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Data · dataset · 2026

Table 1_RNA therapeutics in rheumatoid arthritis, systemic lupus erythematosus, and systemic sclerosis: a compartment-aware translational framework.docx

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<p>Rheumatoid arthritis (RA), systemic lupus erythematosus/lupus nephritis (SLE/LN), and systemic sclerosis (SSc) remain major causes of chronic inflammation, disability, organ damage, and treatment burden despite therapeutic advances.

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RNA therapeutics offer programmable transcript suppression, network-level microRNA modulation, transient restoration of protective proteins, and targeting-ligand functions. Existing reviews largely catalogue modalities or individual delivery systems; this review instead asks whether a candidate forms an interpretable translational program across target biology, disease compartment, intended cell, productive intracellular access, direct target engagement, pathway pharmacodynamics, repeat-dose safety, and manufacturing feasibility.

RA is primarily a synovial immune–stromal delivery problem in which RNA programs must also demonstrate an advantage over effective biologic or targeted synthetic therapies. SLE/LN offers interferon, B-cell, co-stimulatory, microRNA, messenger RNA (mRNA), and complement opportunities, but therapeutic nucleic acids and carriers must not intensify nucleic-acid sensing, interferon activity, or complement-associated injury.

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SSc combines strong antifibrotic RNA biology with an accessible skin proof-of-mechanism window, whereas lung, vascular, and internal-organ programs remain more delivery-limited. We separate human pathway validation, RNA-platform evidence outside the target disease, disease-specific RNA evidence, and patient efficacy. Recent human complement-factor-B pharmacodynamic data strengthen the platform-level evidence but do not establish efficacy in RA or LN.

The most informative early trials will therefore be biomarker-enriched and mechanism-rich, with prespecified criteria that distinguish target failure from delivery, dose, endotype, or safety failure.</p>

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Disease 75% · Tabular 65%
Provenance · 1 source records, 9 field assertions
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NCL Dataoai:figshare.com:article/340695608 d agoJSON v1
FieldAssertionExtractorEvidence
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