Results 31 to 40 of about 1,821,409 (281)

Drug repositioning: A bibliometric analysis

open access: yesFrontiers in Pharmacology, 2022
Drug repurposing has become an effective approach to drug discovery, as it offers a new way to explore drugs. Based on the Science Citation Index Expanded (SCI-E) and Social Sciences Citation Index (SSCI) databases of the Web of Science core collection, this study presents a bibliometric analysis of drug repurposing publications from 2010 to 2020. Data
Guojun Sun   +9 more
openaire   +3 more sources

Drug Repositioning: New Approaches and Future Prospects for Life-Debilitating Diseases and the COVID-19 Pandemic Outbreak

open access: yesViruses, 2020
Traditionally, drug discovery utilises a de novo design approach, which requires high cost and many years of drug development before it reaches the market.
Zheng Yao Low   +2 more
doaj   +1 more source

Recent computational drug repositioning strategies against SARS-CoV-2

open access: yesComputational and Structural Biotechnology Journal, 2022
Since COVID-19 emerged in 2019, significant levels of suffering and disruption have been caused on a global scale. Although vaccines have become widely used, the virus has shown its potential for evading immunities or acquiring other novel ...
Lu Lu   +6 more
doaj   +1 more source

Repositioned Drugs for Chagas Disease Unveiled via Structure-Based Drug Repositioning [PDF]

open access: yesInternational Journal of Molecular Sciences, 2020
Chagas disease, caused by the parasite Trypanosoma cruzi, affects millions of people in South America. The current treatments are limited, have severe side effects, and are only partially effective. Drug repositioning, defined as finding new indications for already approved drugs, has the potential to provide new therapeutic options for Chagas. In this
Melissa F. Adasme   +11 more
openaire   +2 more sources

A two-tiered unsupervised clustering approach for drug repositioning through heterogeneous data integration

open access: yesBMC Bioinformatics, 2018
Background Drug repositioning is the process of identifying new uses for existing drugs. Computational drug repositioning methods can reduce the time, costs and risks of drug development by automating the analysis of the relationships in pharmacology ...
Pathima Nusrath Hameed   +3 more
doaj   +1 more source

RepCOOL: computational drug repositioning via integrating heterogeneous biological networks

open access: yesJournal of Translational Medicine, 2020
Background It often takes more than 10 years and costs more than 1 billion dollars to develop a new drug for a particular disease and bring it to the market. Drug repositioning can significantly reduce costs and time in drug development.
Ghazale Fahimian   +3 more
doaj   +1 more source

In silico drug repositioning based on the integration of chemical, genomic and pharmacological spaces

open access: yesBMC Bioinformatics, 2021
Background Drug repositioning refers to the identification of new indications for existing drugs. Drug-based inference methods for drug repositioning apply some unique features of drugs for new indication prediction. Complementary information is provided
Hailin Chen, Zuping Zhang, Jingpu Zhang
doaj   +1 more source

Maltol has anti-cancer effects via modulating PD-L1 signaling pathway in B16F10 cells

open access: yesFrontiers in Pharmacology, 2023
Introduction: Among skin cancers, melanoma has a high mortality rate. Recent advances in immunotherapy, particularly through immune checkpoint modulation, have improved the clinical treatment of melanoma.
Na-Ra Han   +5 more
doaj   +1 more source

Repositioning Natural Products in Drug Discovery [PDF]

open access: yesMolecules, 2020
Drug repositioning (o repurposing) has become one of the most popular and successful strategies to reduce failures typically associated with drug discovery [...]
Rastelli, G.   +3 more
openaire   +4 more sources

Novel network pharmacology methods for drug mechanism of action identification, pre-clinical drug screening and drug repositioning [PDF]

open access: yes, 2011
The high rates of failure in oncology drug clinical trials highlight the problems of using pre-clinical data to predict the clinical effects of drugs. Here we present two methodology innovations on network pharmacology modeling.
Jianghui Xiong
core   +1 more source

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