ReviewJournal of cheminformatics2020
A review of computational drug repositioning: strategies, approaches, opportunities, challenges, and directions.
Review in Journal of cheminformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 146 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
146 citing papers in PubMed, 1 synthesis or guideline pooled it, 384 citations in OpenAlex.
- Drug repurposing on Alzheimer's disease through modulation of NRF2 neighborhood.Redox biology · 2023Pooled it
- A Randomized Controlled Pilot Study Evaluating the Safety and Efficacy of Nifuroxazide in Patients with Ulcerative Colitis.Drug design, development and therapy · 2025Trial
- Identification of Potential Biomarkers Associated with Impaired Fatty Acid Oxidation in Aged Skeletal Muscle Using Bioinformatics and Machine Learning Approaches.Biomolecules · 2026Article
- Medicinal Chemistry Perspectives on Drug Repurposing: Innovative Approaches and Therapeutic Breakthrough.Therapeutic innovation & regulatory science · 2026Review
- Systems biology-based drug repurposing for neuroinflammation treatment in activated human microglia.Scientific reports · 2026Article
- From General-Purpose to Disease-Specific Features: Aligning LLM Embeddings on a Disease-Specific Biomedical Knowledge Graph for Drug Repurposing.bioRxiv : the preprint server for biology · 2026Article
- Enhanced drug disease association prediction through multimodal data integration and meta path guided global local feature fusion.Scientific reports · 2026Article
- ConvAHKG: Action-based hybrid knowledge graph with a dual-channel convolutional approach for drug repurposing.Scientific reports · 2026Article
- Recent advances in drug repositioning and rediscovery for different therapeutic activities utilizing updated technological approaches.Molecular diversity · 2026Review
- Robustness Analyses Substantially Narrow in silico Network-Toxicology Signals Linking Selected Pharmaceuticals and Caffeine to Vitiligo.Clinical, cosmetic and investigational dermatology · 2026Article
- In-silico target prediction and pathway analysis of propranolol as a potential therapeutic agent for hepatocellular carcinoma.PloS one · 2026Article
- Enhanced drug-disease association prediction through representation learning on similarity networks.Biology methods & protocols · 2026Article
- molIEreVIS: exploring and interpreting the evidence behind drug repurposing predictions.Frontiers in bioinformatics · 2026Article
- SMPR: a structure-enhanced multimodal drug‒disease prediction model for drug repositioning and cold start.Journal of cheminformatics · 2025Article
- AI-based mining of biomedical literature: Applications for drug repurposing for the treatment of dementia.Artificial intelligence in medicine · 2025Article
- Dual-route embedding-aware graph neural networks for drug repositioning.Briefings in bioinformatics · 2025Article
- Improving computational drug repositioning through multi-source disease similarity networks.Scientific reports · 2025Article
- Drug repurposing for Alzheimer's disease using a graph-of-thoughts based large language model to infer drug-disease relationships in a comprehensive knowledge graph.BioData mining · 2025Article
- Selective Cleaning Enhances Machine Learning Accuracy for Drug Repurposing: Multiscale Discovery of MDM2 Inhibitors.Molecules (Basel, Switzerland) · 2025Article
- DrugReX: an explainable drug repurposing system powered by large language models and literature-based knowledge graph.Research square · 2025Article
86 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Drug repositioning is the process of identifying novel therapeutic potentials for existing drugs and discovering therapies for untreated diseases. Drug repositioning, therefore, plays an important role in optimizing the pre-clinical process of developing novel drugs by saving time and cost compared to the traditional de novo drug discovery processes. Since drug repositioning relies on data for existing drugs and diseases the enormous growth of publicly available large-scale biological, biomedical, and electronic health-related data along with the high-performance computing capabilities have accelerated the development of computational drug repositioning approaches. Multidisciplinary researchers and scientists have carried out numerous attempts, with different degrees of efficiency and success, to computationally study the potential of repositioning drugs to identify alternative drug indications. This study reviews recent advancements in the field of computational drug repositioning. First, we highlight different drug repositioning strategies and provide an overview of frequently used resources. Second, we summarize computational approaches that are extensively used in drug repositioning studies. Third, we present different computing and experimental models to validate computational methods. Fourth, we address prospective opportunities, including a few target areas. Finally, we discuss challenges and limitations encountered in computational drug repositioning and conclude with an outline of further research directions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.