Monday, May 23, 2022 5/23/2022

Leveraging Artificial Intelligence Solutions to Develop Digital Biomarkers for Precision Trauma Resuscitation

Award Number: R01HL149670
ORGANIZATION: NATIONAL HEART, LUNG, & BLOOD INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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PROJECT SUMMARY / ABSTRACT In the U.S., trauma is the leading cause of death for those 1-45 years old and hemorrhage remains the largest contributing factor to preventable death. Providers must rapidly identify those suffering from hemorrhage to optimize outcome, but internal bleeding remains difficult to diagnose even for experienced clinicians. Little is known on presentation about those suffering from occult hemorrhage and providers must quickly make treatment decisions in these time-pressured, time-sensitive clinical scenarios. This proposal seeks to develop through artificial intelligence, a type of advanced machine learning, prediction algorithms that could be deployed at the bedside of patients to assist clinicians with more timely recognition of hemorrhage. By doing so, we hypothesize that this approach (integrating diverse data sources that have not previously been combined to one another) could identify patterns in our patients that far surpass current capabilities to quickly detect and act on the critical components contributing to outcome. The ability to rapidly pinpoint these patterns and display them to the bedside clinician could allow more timely intervention and precise therapeutic approaches for hemorrhage control. Beyond the challenges in rapidly identifying bleeding, current treatment of hemorrhage is rudimentary with a standard resuscitation approach for all patients. This reflects attempts to optimize outcome based upon the average treatment effect, rather than being adaptable for unique patient phenotypes. Hemorrhage is believed to initiate a complex chain of events involving crosstalk between the coagulation and inflammatory systems that are hypothesized to play a key role in outcome. Trauma has a known time zero of onset, making it an ideal model to study the immediate pathophysiologic changes associated with hemorrhage. This complex, individual patient biology is believed to explain why those suffering similar injury have differing outcomes. However, to date, these individual characteristics are poorly understood and not factored into initial treatment approaches. Through this proposal, I also seek to define novel digital biomarkers representing patient phenotypes that require precision resuscitation approaches to maximize outcome. Fundamental to reducing hemorrhagic deaths is the need to elucidate a deeper understanding of these mechanistic models of patient states. Strategies that help to identify novel patient phenotypes that could benefit from more tailored treatment pathways may provide important advances in decreasing preventable death. The net result of this proposal will be a deeper insight into the mechanistic models contributing to evolving patient states following hemorrhage, and identify the key phenotypes or digital biomarkers associated with mortality, complications, and occult hemorrhage. Finding solutions to advance our resuscitation approaches following hemorrhage has potential to decrease complications, save lives, and reduce health care costs.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2022 ( Subtotal = $772,158 )
2022	2022	UNIVERSITY OF CALIFORNIA, DAVIS	1850 RESEARCH PARK DR, STE 300	DAVIS	CA	95618	YOLO	USA	Blood Diseases and Resources Research	001	4	1/14/2022	NON-COMPETING CONTINUATION	$694,906
2022	2021	UNIVERSITY OF CALIFORNIA, DAVIS	1850 RESEARCH PARK DR, STE 300	DAVIS	CA	95618	YOLO	USA	Blood Diseases and Resources Research	000	3	1/13/2022	NON-COMPETING CONTINUATION	$77,252


Issue Date FY: 2021 ( Subtotal = $695,258 )
2021	2021	UNIVERSITY OF CALIFORNIA, DAVIS	1850 RESEARCH PARK DR, STE 300	DAVIS	CA	95618	YOLO	USA	Blood Diseases and Resources Research	000	3	11/25/2020	NON-COMPETING CONTINUATION	$695,258
2021	2021	UNIVERSITY OF CALIFORNIA, DAVIS	1850 RESEARCH PARK DR, STE 300	DAVIS	CA	95618	YOLO	USA	Blood Diseases and Resources Research	002	3	7/15/2021	NON-COMPETING CONTINUATION	$17,591
2021	2020	REGENTS OF THE UNIVERSITY OF CALIFORNIA, SAN FRANCISCO, THE	1855 FOLSOM ST STE 425	SAN FRANCISCO	CA	94143	SAN FRANCISCO	USA	Blood Diseases and Resources Research	001	1	7/15/2021	NEW	-$17,591


Issue Date FY: 2020 ( Subtotal = $790,053 )
2020	2020	REGENTS OF THE UNIVERSITY OF CALIFORNIA, SAN FRANCISCO, THE	1855 FOLSOM ST STE 425	SAN FRANCISCO	CA	94143	SAN FRANCISCO	USA	Blood Diseases and Resources Research	000	1	11/27/2019	NEW	$790,053
2020	2020	REGENTS OF THE UNIVERSITY OF CALIFORNIA, SAN FRANCISCO, THE	1855 FOLSOM ST STE 425	SAN FRANCISCO	CA	94143	SAN FRANCISCO	USA	Blood Diseases and Resources Research	001	1	6/30/2020	NEW	-$772,462
2020	2020	UNIVERSITY OF CALIFORNIA, DAVIS	1850 RESEARCH PARK DR, STE 300	DAVIS	CA	95618	YOLO	USA	Blood Diseases and Resources Research	002	2	6/30/2020	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$772,462


Grand Total All Awards = $2,257,469

Sum of Action Amount is $2,257,469;

Grand Total = $2,257,469

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Leveraging Artificial Intelligence Solutions to Develop Digital Biomarkers for Precision Trauma Resuscitation

Award Number: R01HL149670

ORGANIZATION: NATIONAL HEART, LUNG, & BLOOD INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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