lidocaine has been researched along with clarithromycin in 10 studies
| Timeframe | Studies, this research(%) | All Research% |
|---|---|---|
| pre-1990 | 0 (0.00) | 18.7374 |
| 1990's | 0 (0.00) | 18.2507 |
| 2000's | 3 (30.00) | 29.6817 |
| 2010's | 7 (70.00) | 24.3611 |
| 2020's | 0 (0.00) | 2.80 |
| Authors | Studies |
|---|---|
| Huang, L; Humphreys, JE; Morgan, JB; Polli, JW; Serabjit-Singh, CS; Webster, LO; Wring, SA | 1 |
| Lombardo, F; Obach, RS; Waters, NJ | 1 |
| Barnes, JC; Bradley, P; Day, NC; Fourches, D; Reed, JZ; Tropsha, A | 1 |
| Choi, SS; Contrera, JF; Hastings, KL; Kruhlak, NL; Sancilio, LF; Weaver, JL; Willard, JM | 1 |
| Fisk, L; Greene, N; Naven, RT; Note, RR; Patel, ML; Pelletier, DJ | 1 |
| Glen, RC; Lowe, R; Mitchell, JB | 1 |
| Ekins, S; Williams, AJ; Xu, JJ | 1 |
| Afshari, CA; Chen, Y; Dunn, RT; Hamadeh, HK; Kalanzi, J; Kalyanaraman, N; Morgan, RE; van Staden, CJ | 1 |
| Bellman, K; Knegtel, RM; Settimo, L | 1 |
| Chen, M; Hu, C; Suzuki, A; Thakkar, S; Tong, W; Yu, K | 1 |
1 review(s) available for lidocaine and clarithromycin
| Article | Year |
|---|---|
DILIrank: the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans.
Topics: Chemical and Drug Induced Liver Injury; Databases, Factual; Drug Labeling; Humans; Pharmaceutical Preparations; Risk | 2016 |
9 other study(ies) available for lidocaine and clarithromycin
| Article | Year |
|---|---|
Rational use of in vitro P-glycoprotein assays in drug discovery.
Topics: Adenosine Triphosphatases; Animals; ATP Binding Cassette Transporter, Subfamily B, Member 1; Cells, Cultured; Chromatography, Liquid; Enzyme Inhibitors; Fluoresceins; Fluorescent Dyes; Humans; Mass Spectrometry; Pharmacology; Spodoptera | 2001 |
Trend analysis of a database of intravenous pharmacokinetic parameters in humans for 670 drug compounds.
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.
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.
Topics: | 2008 |
Developing structure-activity relationships for the prediction of hepatotoxicity.
Topics: Chemical and Drug Induced Liver Injury; Databases, Factual; Humans; Structure-Activity Relationship; Tetracyclines; Thiophenes | 2010 |
Predicting phospholipidosis using machine learning.
Topics: Animals; Artificial Intelligence; Databases, Factual; Drug Discovery; Humans; Lipidoses; Models, Biological; Phospholipids; Support Vector Machine | 2010 |
A predictive ligand-based Bayesian model for human drug-induced liver injury.
Topics: Bayes Theorem; Chemical and Drug Induced Liver Injury; Humans; Ligands | 2010 |
A multifactorial approach to hepatobiliary transporter assessment enables improved therapeutic compound development.
Topics: Animals; ATP Binding Cassette Transporter, Subfamily B; ATP Binding Cassette Transporter, Subfamily B, Member 11; ATP-Binding Cassette Transporters; Biological Transport; Chemical and Drug Induced Liver Injury; Cluster Analysis; Drug-Related Side Effects and Adverse Reactions; Humans; Liver; Male; Multidrug Resistance-Associated Proteins; Pharmacokinetics; Rats; Rats, Sprague-Dawley; Recombinant Proteins; Risk Assessment; Risk Factors; Toxicity Tests | 2013 |
Comparison of the accuracy of experimental and predicted pKa values of basic and acidic compounds.
Topics: Chemistry, Pharmaceutical; Forecasting; Hydrogen-Ion Concentration; Pharmaceutical Preparations; Random Allocation | 2014 |