ambroxol and clarithromycin

ambroxol has been researched along with clarithromycin in 4 studies

Research

Studies (4)

TimeframeStudies, this research(%)All Research%
pre-19900 (0.00)18.7374
1990's0 (0.00)18.2507
2000's2 (50.00)29.6817
2010's2 (50.00)24.3611
2020's0 (0.00)2.80

Authors

AuthorsStudies
Barnes, JC; Bradley, P; Day, NC; Fourches, D; Reed, JZ; Tropsha, A1
Choi, SS; Contrera, JF; Hastings, KL; Kruhlak, NL; Sancilio, LF; Weaver, JL; Willard, JM1
Glen, RC; Lowe, R; Mitchell, JB1
Kido, H; Le, TQ; Okumura, Y; Yamada, H; Yano, M1

Reviews

1 review(s) available for ambroxol and clarithromycin

ArticleYear
Proteases essential for human influenza virus entry into cells and their inhibitors as potential therapeutic agents.
    Current pharmaceutical design, 2007, Volume: 13, Issue:4

    Topics: Ambroxol; Animals; Antiviral Agents; Brain; Clarithromycin; Drug Therapy, Combination; Expectorants; Hemagglutinin Glycoproteins, Influenza Virus; Humans; Influenza A virus; Influenza, Human; Neuraminidase; Peptide Hydrolases; Protease Inhibitors; Protein Processing, Post-Translational; Pulmonary Surfactants; Respiratory System; Secretory Leukocyte Peptidase Inhibitor; Virus Replication

2007

Other Studies

3 other study(ies) available for ambroxol and clarithromycin

ArticleYear
Cheminformatics analysis of assertions mined from literature that describe drug-induced liver injury in different species.
    Chemical research in toxicology, 2010, Volume: 23, Issue:1

    Topics: Animals; Chemical and Drug Induced Liver Injury; Cluster Analysis; Databases, Factual; Humans; MEDLINE; Mice; Models, Chemical; Molecular Conformation; Quantitative Structure-Activity Relationship

2010
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