Compounds > emetine
Page last updated: 2024-08-21

emetine and chlorcyclizine

emetine has been researched along with chlorcyclizine in 5 studies

Research

Studies (5)

TimeframeStudies, this research(%)All Research%
pre-19900 (0.00)18.7374
1990's0 (0.00)18.2507
2000's1 (20.00)29.6817
2010's3 (60.00)24.3611
2020's1 (20.00)2.80

Authors

AuthorsStudies
Choi, SS; Contrera, JF; Hastings, KL; Kruhlak, NL; Sancilio, LF; Weaver, JL; Willard, JM1
Glen, RC; Lowe, R; Mitchell, JB1
Jadhav, A; Kerns, E; Nguyen, K; Shah, P; Sun, H; Xu, X; Yan, Z; Yu, KR1
Kabir, M; Kerns, E; Nguyen, K; Shah, P; Sun, H; Wang, Y; Xu, X; Yu, KR1
Kabir, M; Kerns, E; Neyra, J; Nguyen, K; Nguyễn, ÐT; Shah, P; Siramshetty, VB; Southall, N; Williams, J; Xu, X; Yu, KR1

Other Studies

5 other study(ies) available for emetine and chlorcyclizine

ArticleYear
Development of a phospholipidosis database and predictive quantitative structure-activity relationship (QSAR) models.
    Toxicology mechanisms and methods, 2008, Volume: 18, Issue:2-3

    Topics:

2008
Predicting phospholipidosis using machine learning.
    Molecular pharmaceutics, 2010, Oct-04, Volume: 7, Issue:5

    Topics: Animals; Artificial Intelligence; Databases, Factual; Drug Discovery; Humans; Lipidoses; Models, Biological; Phospholipids; Support Vector Machine

2010
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
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.
    Bioorganic & medicinal chemistry, 2019, 07-15, Volume: 27, Issue:14

    Topics: Drug Discovery; Organic Chemicals; Pharmaceutical Preparations; Solubility

2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.
    Scientific reports, 2020, 11-26, Volume: 10, Issue:1

    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