tipifarnib has been researched along with ketamine in 3 studies
| Studies (tipifarnib) | Trials (tipifarnib) | Recent Studies (post-2010) (tipifarnib) | Studies (ketamine) | Trials (ketamine) | Recent Studies (post-2010) (ketamine) |
|---|---|---|---|---|---|
| 309 | 92 | 94 | 15,029 | 2,321 | 6,678 |
| Protein | Taxonomy | tipifarnib (IC50) | ketamine (IC50) |
|---|---|---|---|
| Glutamate receptor ionotropic, NMDA 1 | Rattus norvegicus (Norway rat) | 4.216 | |
| Glutamate receptor ionotropic, NMDA 2A | Rattus norvegicus (Norway rat) | 4.216 | |
| Glutamate receptor ionotropic, NMDA 2B | Rattus norvegicus (Norway rat) | 5.02 | |
| Glutamate receptor ionotropic, NMDA 2C | Rattus norvegicus (Norway rat) | 5.02 | |
| Glutamate receptor ionotropic, NMDA 1 | Homo sapiens (human) | 3.7762 | |
| Glutamate receptor ionotropic, NMDA 2A | Homo sapiens (human) | 3.5563 | |
| Glutamate receptor ionotropic, NMDA 2B | Homo sapiens (human) | 4.1059 | |
| Glutamate receptor ionotropic, NMDA 2D | Rattus norvegicus (Norway rat) | 5.02 | |
| Glutamate receptor ionotropic, NMDA 3B | Rattus norvegicus (Norway rat) | 5.02 | |
| Glutamate receptor ionotropic, NMDA 3A | Rattus norvegicus (Norway rat) | 5.02 |
| Timeframe | Studies, this research(%) | All Research% |
|---|---|---|
| pre-1990 | 0 (0.00) | 18.7374 |
| 1990's | 0 (0.00) | 18.2507 |
| 2000's | 0 (0.00) | 29.6817 |
| 2010's | 2 (66.67) | 24.3611 |
| 2020's | 1 (33.33) | 2.80 |
| Authors | Studies |
|---|---|
| Jadhav, A; Kerns, E; Nguyen, K; Shah, P; Sun, H; Xu, X; Yan, Z; Yu, KR | 1 |
| Kabir, M; Kerns, E; Nguyen, K; Shah, P; Sun, H; Wang, Y; Xu, X; Yu, KR | 1 |
| Kabir, M; Kerns, E; Neyra, J; Nguyen, K; Nguyễn, ÐT; Shah, P; Siramshetty, VB; Southall, N; Williams, J; Xu, X; Yu, KR | 1 |
3 other study(ies) available for tipifarnib and ketamine
| Article | Year |
|---|---|
Highly predictive and interpretable models for PAMPA permeability.
Topics: Artificial Intelligence; Caco-2 Cells; Cell Membrane Permeability; Humans; Models, Biological; Organic Chemicals; Regression Analysis; Support Vector Machine | 2017 |
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.
Topics: Drug Discovery; Organic Chemicals; Pharmaceutical Preparations; Solubility | 2019 |
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.
Topics: Animals; Computer Simulation; Databases, Factual; Drug Discovery; High-Throughput Screening Assays; Liver; Machine Learning; Male; Microsomes, Liver; National Center for Advancing Translational Sciences (U.S.); Pharmaceutical Preparations; Quantitative Structure-Activity Relationship; Rats; Rats, Sprague-Dawley; Retrospective Studies; United States | 2020 |