metformin has been researched along with zithromax in 15 studies
| Timeframe | Studies, this research(%) | All Research% |
|---|---|---|
| pre-1990 | 0 (0.00) | 18.7374 |
| 1990's | 0 (0.00) | 18.2507 |
| 2000's | 4 (26.67) | 29.6817 |
| 2010's | 10 (66.67) | 24.3611 |
| 2020's | 1 (6.67) | 2.80 |
| Authors | Studies |
|---|---|
| Benz, RD; Contrera, JF; Kruhlak, NL; Matthews, EJ; Weaver, JL | 1 |
| Lombardo, F; Obach, RS; Waters, NJ | 1 |
| Chupka, J; El-Kattan, A; Feng, B; Miller, HR; Obach, RS; Troutman, MD; Varma, MV | 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 |
| Chang, G; El-Kattan, A; Miller, HR; Obach, RS; Rotter, C; Steyn, SJ; Troutman, MD; Varma, MV | 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 |
| Bellera, CL; Bruno-Blanch, LE; Castro, EA; Duchowicz, PR; Goodarzi, M; Ortiz, EV; Pesce, G; Talevi, A | 1 |
| Afshari, CA; Chen, Y; Dunn, RT; Hamadeh, HK; Kalanzi, J; Kalyanaraman, N; Morgan, RE; van Staden, CJ | 1 |
| Chen, M; Hu, C; Suzuki, A; Thakkar, S; Tong, W; Yu, K | 1 |
| Agard, DA; Ashworth, A; Barrio-Hernandez, I; Batra, J; Beltrao, P; Bennett, MJ; Bohn, M; Bouhaddou, M; Braberg, H; Broadhurst, DJ; Cai, Y; Cakir, M; Calviello, L; Cavero, DA; Chang, JCJ; Chorba, JS; Craik, CS; d'Enfert, C; Dai, SA; Eckhardt, M; Emerman, M; Fabius, JM; Fletcher, SJ; Floor, SN; Foussard, H; Frankel, AD; Fraser, JS; Fujimori, DG; Ganesan, SJ; García-Sastre, A; Gordon, DE; Gross, JD; Guo, JZ; Haas, K; Haas, P; Hernandez-Armenta, C; Hiatt, J; Huang, XP; Hubert, M; Hüttenhain, R; Ideker, T; Jacobson, M; Jang, GM; Jura, N; Kaake, RM; Kim, M; Kirby, IT; Klippsten, S; Koh, C; Kortemme, T; Krogan, NJ; Kuzuoglu-Ozturk, D; Li, Q; Liboy-Lugo, J; Lin, Y; Liu, X; Liu, Y; Lou, K; Lyu, J; Mac Kain, A; Malik, HS; Mathy, CJP; McGregor, MJ; Melnyk, JE; Memon, D; Meyer, B; Miorin, L; Modak, M; Moreno, E; Mukherjee, S; Naing, ZZC; Noack, J; O'Meara, MJ; O'Neal, MC; Obernier, K; Ott, M; Peng, S; Perica, T; Pilla, KB; Polacco, BJ; Rakesh, R; Rathore, U; Rezelj, VV; Richards, AL; Roesch, F; Rosenberg, OS; Rosenthal, SB; Roth, BL; Roth, TL; Ruggero, D; Safari, M; Sali, A; Saltzberg, DJ; Savar, NS; Schwartz, O; Sharp, PP; Shen, W; Shengjuler, D; Shi, Y; Shoichet, BK; Shokat, KM; Soucheray, M; Stroud, RM; Subramanian, A; Swaney, DL; Taunton, J; Tran, QD; Trenker, R; Tummino, TA; Tutuncuoglu, B; Ugur, FS; Vallet, T; Venkataramanan, S; Verba, KA; Verdin, E; Vignuzzi, M; von Zastrow, M; Wang, HY; Wankowicz, SA; Wenzell, NA; White, KM; Xu, J; Young, JM; Zhang, Z; Zhou, Y | 1 |
| Arafat, T; Idkaidek, N | 1 |
| Bailey, SR; Bauquier, JR; Tudor, E | 1 |
1 review(s) available for metformin and zithromax
| 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 |
14 other study(ies) available for metformin and zithromax
| 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 |
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 |
Physicochemical determinants of human renal clearance.
Topics: Humans; Hydrogen Bonding; Hydrogen-Ion Concentration; Hydrophobic and Hydrophilic Interactions; Kidney; Metabolic Clearance Rate; Molecular Weight | 2009 |
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 |
Physicochemical space for optimum oral bioavailability: contribution of human intestinal absorption and first-pass elimination.
Topics: Administration, Oral; Biological Availability; Humans; Intestinal Absorption; Pharmaceutical Preparations | 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 |
Prediction of drug intestinal absorption by new linear and non-linear QSPR.
Topics: Humans; Intestinal Absorption; Linear Models; Molecular Conformation; Nonlinear Dynamics; Permeability; Pharmaceutical Preparations; Probability; Quantitative Structure-Activity Relationship; Thermodynamics | 2011 |
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 |
A SARS-CoV-2 protein interaction map reveals targets for drug repurposing.
Topics: Animals; Antiviral Agents; Betacoronavirus; Chlorocebus aethiops; Cloning, Molecular; Coronavirus Infections; COVID-19; COVID-19 Drug Treatment; Drug Evaluation, Preclinical; Drug Repositioning; HEK293 Cells; Host-Pathogen Interactions; Humans; Immunity, Innate; Mass Spectrometry; Molecular Targeted Therapy; Pandemics; Pneumonia, Viral; Protein Binding; Protein Biosynthesis; Protein Domains; Protein Interaction Mapping; Protein Interaction Maps; Receptors, sigma; SARS-CoV-2; SKP Cullin F-Box Protein Ligases; Vero Cells; Viral Proteins | 2020 |
Saliva versus plasma pharmacokinetics: theory and application of a salivary excretion classification system.
Topics: Acetates; Anthraquinones; Azithromycin; Benzhydryl Compounds; Cinacalcet; Cloxacillin; Cresols; Cyclopropanes; Female; Fluorobenzenes; Humans; Hydrochlorothiazide; Losartan; Male; Metformin; Naphthalenes; Phenylpropanolamine; Piroxicam; Pyrazines; Pyrimidines; Quinolines; Rosuvastatin Calcium; Saliva; Sitagliptin Phosphate; Sulfides; Sulfonamides; Tamsulosin; Tolterodine Tartrate; Triazoles | 2012 |
Anti-inflammatory effects of four potential anti-endotoxaemic drugs assessed in vitro using equine whole blood assays.
Topics: Animals; Anti-Inflammatory Agents; Azithromycin; Endotoxemia; Horse Diseases; Horses; In Vitro Techniques; Interleukin-1beta; Lipopolysaccharides; Metformin; Pyruvates; Rolipram; Tumor Necrosis Factor-alpha | 2015 |