mebendazole and ph 797804

mebendazole has been researched along with ph 797804 in 4 studies

Research

Studies (4)

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

Authors

AuthorsStudies
Jadhav, A; Kerns, E; Nguyen, K; Shah, P; Sun, H; Xu, X; Yan, Z; Yu, KR1
Kabir, M; Kerns, E; Nguyen, K; Shah, P; Sun, H; Wang, Y; Xu, X; Yu, KR1
Kabir, M; Kerns, E; Neyra, J; Nguyen, K; Nguyễn, ÐT; Shah, P; Siramshetty, VB; Southall, N; Williams, J; Xu, X; Yu, KR1
Itkin, M; Kabir, M; Mathé, EA; Nguyễn, ÐT; Padilha, EC; Shah, P; Shinn, P; Siramshetty, V; Wang, AQ; Williams, J; Xu, X; Yu, KR; Zhao, T1

Reviews

1 review(s) available for mebendazole and ph 797804

ArticleYear
Using in vitro ADME data for lead compound selection: An emphasis on PAMPA pH 5 permeability and oral bioavailability.
    Bioorganic & medicinal chemistry, 2022, 02-15, Volume: 56

    Topics: Administration, Oral; Animals; Betamethasone; Biological Availability; Caco-2 Cells; Cell Membrane Permeability; Cells, Cultured; Dexamethasone; Dogs; Dose-Response Relationship, Drug; Humans; Hydrogen-Ion Concentration; Madin Darby Canine Kidney Cells; Mice; Molecular Structure; Neural Networks, Computer; Ranitidine; Rats; Structure-Activity Relationship; Verapamil

2022

Other Studies

3 other study(ies) available for mebendazole and ph 797804

ArticleYear
Highly predictive and interpretable models for PAMPA permeability.
    Bioorganic & medicinal chemistry, 2017, 02-01, Volume: 25, Issue:3

    Topics: Artificial Intelligence; Caco-2 Cells; Cell Membrane Permeability; Humans; Models, Biological; Organic Chemicals; Regression Analysis; Support Vector Machine

2017
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.
    Bioorganic & medicinal chemistry, 2019, 07-15, Volume: 27, Issue:14

    Topics: Drug Discovery; Organic Chemicals; Pharmaceutical Preparations; Solubility

2019
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models.
    Scientific reports, 2020, 11-26, Volume: 10, Issue:1

    Topics: Animals; Computer Simulation; Databases, Factual; Drug Discovery; High-Throughput Screening Assays; Liver; Machine Learning; Male; Microsomes, Liver; National Center for Advancing Translational Sciences (U.S.); Pharmaceutical Preparations; Quantitative Structure-Activity Relationship; Rats; Rats, Sprague-Dawley; Retrospective Studies; United States

2020