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     Gel: 12%SDS-PAGE, Lysate: 40 μg, Lane 1-3: Rat kidney tissue, Mouse liver tissue and Human fetal liver tissue lysates, Primary antibody: P10246(RIDA Antibody) at dilution 1/600, Secondary antibody: Goat anti rabbit IgG at 1/5000 dilution, Exposure time: 15 seconds    

  
  

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     The image is immunohistochemistry of paraffin-embedded Human lung cancer tissue using P10246(RIDA Antibody) at dilution 1/65. (Original magnification: ×200)    

  
  

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     The image is immunohistochemistry of paraffin-embedded Human liver cancer tissue using P10246(RIDA Antibody) at dilution 1/65. (Original magnification: ×200)    

  
  

RIDA antibodies, developed as part of the Rapid Immunoassay for Dementia Antigens (RIDA) project, are specialized tools designed to detect biomarkers associated with neurodegenerative diseases, particularly Alzheimer's disease (AD). Emerging in the early 2010s, these antibodies were engineered to address the urgent need for early, non-invasive diagnostic methods in dementia research. Traditional diagnostic approaches often relied on post-mortem analysis or invasive cerebrospinal fluid sampling, highlighting a gap in clinical practice.

RIDA antibodies target key pathological proteins like amyloid-beta (Aβ) oligomers and hyperphosphorylated tau, which are critical in AD pathogenesis. Unlike conventional antibodies, they were optimized for high sensitivity and specificity in blood-based immunoassays, leveraging advancements in recombinant antibody technology and epitope mapping. This innovation aimed to enable earlier disease detection, monitor progression, and assess therapeutic efficacy in living patients.

Their development coincided with growing emphasis on precision medicine and biomarker-driven clinical trials. By 2018. RIDA-based assays showed promise in differentiating AD from other dementias in cohort studies. While not yet fully integrated into diagnostic guidelines, they represent a significant stride toward accessible neurodegeneration diagnostics. Current research explores their utility in combination with emerging technologies like digital ELISA and AI-driven data analysis, potentially reshaping dementia diagnostics and therapeutic development pipelines.