Check pharmacology, toxicology and pharmaceutics papers: citations, claims and retractions

Characterisation of pore structures of pharmaceutical tablets: A review

Markl, D., Strobel, A., Schlossnikl, R., Bøtker, J., Bawuah, P., Ridgway, C., Rantanen, J., Rades, T., Gane, P., Peiponen, K.-E., et al. (2018) · International Journal of Pharmaceutics

Drug Solubulity and Delivery SystemsGranular flow and fluidized beds

Cited by 154

Big data in chemical toxicity research: The use of high-throughput screening assays to identify potential toxicants

Zhu, H., Zhang, J., Kim, M. T., Boison, A., Sedykh, A., & Moran, K. (2014) · Chemical Research in Toxicology

Computational Drug Discovery MethodsEnvironmental Toxicology and Ecotoxicology

Cited by 154

Artificial Intelligence and Machine Learning in Pharmacological Research: Bridging the Gap Between Data and Drug Discovery

Singh, S., Kumar, R., Payra, S., & Singh, S. K. (2023) · Cureus

Computational Drug Discovery MethodsArtificial Intelligence in Healthcare and Education

Cited by 154

Polymeric micelles in mucosal drug delivery: challenges towards clinical translation

Sosnik, A., & Menaker Raskin, M. (2015) · Biotechnology Advances

Advanced Drug Delivery SystemsNanoparticle-Based Drug Delivery

Cited by 154

Leveraging Uncertainty in Machine Learning Accelerates Biological Discovery and Design

Hie, B., Bryson, B. D., & Berger, B. (2020) · Cell Systems

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 154

Functional chitosan oligosaccharide nanomicelles for topical ocular drug delivery of dexamethasone

Xu, X., Sun, L., Zhou, L., Cheng, Y., & Cao, F. (2020) · Carbohydrate Polymers

Advanced Drug Delivery SystemsOcular Surface and Contact Lens

Cited by 153

Toxicity prediction based on artificial intelligence: A multidisciplinary overview

Pérez Santín, E., Rodríguez Solana, R., González García, M., García Suárez, M. D. M., Blanco Díaz, G. D., Cima Cabal, M. D., Moreno Rojas, J. M., & López Sánchez, J. I. (2021) · WIREs Computational Molecular Science

Computational Drug Discovery MethodsAnimal testing and alternatives

Cited by 153

Impact of ABCG2 and SLCO1B1 polymorphisms on pharmacokinetics of rosuvastatin, atorvastatin and simvastatin acid in Caucasian and Asian subjects: a class effect?

Birmingham, B. K., Bujac, S. R., Elsby, R., Azumaya, C. T., Wei, C., Chen, Y., Mosqueda-Garcia, R., & Ambrose, H. J. (2015) · European Journal of Clinical Pharmacology

Pharmacogenetics and Drug MetabolismDrug Transport and Resistance Mechanisms

Cited by 153

Adverse reactions associated with oral and parenteral use of cephalosporins: a retrospective population-based analysis.

Macy, E., & Contreras, R. (2015) · Journal of Allergy and Clinical Immunology

Pharmacovigilance and Adverse Drug ReactionsDrug-Induced Adverse Reactions

Cited by 153

Effects of ginger ( Zingiber officinale ) on plasma glucose level, HbA1c and insulin sensitivity in type 2 diabetic patients

Mahluji, S., Attari, V. E., Mobasseri, M., Payahoo, L., Ostadrahimi, A., & Golzari, S. E. (2013) · International Journal of Food Sciences and Nutrition

Ginger and Zingiberaceae researchNatural Antidiabetic Agents Studies

Cited by 153

Sedation with "non-sedating" antihistamines: four prescription-event monitoring studies in general practice Commentary: Reporting of adverse events is worth the effort

Mann, R. D. (2000) · BMJ

Pharmacovigilance and Adverse Drug ReactionsPharmaceutical Practices and Patient Outcomes

Cited by 152

Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding Prediction

Russo, D. P., Zorn, K. M., Clark, A. M., Zhu, H., & Ekins, S. (2018) · Molecular Pharmaceutics

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 152

Data Set Modelability by QSAR

Golbraikh, A., Muratov, E., Fourches, D., & Tropsha, A. (2014) · Journal of Chemical Information and Modeling

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 152

ahr null alleles: distinctive or different?

