Page last updated: 2024-08-23

methyldopa and amikacin

methyldopa has been researched along with amikacin in 5 studies

Research

Studies (5)

TimeframeStudies, this research(%)All Research%
pre-19900 (0.00)18.7374
1990's0 (0.00)18.2507
2000's2 (40.00)29.6817
2010's3 (60.00)24.3611
2020's0 (0.00)2.80

Authors

AuthorsStudies
Lombardo, F; Obach, RS; Waters, NJ1
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
Chen, M; Hu, C; Suzuki, A; Thakkar, S; Tong, W; Yu, K1

Reviews

1 review(s) available for methyldopa and amikacin

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

Other Studies

4 other study(ies) available for methyldopa and amikacin

ArticleYear
Trend analysis of a database of intravenous pharmacokinetic parameters in humans for 670 drug compounds.
    Drug metabolism and disposition: the biological fate of chemicals, 2008, Volume: 36, Issue:7

    Topics: Blood Proteins; Half-Life; Humans; Hydrogen Bonding; Infusions, Intravenous; Pharmacokinetics; Protein Binding

2008
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