← Leaderboards
Joel Stephen Freundlich
Rbhs-New Jersey Medical School
$12,353,203
Attributed
$12,906,048
Total exposure
9
Grants
8
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 $1.9M · FY2014–24$2M$1.5M$1M$500K$0
'14
'15
'16
'17
'18
'19
'20
'21
'22
'23
'24
Funding mix
By agency
NIH$12,906,048 · 9
By mechanism
U19$8,588,173 · 5
R01$3,212,184 · 1
R21$880,693 · 2
R41$224,998 · 1
Top collaborators
- Connor Wilson Coley2 shared
- Emily R Derbyshire2 shared
- Sean Ekins1 shared
Others in their field
Top investigators on “Drug Discovery”
- David Heimbrook · Leidos Biomedical Research, Inc.$369,513,553
- Leonard Freedman · Leidos Biomedical Research, Inc.$255,277,443
- Douglas S. Hawkins · Children'S Hosp Of Philadelphia$157,315,120
- Ralph Parchment · Leidos Biomedical Research, Inc.$137,717,670
- Daniel Ernest Ford · Johns Hopkins University$137,014,543
- Lynn Briscoe · Leidos Biomedical Research, Inc.$93,294,869
Research focus
Drug DiscoveryLeadPharmaceutical ChemistryValidationGlobal HealthDrug KineticsSmall MoleculeInfectionSkillsEvolutionPharmaceutical PreparationsScreeningNovel TherapeuticsBiologicalBacterial InfectionsMycobacterium TuberculosisProgramsLearningStructural BiologyIn VitroAnalogDesignDrug ResistanceEvaluation
Grant awards (26)
A Preclinical Program for Targeting Mycobacterium tuberculosis KasA$790,771
R01 · FY2024 · AI · contact PI
Novel Dual-Stage Antimalarials: Machine learning prediction, validation and evolution$194,915
R21 · FY2024 · AI · contact PI
A Preclinical Program for Targeting Mycobacterium tuberculosis KasA$799,834
R01 · FY2023 · AI · contact PI
Core B Medicinal Chemistry$435,427
U19 · FY2023 · AI · contact PI
Novel Dual-Stage Antimalarials: Machine learning prediction, validation and evolution$246,404
R21 · FY2023 · AI · contact PI
Synthesizability-constrained expansion and multi-objective evolution of antitubercular compounds$242,025
R21 · FY2023 · AI · contact PI
Core B Medicinal Chemistry$930,949
U19 · FY2022 · AI · contact PI
A Preclinical Program for Targeting Mycobacterium tuberculosis KasA$795,178
R01 · FY2022 · AI · contact PI
Synthesizability-constrained expansion and multi-objective evolution of antitubercular compounds$197,349
R21 · FY2022 · AI · contact PI
Core B Medicinal Chemistry$1,031,010
U19 · FY2021 · AI · contact PI
A Preclinical Program for Targeting Mycobacterium tuberculosis KasA$826,401
R01 · FY2021 · AI · contact PI
Core B Medicinal Chemistry$915,335
U19 · FY2020 · AI · contact PI
Core B Medicinal Chemistry$1,022,482
U19 · FY2019 · AI · contact PI
Medicinal Chemistry Core$291,133
U19 · FY2018 · AI · contact PI
Bayesian models to accelerate antibacterial drug discovery$271,991
U19 · FY2018 · AI · contact PI
Structure-guided optimization of an in vivo active small molecule antitubercular targeting KasA$224,998
R41 · FY2018 · AI
Medicinal Chemistry Core$154,036
U19 · FY2018 · AI · contact PI
Bayesian models to accelerate antibacterial drug discovery$150,178
U19 · FY2018 · AI · contact PI
Medicinal Chemistry Core$459,324
U19 · FY2017 · AI · contact PI
Bayesian models to accelerate antibacterial drug discovery$429,294
U19 · FY2017 · AI · contact PI
Medicinal Chemistry Core$429,875
U19 · FY2016 · AI · contact PI
Bayesian models to accelerate antibacterial drug discovery$401,769
U19 · FY2016 · AI · contact PI
Medicinal Chemistry Core$395,674
U19 · FY2015 · AI · contact PI
Bayesian models to accelerate antibacterial drug discovery$383,852
U19 · FY2015 · AI · contact PI
Medicinal Chemistry Core$506,270
U19 · FY2014 · AI · contact PI
Bayesian models to accelerate antibacterial drug discovery$379,574
U19 · FY2014 · AI · contact PI