Lahvis, G. P., & Bradfield, C. A. (1998) · Biochemical Pharmacology

Pharmacogenetics and Drug MetabolismAnimal Genetics and Reproduction

Cited by 152

Studies on the role of intestinal bacteria in metabolism of synthetic and natural steroid hormones

Adlercreutz, H., Pulkkinen, M. O., Hämäläinen, E. K., & Korpela, J. T. (1984) · Journal of Steroid Biochemistry

Pharmacogenetics and Drug MetabolismGut microbiota and health

Cited by 151

Evidence for the Existence of a Self-Regulated Enzymatic Process Within the Human Stratum Corneum –An Unexpected Role for Urocanic Acid

Krien, P. M., & Kermici, M. (2000) · Journal of Investigative Dermatology

Advancements in Transdermal Drug DeliverySkin Protection and Aging

Cited by 151

Anti-inflammatory efficacy of Licochalcone A: Correlation of clinical potency and in vitro effects

Kolbe, L., Immeyer, J., Batzer, J., Wensorra, U., Dieck, K. T., Mundt, C., Wolber, R., Stäb, F., Schönrock, U., Ceilley, R. I., et al. (2006) · Archives of Dermatological Research

Pharmacological Effects of Natural CompoundsSkin Protection and Aging

Cited by 151

Challenges of peptide and protein drug delivery by oral route: Current strategies to improve the bioavailability

Verma, S., Goand, U. K., Husain, A., Katekar, R. A., Garg, R., & Gayen, J. R. (2021) · Drug Development Research

Advanced Drug Delivery SystemsDrug Solubulity and Delivery Systems

Cited by 151

The Advent of Generative Chemistry

Vanhaelen, Q., Lin, Y.-C., & Zhavoronkov, A. (2020) · ACS Medicinal Chemistry Letters

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 151

Design of efficient computational workflows for in silico drug repurposing

Vanhaelen, Q., Mamoshina, P., Aliper, A. M., Artemov, A., Lezhnina, K., Ozerov, I., Labat, I., & Zhavoronkov, A. (2017) · Drug Discovery Today

Computational Drug Discovery Methodsvaccines and immunoinformatics approaches

Cited by 150

G.L. Amidon, H. Lennernas, V.P. Shah, and J.R. Crison. A Theoretical Basis for a Biopharmaceutic Drug Classification: The Correlation of In Vitro Drug Product Dissolution and In Vivo Bioavailability, Pharm Res 12, 413–420, 1995—Backstory of BCS

Shah, V. P., & Amidon, G. L. (2014) · The AAPS Journal

Drug Solubulity and Delivery SystemsAdvanced Drug Delivery Systems

Cited by 150

Predicting drug-target interaction network using deep learning model

You, J., McLeod, R. D., & Hu, P. (2019) · Computational Biology and Chemistry

Computational Drug Discovery MethodsMachine Learning in Bioinformatics

Cited by 150

Atomic convolutional networks for predicting protein-ligand binding affinity

Gomes, J., Ramsundar, B., Feinberg, E. N., & Pande, V. S. (2017) · arXiv

Computational Drug Discovery MethodsMachine Learning in Bioinformatics

Cited by 150

Effective GDNF brain delivery using microspheres—A promising strategy for Parkinson's disease

Garbayo, E., Montero-Menei, C. N., Ansorena, E., Lanciego, J. L., Aymerich, M. S., & Blanco-Prieto, M. J. (2009) · Journal of Controlled Release

Advanced Drug Delivery SystemsParkinson's Disease Mechanisms and Treatments

Cited by 150