NeuroCADR: Drug Repurposing to Reveal Novel Anti-Epileptic Drug Candidates Through an Integrated Computational Approach [PDF]
arXiv, 2023 Drug repurposing is an emerging approach for drug discovery involving the reassignment of existing drugs for novel purposes. An alternative to the traditional de novo process of drug development, repurposed drugs are faster, cheaper, and less failure prone than drugs developed from traditional methods.
arxiv
Multi-drug resistant Gram-negative bacteria: antibiotic-resistance and new treatment strategies [PDF]
, 2017 In this editorial, we treat the multi-drug-resistance of microorganisms such as Klebsiella pneumonia (Kp) and Acinetobacter baumanii and the issues concerning the management of these infections.
Angelis, Massimiliano De +2 more
core +1 more source
Combinations of drugs in the Treatment of Obesity [PDF]
Pharmaceuticals, 2010 Obesity is a chronic disease associated with excess morbidity and mortality. Clinical treatment, however, currently offers disappointing results, with very high rates of weight loss failure or weight regain cycles, and only two drugs (orlistat and sibutramine) approved for long-term use.
Maria Edna de Melo +6 more
openaire +3 more sources
Principled Drug-Drug Interaction Terms for Bayesian Logistic Regression Models of Drug Safety in Oncology Phase I Combination Trials [PDF]
arXiv, 2023 In Oncology, trials evaluating drug combinations are becoming more common. While combination therapies bring the potential for greater efficacy, they also create unique challenges for ensuring drug safety. In Phase-I dose escalation trials of drug combinations, model-based approaches enable efficient use of information gathered, but the models need to ...
arxiv
DCcov: Repositioning of Drugs and Drug Combinations for SARS-CoV-2 Infected Lung through Constraint-Based Modelling [PDF]
, 2021 The 2019 coronavirus disease (COVID-19) became a worldwide pandemic with currently no effective antiviral drug except treatments for symptomatic therapy. Flux balance analysis is an efficient method to analyze metabolic networks. It allows optimizing for a metabolic function and thus e.g., predicting the growth rate of a specific cell or the production
arxiv +1 more source
The targeted delivery of multicomponent cargos to cancer cells by nanoporous particle-supported lipid bilayers. [PDF]
, 2011 Encapsulation of drugs within nanocarriers that selectively target malignant cells promises to mitigate side effects of conventional chemotherapy and to enable delivery of the unique drug combinations needed for personalized medicine.
Ashley, Carlee E +20 more
core +2 more sources
Drug Repurposing for Schistosomiasis: Combinations of Drugs or Biomolecules [PDF]
Pharmaceuticals, 2018 Schistosomiasis is a major neglected tropical disease. Control of schistosomiasis currently relies on a single drug, praziquantel, and despite its efficacy against the all schistosome species that parasitize humans, it displays some problematic drawbacks and alone is ineffective in counteracting adverse pathologies associated with infection.
Paul J. Brindley +6 more
openaire +4 more sources
Frontiers in Molecular Biosciences, 2022 Drug combinations can increase the therapeutic effect by reducing the level of toxicity and the occurrence of drug resistance. Therefore, several drug combinations are often used in the management of complex diseases.
Yongkai Hong +4 more
doaj +1 more source
Multi-View Substructure Learning for Drug-Drug Interaction Prediction [PDF]
arXiv, 2022 Drug-drug interaction (DDI) prediction provides a drug combination strategy for systemically effective treatment. Previous studies usually model drug information constrained on a single view such as the drug itself, leading to incomplete and noisy information, which limits the accuracy of DDI prediction.
arxiv
Improved Network Performance via Antagonism: From Synthetic Rescues to Multi-drug Combinations [PDF]
, 2010 Recent research shows that a faulty or sub-optimally operating metabolic network can often be rescued by the targeted removal of enzyme-coding genes--the exact opposite of what traditional gene therapy would suggest.
Adilson E. Motter +58 more
core +3 more sources