Computational Identification of Repurposable Drug Candidates for Psoriatic Arthritis via Single-Cell RNA Sequencing of Synovial Tissue

Computational Identification of Repurposable Drug Candidates for Psoriatic Arthritis via Single-Cell RNA Sequencing of Synovial Tissue | Zenodo Skip to main Communities My dashboard Log in Sign up Zenodo is currently experiencing slowness and intermittent outages due to heavy automated traffic from bots and AI crawlers. We are aware of the problem, and our team is focused on stabilizing the service. Thank you for your patience. Published May 4, 2026 | Version V2 Patent Open Computational Identification of Repurposable Drug Candidates for Psoriatic Arthritis via Single-Cell RNA Sequencing of Synovial Tissue Authors/Creators Ritschel, Glen Charles (Researcher) 1 Claude (Researcher) 2 Show affiliations 1.

Ritschel Research 2.

Anthropic Description This provisional patent specification describes a computational drug repurposing pipeline applied to publicly available single-cell RNA sequencing data from human psoriatic arthritis (PsA) and rheumatoid arthritis (RA) synovial tissue biopsies (GSE200815; Floudas et al., Ann Rheum Dis 2022). After quality control filtering, 48,201 cells were analyzed using scVI batch-corrected dimensionality reduction and Leiden clustering, identifying 11 synovial cell types including lining fibroblasts (PRG4+/MMP3+), sublining fibroblasts (THY1+/CXCL12+/DKK3+), SPP1+ macrophages, endothelial cells, pericytes, and lymphoid populations. Wilcoxon differential expression analysis identified 467 genes upregulated in PsA versus RA, prominently including MMP3, FN1, PRG4, VCAM1, HTRA1, AXL, DDR2, and PDGFRA. ChEMBL bioactivity screening identified 11,910 drug candidates; the top 2,000 were assessed for novelty via PubChem, all classified as NOVEL for the PsA indication. Top candidates include CHEMBL5653589 (score 79.24, targeting HSPA5/ER stress and ZMYND8 epigenetic regulation), foretinib (50.03, AXL/DDR2/PDGFRA axis), nintedanib (38.72), prinomastat (30.52, MMP1/MMP3 inhibitor), and dasatinib (29.40, DDR2/PDGFRA). CHEMBL5653589 represents a pan-disease signal independently identified across seven scRNA-seq pipelines spanning neurodegeneration and autoimmune disease. Inventors: Glen Charles Ritschel, Ritschel Research, Tega Cay SC; Claude, Anthropic, San Francisco CA. Files Files (20.8 kB) Name Size Download all Patent43_PsA_Spec.docx md5:aa3eab0d49a3c7934318e5d8ac238506 20.8 kB Download Additional details Dates Updated 2026-05-04 v2: Corrected inventorship attribution 82 Views 12 Downloads Show more details All versions This version Views Total views 82 49 Downloads Total downloads 12 6 Data volume Total data volume 242.3 kB 125.1 kB More info on how stats are collected.... Versions External resources Indexed in OpenAIRE Communities Keywords and subjects Keywords psoriatic arthritis drug repurposing single-cell RNA sequencing scRNA-seq synovial tissue fibroblast macrophage MMP3 DDR2 AXL PDGFRA CHEMBL5653589 foretinib nintedanib dasatinib prinomastat scVI ChEMBL computational pharmacology provisional patent Details DOI DOI Badge DOI 10.5281/zenodo.20030609 Markdown [](https://doi.org/10.5281/zenodo.20030609) reStructuredText .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.20030609.svg :target: https://doi.org/10.5281/zenodo.20030609 HTML <a href="https://doi.org/10.5281/zenodo.20030609"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.20030609.svg" alt="DOI"></a> Image URL https://zenodo.org/badge/DOI/10.5281/zenodo.20030609.svg Target URL https://doi.org/10.5281/zenodo.20030609 Resource type Patent Publisher Zenodo Rights License Creative Commons Attribution 4.0 International The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited. Read more Citation Export Technical metadata Created May 4, 2026 Modified May 4, 2026 Jump up About About Policies Infrastructure Principles Projects Roadmap Contact Blog Blog Support Help FAQ Developers REST API OAI-PMH Contribute GitHub Donate Funded by Powered by CERN Data Centre & InvenioRDM Status Privacy policy Cookie policy Terms of Use This site uses cookies. Find out more on how we use cookies Accept all cookies Accept only essential cookies

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