l 163191 has been researched along with azd 1152 in 4 studies
| Studies (l 163191) | Trials (l 163191) | Recent Studies (post-2010) (l 163191) | Studies (azd 1152) | Trials (azd 1152) | Recent Studies (post-2010) (azd 1152) |
|---|---|---|---|---|---|
| 35 | 0 | 17 | 21 | 0 | 16 |
| Protein | Taxonomy | l 163191 (IC50) | azd 1152 (IC50) |
|---|---|---|---|
| Aurora kinase A | Homo sapiens (human) | 0.3268 | |
| Aurora kinase B | Homo sapiens (human) | 0.0393 | |
| Aurora kinase C | Homo sapiens (human) | 0.0627 |
| 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 (50.00) | 24.3611 |
| 2020's | 2 (50.00) | 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 |
| Itkin, M; Kabir, M; Mathé, EA; Nguyễn, ÐT; Padilha, EC; Shah, P; Shinn, P; Siramshetty, V; Wang, AQ; Williams, J; Xu, X; Yu, KR; Zhao, T | 1 |
1 review(s) available for l 163191 and azd 1152
| Article | Year |
|---|---|
Using in vitro ADME data for lead compound selection: An emphasis on PAMPA pH 5 permeability and oral bioavailability.
Topics: Administration, Oral; Animals; Betamethasone; Biological Availability; Caco-2 Cells; Cell Membrane Permeability; Cells, Cultured; Dexamethasone; Dogs; Dose-Response Relationship, Drug; Humans; Hydrogen-Ion Concentration; Madin Darby Canine Kidney Cells; Mice; Molecular Structure; Neural Networks, Computer; Ranitidine; Rats; Structure-Activity Relationship; Verapamil | 2022 |
3 other study(ies) available for l 163191 and azd 1152
| 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 |