erythromycin has been researched along with felbamate in 9 studies
| Timeframe | Studies, this research(%) | All Research% |
|---|---|---|
| pre-1990 | 0 (0.00) | 18.7374 |
| 1990's | 1 (11.11) | 18.2507 |
| 2000's | 1 (11.11) | 29.6817 |
| 2010's | 7 (77.78) | 24.3611 |
| 2020's | 0 (0.00) | 2.80 |
| Authors | Studies |
|---|---|
| Benz, RD; Contrera, JF; Kruhlak, NL; Matthews, EJ; Weaver, JL | 1 |
| Barnes, JC; Bradley, P; Day, NC; Fourches, D; Reed, JZ; Tropsha, A | 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 |
| Chen, M; Fang, H; Liu, Z; Shi, Q; Tong, W; Vijay, V | 1 |
| Ambroso, JL; Ayrton, AD; Baines, IA; Bloomer, JC; Chen, L; Clarke, SE; Ellens, HM; Harrell, AW; Lovatt, CA; Reese, MJ; Sakatis, MZ; Taylor, MA; Yang, EY | 1 |
| Chen, M; Hu, C; Suzuki, A; Thakkar, S; Tong, W; Yu, K | 1 |
| Lyness, WH; Montgomery, PA; Narang-Sachdeo, S; Perhach, JL; Rosenberg, A; Sachdeo, RC; Shumaker, RC | 1 |
1 review(s) available for erythromycin and felbamate
| 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 |
1 trial(s) available for erythromycin and felbamate
| Article | Year |
|---|---|
Evaluation of the potential interaction between felbamate and erythromycin in patients with epilepsy.
Topics: Adult; Anti-Bacterial Agents; Anticonvulsants; Cross-Over Studies; Drug Interactions; Epilepsy; Erythromycin; Felbamate; Female; Humans; Male; Metabolic Clearance Rate; Middle Aged; Phenylcarbamates; Propylene Glycols | 1998 |
7 other study(ies) available for erythromycin and felbamate
| Article | Year |
|---|---|
Assessment of the health effects of chemicals in humans: II. Construction of an adverse effects database for QSAR modeling.
Topics: Adverse Drug Reaction Reporting Systems; Artificial Intelligence; Computers; Databases, Factual; Drug Prescriptions; Drug-Related Side Effects and Adverse Reactions; Endpoint Determination; Models, Molecular; Quantitative Structure-Activity Relationship; Software; United States; United States Food and Drug Administration | 2004 |
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 |
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 |
FDA-approved drug labeling for the study of drug-induced liver injury.
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 |
Preclinical strategy to reduce clinical hepatotoxicity using in vitro bioactivation data for >200 compounds.
Topics: Chemical and Drug Induced Liver Injury; Cytochrome P-450 Enzyme Inhibitors; Cytochrome P-450 Enzyme System; Decision Trees; Drug Evaluation, Preclinical; Drug-Related Side Effects and Adverse Reactions; Glutathione; Humans; Liver; Pharmaceutical Preparations; Protein Binding | 2012 |