ArticleOrphanet journal of rare diseases2019
The use or generation of biomedical data and existing medicines to discover and establish new treatments for patients with rare diseases - recommendations of the IRDiRC Data Mining and Repurposing Task Force.
Article in Orphanet journal of rare diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Data Augmentation and Synthetic Data Generation in Rare Disease Research: A Scoping Review.Medical sciences (Basel, Switzerland) · 2025Article
- Computational Drug Repositioning in Cardiorenal Disease: Opportunities, Challenges, and Approaches.Proteomics · 2025Article
- Drug repurposing for rare: progress and opportunities for the rare disease community.Frontiers in medicine · 2024Article
- Literature Review on Health Emigration in Rare Diseases-A Machine Learning Perspective.International journal of environmental research and public health · 2023Review
- Expert-opinion-based guidance for the care of children with lysosomal storage diseases during the COVID-19 pandemic: An experience-based Turkey perspective.Frontiers in public health · 2023Review
- Phase-In to Phase-Out-Targeted, Inclusive Strategies Are Needed to Enable Full Replacement of Animal Use in the European Union.Animals : an open access journal from MDPI · 2022Article
- Drug repositioning: A bibliometric analysis.Frontiers in pharmacology · 2022Review
- Improving early diagnosis of rare diseases using Natural Language Processing in unstructured medical records: an illustration from Dravet syndrome.Orphanet journal of rare diseases · 2021Article
- Dried Blood Spot (DBS) Methodology Study for Biomarker Discovery in Lysosomal Storage Disease (LSD).Metabolites · 2021Article
- Scoring functions for drug-effect similarity.Briefings in bioinformatics · 2021Review
- The case for open science: rare diseases.JAMIA open · 2020Review
- A guide to writing systematic reviews of rare disease treatments to generate FAIR-compliant datasets: building a Treatabolome.Orphanet journal of rare diseases · 2020Article
- DDIEM: drug database for inborn errors of metabolism.Orphanet journal of rare diseases · 2020Article
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Authors and funding
11 authors.
Funding
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Abstract
The number of available therapies for rare diseases remains low, as fewer than 6% of rare diseases have an approved treatment option. The International Rare Diseases Research Consortium (IRDiRC) set up the multi-stakeholder Data Mining and Repurposing (DMR) Task Force to examine the potential of applying biomedical data mining strategies to identify new opportunities to use existing pharmaceutical compounds in new ways and to accelerate the pace of drug development for rare disease patients. In reviewing past successes of data mining for drug repurposing, and planning for future biomedical research capacity, the DMR Task Force identified four strategic infrastructure investment areas to focus on in order to accelerate rare disease research productivity and drug development: (1) improving the capture and sharing of self-reported patient data, (2) better integration of existing research data, (3) increasing experimental testing capacity, and (4) sharing of rare disease research and development expertise. Additionally, the DMR Task Force also recommended a number of strategies to increase data mining and repurposing opportunities for rare diseases research as well as the development of individualized and precision medicine strategies.
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