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Biomarkers to predict, prevent, and treat persistent pain: omics
Mark R Hutchinson1,2, Daniel Barratt1, Charlotte H Johnston1
1School of Biomedicine, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, Australia.
Pain
|October 14, 2025
Summary
Persistent pain requires advanced biomarker technologies for personalized treatment. This framework integrates multi-omics, quantum sensing, and AI for precise, accessible pain management solutions.
Area of Science:
- Biomedical Engineering
- Neuroscience
- Computational Biology
Background:
- Persistent pain is a global health issue needing better diagnostic and treatment tools.
- Current biomarkers are limited; a holistic approach integrating multiple dimensions of pain is necessary.
Purpose of the Study:
- To propose a framework for precision pain medicine using innovative technologies.
- To enable personalized prediction, prevention, and treatment of chronic pain.
Main Methods:
- Utilizing multi-omics data (genomics, proteomics, metabolomics, etc.) to map neuroimmune pathways.
- Employing emerging quantum sensing technologies for real-time, multimodal pain assessment.
- Applying transparent machine learning and explainable AI for complex data analysis.
Main Results:
- The proposed framework integrates molecular, emotional, cognitive, functional, and social pain dimensions.
- It facilitates high-resolution mapping of pain chronification pathways.
- It enables rapid feedback for actionable clinical outcomes.
Conclusions:
- A measurement-enabled understanding framework can advance precision pain medicine.
- Interdisciplinary innovation is key to comprehensive and accessible pain management.
- This approach mirrors the transformative impact of genomics and immunotherapy in cancer care.
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