ArticleScientific data2022
CDCDB: A large and continuously updated drug combination database.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 33 citations in OpenAlex.
- A Hypergraph-Based Model for Predicting Potential Drug Combinations in Cancer Therapy.Interdisciplinary sciences, computational life sciences · 2026Article
- Rethinking the role of synergy calculations in the next century of drug combination discovery.Med (New York, N.Y.) · 2026Review
- A Knowledge Graph Approach To Discovering Drug Combination Therapies Across The Phenome.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026Article
- Prediction of mixture toxicity of essential oil constituents using nonparametric and parametric models against Musca domestica L.Pest management science · 2025Article
- The integration of machine learning into traditional Chinese medicine.Journal of pharmaceutical analysis · 2025Review
- A highly annotated drug combination resource for catalyzing precision combinatorial therapy.Scientific data · 2025Article
- Integrating transcriptomic data with a novel drug efficacy prediction model for TCM active compound discovery.Scientific reports · 2025Article
- Data-driven learning of structure augments quantitative prediction of biological responses.PLoS computational biology · 2024Article
- Revolutionizing adjuvant development: harnessing AI for next-generation cancer vaccines.Frontiers in immunology · 2024Review
- Network pharmacology: towards the artificial intelligence-based precision traditional Chinese medicine.Briefings in bioinformatics · 2023Review
- Multi-task learning for predicting synergistic drug combinations based on auto-encoding multi-relational graphs.iScience · 2023Article
- EDST: a decision stump based ensemble algorithm for synergistic drug combination prediction.BMC bioinformatics · 2023Review
- Predicting anti-cancer drug combination responses with a temporal cell state network model.PLoS computational biology · 2023Article
- CDCDB: A large and continuously updated drug combination database.Scientific data · 2022Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, due to the complementary action of drug combinations over mono-therapy, the multiple-drugs for multiple-targets paradigm has received increased attention to treat bacterial infections and complex diseases. Although new drug combinations screening has benefited from experimental tests like automated high throughput screening, it is limited due to the large number of possible drug combinations. The task of drug combination screening can be streamlined through computational methods and models. Such models require up-to-date databases; however, existing databases are static and consist of the data collected at the time of their creation. This paper introduces the Continuous Drug Combination Database (CDCDB), a continuously updated drug combination database. The CDCDB includes over 40,795 drug combinations, of which 17,107 are unique combinations consisting of more than 4,129 individual drugs, curated from ClinicalTrials.gov, the FDA Orange Book
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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.