Evidence map›Paper›PMID 38980370›Full record

ArticleBriefings in bioinformatics2024

RepurposeDrugs: an interactive web-portal and predictive platform for repurposing mono- and combination therapies.

Aleksandr Ianevski, Aleksandr Kushnir, Kristen Nader, Mitro Miihkinen, Henri Xhaard, Tero Aittokallio, Ziaurrehman Tanoli

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
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  11. Review
  12. Article
  13. Old drugs, new challenges: reassigning drugs for cancer therapies.Cellular & molecular biology letters · 2025
    Review
  14. Article
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Aleksandr IanevskiInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Finland.
Aleksandr KushnirInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Finland.
Kristen NaderInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Finland.
Mitro MiihkinenInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Finland.
Henri XhaardFaculty of Pharmacy, University of Helsinki, Finland.
Tero AittokallioInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Finland.ORCID 0000-0002-0886-9769
Ziaurrehman TanoliInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Finland.ORCID 0000-0003-2435-9862

Funding

Academy of Finland 351507Academy of Finland Academy of FinlandCancer Society of FinlandEuropean Union's Horizon Europe Research & Innovation 101057442Norwegian Health Authority South-East 2020026REMEDi4ALLSigrid Jusélius Foundation
6 · The paper itself

Abstract

RepurposeDrugs (https://repurposedrugs.org/) is a comprehensive web-portal that combines a unique drug indication database with a machine learning (ML) predictor to discover new drug-indication associations for approved as well as investigational mono and combination therapies. The platform provides detailed information on treatment status, disease indications and clinical trials across 25 indication categories, including neoplasms and cardiovascular conditions. The current version comprises 4314 compounds (approved, terminated or investigational) and 161 drug combinations linked to 1756 indications/conditions, totaling 28 148 drug-disease pairs. By leveraging data on both approved and failed indications, RepurposeDrugs provides ML-based predictions for the approval potential of new drug-disease indications, both for mono- and combinatorial therapies, demonstrating high predictive accuracy in cross-validation. The validity of the ML predictor is validated through a number of real-world case studies, demonstrating its predictive power to accurately identify repurposing candidates with a high likelihood of future approval. To our knowledge, RepurposeDrugs web-portal is the first integrative database and ML-based predictor for interactive exploration and prediction of both single-drug and combination approval likelihood across indications. Given its broad coverage of indication areas and therapeutic options, we expect it accelerates many future drug repurposing projects.

Indexed as

Drug RepositioningMachine LearningDatabases, FactualDatabases, PharmaceuticalDrug Therapy, CombinationHumansInternetclinical trial outcome predictionclinical trialscomputational drug repurposingdrug discoverydrug–disease associationsdrug repositioningrepurposing drug combinations

Identifiers

PMID38980370
PMCPMC11232279

What OpenQuestion holds

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Registered trials

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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.