← Leaderboards
Christopher Warren Seymour
University Of Pittsburgh At Pittsburgh
$6,573,754
Attributed
$7,970,031
Total exposure
5
Grants
3
Lead (contact PI)
Attributed= this PI's even-split share of every grant they're on (the fair, additive number). Exposure = full size of all those grants.
Funding over time
peak $1.3M · FY2013–25$2M$1.5M$1M$500K$0
'13
'14
'15
'16
'17
'18
'19
'20
'21
'22
'23
'24
'25
Funding mix
By agency
NIH$7,970,031 · 5
By mechanism
R35$4,315,511 · 1
R01$2,542,368 · 2
K23$674,212 · 1
R21$437,940 · 1
Top collaborators
- Gregory F Cooper3 shared
- Romain Pirracchio1 shared
- Gary Weissman1 shared
Most similar at University Of Pittsburgh At Pittsburgh
Same institution · by research overlap
- Bill J Yates$10,406,888
- Teresa M Buck$2,416,496
- Ruchira Menka Jha$3,983,339
- Mohammad Al-Bataineh$2,280,027
- Henry E Wang$15,583,055
Others in their field
Top investigators on “Sepsis”
- Ian A Wilson · Scripps Research Institute, The$50,300,809
- Vance G Fowler · Duke University$48,391,331
- Alon Singer · Helixbind, Inc.$39,385,728
- Henry F Chambers · Duke University$39,317,414
- Jonathan Michael Dean · University Of Utah$36,397,260
- Rama K Mallampalli · Ohio State University$23,779,171
Research focus
SepsisImproved OutcomeElectronic Health RecordCessation Of LifeAmericanInflammationLaboratoriesBiological MarkersFundingPathogenBloodInsightAwardSystems BiologyTargeted TreatmentComputational BiologyEarly TreatmentFutureHospitalsScientistTreatment ResponseEnrollmentEthersLearning
Grant awards (20)
SMART-SEPSIS: Sequential MAchine learning for individualized Response to early Treatment in lung SEPSIS$750,561
R01 · FY2025 · HL
Sepsis online: learning while doing to understand biology and treatment$473,447
R35 · FY2025 · GM · contact PI
Individualized Prediction of Treatment Effects Using Data from Both Embedded Clinical Trials and Electronic Health Records$575,480
R01 · FY2024 · HL
Sepsis online: learning while doing to understand biology and treatment$473,447
R35 · FY2024 · GM · contact PI
Individualized Prediction of Treatment Effects Using Data from Both Embedded Clinical Trials and Electronic Health Records$603,080
R01 · FY2023 · HL
Sepsis online: learning while doing to understand biology and treatment$473,447
R35 · FY2023 · GM · contact PI
REMISE study: REMnant biospecimen Investigation in SEpsis$211,980
R21 · FY2023 · GM · contact PI
Individualized Prediction of Treatment Effects Using Data from Both Embedded Clinical Trials and Electronic Health Records$613,247
R01 · FY2022 · HL
Sepsis online: learning while doing to understand biology and treatment$472,834
R35 · FY2022 · GM · contact PI
REMISE study: REMnant biospecimen Investigation in SEpsis$225,960
R21 · FY2022 · GM · contact PI
Sepsis online: learning while doing to understand biology and treatment$483,099
R35 · FY2021 · GM · contact PI
Sepsis endotyping using clinical and biological data$391,128
R35 · FY2020 · GM · contact PI
Sepsis endotyping using clinical and biological data$391,250
R35 · FY2019 · GM · contact PI
Sepsis endotyping using clinical and biological data$391,041
R35 · FY2018 · GM · contact PI
Sepsis endotyping using clinical and biological data$388,438
R35 · FY2017 · GM · contact PI
Sepsis endotyping using clinical and biological data$377,380
R35 · FY2016 · GM · contact PI
Pre-hospital identification of high-risk sepsis$113,124
K23 · FY2016 · GM · contact PI
Pre-hospital identification of high-risk sepsis$187,024
K23 · FY2015 · GM · contact PI
Pre-hospital identification of high-risk sepsis$187,040
K23 · FY2014 · GM · contact PI
Pre-hospital identification of high-risk sepsis$187,024
K23 · FY2013 · GM · contact PI