PA-09
Senators
Robert Casey
John Fetterman
John Fetterman
Budget Funding
Federal Account | Budget Subfunction | Object Class | Total | Percentage |
---|---|---|---|---|
National Human Genome Research Institute, National Institutes of Health, Health and Human Services (075-0891) | Health research and training | Grants, subsidies, and contributions (41.0) | $1,838,861 | 100% |
Modified: 8/6/25