ArticleScientific reports2020
Synergistic drug combinations and machine learning for drug repurposing in chordoma.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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
27 citing papers in PubMed, 42 citations in OpenAlex.
- Current Trends and Future Prospects of Radiomics and Machine Learning (ML) Models in Spinal Tumors-A Narrative Review.Journal of imaging · 2026Review
- RAB3B Dictates mTORC1/S6 Signaling in Chordoma and Predicts Response to mTORC1-Targeted Therapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Repurposing of Anti-Infectives for the Management of Onchocerciasis Using Machine Learning and Protein Docking Studies.Bioinformatics and biology insights · 2025Article
- Integrated Molecular and Histological Insights for Targeted Therapies in Mesenchymal Sinonasal Tract Tumors.Current oncology reports · 2024Review
- Extracting Drug-Protein Relation from Literature Using Ensembles of Biomedical Transformers.Studies in health technology and informatics · 2024Article
- Exploring Scoring Function Space: Developing Computational Models for Drug Discovery.Current medicinal chemistry · 2024Review
- Article
- Targeted Inhibition of Hsp90 in Combination with Metformin Modulates Programmed Cell Death Pathways in A549 Lung Cancer Cells.Applied biochemistry and biotechnology · 2023Article
- Combined Deep Learning and Molecular Modeling Techniques on the Virtual Screening of New mTOR Inhibitors from the Thai Mushroom Database.ACS omega · 2023Article
- Developing Treatments for Rare Diseases on a Shoestring.GEN biotechnology · 2023Article
- Drug Delivery Systems for Localized Cancer Combination Therapy.ACS applied bio materials · 2023Review
- Article
- The Commoditization of AI for Molecule Design.Artificial intelligence in the life sciences · 2022Article
- Multiple approaches to repurposing drugs for neuroblastoma.Bioorganic & medicinal chemistry · 2022Article
- MRI-Based Radiomics Differentiates Skull Base Chordoma and Chondrosarcoma: A Preliminary Study.Cancers · 2022Article
- Recurrent Metastatic Chordoma to the Liver: A Case Report and Review of the Literature.Current oncology (Toronto, Ont.) · 2022Review
- Considerations and challenges for sex-aware drug repurposing.Biology of sex differences · 2022Review
- Personalized chordoma organoids for drug discovery studies.Science advances · 2022Article
- Knowledge-based approaches to drug discovery for rare diseases.Drug discovery today · 2022Review
- A chronicle review of new techniques that facilitate the understanding and development of optimal individualized therapeutic strategies for chordoma.Frontiers in oncology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
Chordoma is a devastating rare cancer that affects one in a million people. With a mean-survival of just 6 years and no approved medicines, the primary treatments are surgery and radiation. In order to speed new medicines to chordoma patients, a drug repurposing strategy represents an attractive approach. Drugs that have already advanced through human clinical safety trials have the potential to be approved more quickly than de novo discovered medicines on new targets. We have taken two strategies to enable this: (1) generated and validated machine learning models of chordoma inhibition and screened compounds of interest in vitro. (2) Tested combinations of approved kinase inhibitors already being individually evaluated for chordoma. Several published studies of compounds screened against chordoma cell lines were used to generate Bayesian Machine learning models which were then used to score compounds selected from the NIH NCATS industry-provided assets. Out of these compounds, the mTOR inhibitor AZD2014, was the most potent against chordoma cell lines (IC
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What OpenQuestion holds
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.