← Leaderboards
Asier Saez-Cirion
University Of Pittsburgh At Pittsburgh
$2,077,673
Attributed
$3,235,706
Total exposure
2
Grants
1
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 $934K · FY2017–24$1M$750K$500K$250K$0
'17
'18
'19
'20
'21
'22
'23
'24
Funding mix
By agency
NIH$3,235,706 · 2
By mechanism
R01$2,316,066 · 1
P01$919,640 · 1
Top collaborators
- Cristian Apetrei3 shared
Most similar at University Of Pittsburgh At Pittsburgh
Same institution · by research overlap
- Cristian Apetrei$24,938,676
- Robert L Cook$22,131,817
- Cristian L Achim$16,124,362
- Clayton A. Wiley$13,389,430
- Thomas Edward Smithgall$26,440,514
Others in their field
Other Emerging Leaders on “Therapeutic Intervention”
- Sonia M Thomas · Research Triangle Institute$701,865,642
- Tracy L Nolen · Research Triangle Institute$474,487,152
- Leonard Freedman · Leidos Biomedical Research, Inc.$269,117,714
- Douglas S. Hawkins · Children'S Hosp Of Philadelphia$157,315,120
- Lynn Briscoe · Leidos Biomedical Research, Inc.$97,254,054
- Marlene Ann Cooper · Harvard University D/B/A Harvard School Of Public Health$71,912,072
Research focus
Therapeutic InterventionHiv-1VirusTissuesImmune ActivationChronicShapesNonhuman PrimateViremiaViral ReservoirImmune SystemImmune ResponseAntiretroviral TherapyBloodHiv InfectionsInfectionMaintenanceCellsViralInterruptionImmunologic FactorsCohortImmunologicsCharacteristics
Grant awards (8)
Impact of metabolic programing of T cells from the GI tract and related tissues on HIV reservoir seeding, maintenance and reactivation$744,929
R01 · FY2024 · DK
Impact of metabolic programing of T cells from the GI tract and related tissues on HIV reservoir seeding, maintenance and reactivation$776,241
R01 · FY2022 · DK
Impact of metabolic programing of T cells from the GI tract and related tissues on HIV reservoir seeding, maintenance and reactivation$794,896
R01 · FY2021 · DK
Project 1. Defining Virologic and Immunologic Factors Predicting the Probability of Post-Treatment HIV Control$139,094
P01 · FY2021 · AI · contact PI
Project 1. Defining Virologic and Immunologic Factors Predicting the Probability of Post-Treatment HIV Control$124,319
P01 · FY2020 · AI · contact PI
Project 1. Defining Virologic and Immunologic Factors Predicting the Probability of Post-Treatment HIV Control$216,562
P01 · FY2019 · AI · contact PI
Project 1. Defining Virologic and Immunologic Factors Predicting the Probability of Post-Treatment HIV Control$213,327
P01 · FY2018 · AI · contact PI
Project 1. Defining Virologic and Immunologic Factors Predicting the Probability of Post-Treatment HIV Control$226,338
P01 · FY2017 · AI · contact PI