benzbromarone and su 11248

benzbromarone has been researched along with su 11248 in 4 studies

Research

Studies (4)

TimeframeStudies, this research(%)All Research%
pre-19900 (0.00)18.7374
1990's0 (0.00)18.2507
2000's0 (0.00)29.6817
2010's3 (75.00)24.3611
2020's1 (25.00)2.80

Authors

AuthorsStudies
Chen, M; Fang, H; Liu, Z; Shi, Q; Tong, W; Vijay, V1
Chen, M; Hu, C; Suzuki, A; Thakkar, S; Tong, W; Yu, K1
Jadhav, A; Kerns, E; Nguyen, K; Shah, P; Sun, H; Xu, X; Yan, Z; Yu, KR1
Delabio, LC; Dutra, JP; Hembecker, M; Kita, DH; Moure, VR; Pereira, GDS; Scheiffer, G; Valdameri, G; Zattoni, IF1

Reviews

2 review(s) available for benzbromarone and su 11248

ArticleYear
DILIrank: the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans.
    Drug discovery today, 2016, Volume: 21, Issue:4

    Topics: Chemical and Drug Induced Liver Injury; Databases, Factual; Drug Labeling; Humans; Pharmaceutical Preparations; Risk

2016
Targeting breast cancer resistance protein (BCRP/ABCG2): Functional inhibitors and expression modulators.
    European journal of medicinal chemistry, 2022, Jul-05, Volume: 237

    Topics: Antineoplastic Agents; ATP Binding Cassette Transporter, Subfamily G, Member 2; Breast Neoplasms; Drug Resistance, Multiple; Drug Resistance, Neoplasm; Female; Humans; Neoplasm Proteins; Neoplastic Stem Cells

2022

Other Studies

2 other study(ies) available for benzbromarone and su 11248

ArticleYear
FDA-approved drug labeling for the study of drug-induced liver injury.
    Drug discovery today, 2011, Volume: 16, Issue:15-16

    Topics: Animals; Benchmarking; Biomarkers, Pharmacological; Chemical and Drug Induced Liver Injury; Drug Design; Drug Labeling; Drug-Related Side Effects and Adverse Reactions; Humans; Pharmaceutical Preparations; Reproducibility of Results; United States; United States Food and Drug Administration

2011
Highly predictive and interpretable models for PAMPA permeability.
    Bioorganic & medicinal chemistry, 2017, 02-01, Volume: 25, Issue:3

    Topics: Artificial Intelligence; Caco-2 Cells; Cell Membrane Permeability; Humans; Models, Biological; Organic Chemicals; Regression Analysis; Support Vector Machine

2017