ImmunoINSIGHTS™ autoantibody biomarker discovery and analytical engine
The most comprehensive human antigen library and advanced platform for autoantibody / antibody biomarker discovery leading, to more effective and safer treatments for patients.
Our revolutionary platform and analytical engine, ImmunoINSIGHTS™ is designed to give access to more than 8,000 human antigens across various biologic samples in very low volume (50 µl), provides an extensive coverage of the proteome, translating into a powerhouse of biomarker insights to better understand the immune response to therapies in clinical projects.
WHY CHOOSE ImmunoINSIGHTS?
Developed and curated by a team of immunologists, our proprietary platform offers high content biological insights and analytics powered by proprietary algorithms, models and deep knowledge mining solutions.
- Largest Human Antigen Library
- The world’s most comprehensive human antigen library with 8000 antigens ready for interrogation
- Minimal Sample Volume
- Requires small sample volume, 50 µl per sample (serum, plasma and others)
- Bioinformatics & Data Science
- Advanced data insights, analytics and the flexibility of multiomics data integration
- Robust & Reproducible
- High throughput bead-based Luminex multiplex technology capable of performing simultaneously detection of hundreds of targets in a single sample depending on panel design
- Automated robotic workflows that handle large numbers of samples
- Rapid & Reliable
- Tailored to your projects and timelines
- Panel Customization
- Unique and custom-made panels tailored to specific studies
- Ongoing partnering and communications
Explore Oncimmune’s ImmunoINSIGHTS™ services & disease-specific panels
- ImmunoINSIGHTS™ Discovery more>
- ImmunoINSIGHTS™ Targeted panels and arrays more>
- Bioinformatics & Data Science more>
• Identify novel target molecules
• Disease characterization
• Understand the immune response to disease (e.g. COVID-19)
• Predict response to treatment and immune-related adverse events (irAEs)
• Stratify patients into clinically relevant sub-groups
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