ArticleGenome medicine2024
scDrugPrio: a framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases.
Article in Genome medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 11 citations in OpenAlex.
- Decoding drug-responsive cell subpopulations in triple-negative breast cancer using single-cell multiomics.iScience · 2026Article
- Advances in nanotechnology for the diagnosis and management of autoimmune diseases.Asian journal of pharmaceutical sciences · 2026Review
- Cellular heterogeneity and multicellular mechanisms in the pathogenesis of late-life depression: insights from single-cell and spatial multi-omics.Frontiers in immunology · 2026Review
- Harnessing Single-Cell RNA-Seq for Computational Drug Repurposing in Cancer Immunotherapy.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Applications of digital twins in medicine.Nature biotechnology · 2025Article
- Digital twins as global learning health and disease models for preventive and personalized medicine.Genome medicine · 2025Review
- Towards the Next Generation of Data-Driven Therapeutics Using Spatially Resolved Single-Cell Technologies and Generative AI.European journal of immunology · 2025Review
- Opportunities for use of neuroimaging in de-risking drug development and improving clinical outcomes in psychiatry: an industry perspective.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024Review
- An interactive atlas of genomic, proteomic, and metabolomic biomarkers promotes the potential of proteins to predict complex diseases.Scientific reports · 2024Article
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17 authors at 7 institutions in 5 countries.
Funding
Abstract
backgroundIneffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs.
methodsHere, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs.
resultsscDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn's disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn's disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment.
conclusionsWe propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio's potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package ( https://github.com/SDTC-CPMed/scDrugPrio ).
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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.