lapatinib has been researched along with nintedanib in 6 studies
| Studies (lapatinib) | Trials (lapatinib) | Recent Studies (post-2010) (lapatinib) | Studies (nintedanib) | Trials (nintedanib) | Recent Studies (post-2010) (nintedanib) |
|---|---|---|---|---|---|
| 1,919 | 305 | 1,442 | 846 | 133 | 801 |
| 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 | 5 (83.33) | 24.3611 |
| 2020's | 1 (16.67) | 2.80 |
| Authors | Studies |
|---|---|
| Ciceri, P; Davis, MI; Herrgard, S; Hocker, M; Hunt, JP; Pallares, G; Treiber, DK; Wodicka, LM; Zarrinkar, PP | 1 |
| Davis, MI; Khan, J; Li, SQ; Patel, PR; Shen, M; Sun, H; Thomas, CJ | 1 |
| Jadhav, A; Kerns, E; Nguyen, K; Shah, P; Sun, H; Xu, X; Yan, Z; Yu, KR | 1 |
| Aiche, S; Bassermann, F; Becker, W; Canevari, G; Casale, E; Depaolini, SR; Ehrlich, HC; Felder, ER; Feuchtinger, A; Garz, AK; Gohlke, BO; Götze, K; Greif, PA; Hahne, H; Heinzlmeir, S; Helm, D; Huenges, J; Jeremias, I; Kayser, G; Klaeger, S; Koch, H; Koenig, PA; Kramer, K; Kuster, B; Médard, G; Meng, C; Petzoldt, S; Polzer, H; Preissner, R; Qiao, H; Reinecke, M; Reiter, K; Rueckert, L; Ruland, J; Ruprecht, B; Schlegl, J; Schmidt, T; Schneider, S; Schoof, M; Spiekermann, K; Tõnisson, N; Vick, B; Vooder, T; Walch, A; Wilhelm, M; Wu, Z; Zecha, J; Zolg, DP | 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 |
6 other study(ies) available for lapatinib and nintedanib
| Article | Year |
|---|---|
Comprehensive analysis of kinase inhibitor selectivity.
Topics: Catalysis; Drug Design; Enzyme Stability; High-Throughput Screening Assays; Humans; Protein Binding; Protein Kinase Inhibitors; Protein Kinases; Proteomics; Signal Transduction; Substrate Specificity | 2011 |
Identification of potent Yes1 kinase inhibitors using a library screening approach.
Topics: Binding Sites; Cell Line; Cell Survival; Drug Design; Humans; Hydrogen Bonding; Molecular Docking Simulation; Protein Kinase Inhibitors; Protein Structure, Tertiary; Proto-Oncogene Proteins c-yes; Small Molecule Libraries; Structure-Activity Relationship | 2013 |
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 |
The target landscape of clinical kinase drugs.
Topics: Animals; Antineoplastic Agents; Cell Line, Tumor; Cytokines; Drug Discovery; fms-Like Tyrosine Kinase 3; Humans; Leukemia, Myeloid, Acute; Lung Neoplasms; Mice; Molecular Targeted Therapy; Protein Kinase Inhibitors; Protein Serine-Threonine Kinases; Proteomics; Xenograft Model Antitumor Assays | 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 |