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Published on: November 24, 2016
Sweat as a diagnostic biofluid: analytical advances and future directions
Dayanne Mozaner Bordin1,2, Janice Irene McCauley1,2, Eduardo Geraldo de Campos3,4
1Atomic Medicine Initiative, University of Technology Sydney, Ultimo, NSW, Australia.
Journal of Pharmaceutical Analysis
|July 26, 2026
Summary
Sweat analysis offers a less invasive method for detecting drugs and biomarkers compared to blood or urine. Advances in wearable biosensors and artificial intelligence (AI) are enhancing sweat analysis for personalized medicine and real-time health monitoring.
Area of Science:
- Biomedical Engineering
- Analytical Chemistry
- Translational Medicine
Background:
- Sweat analysis is a recognized, less invasive alternative to blood and urine for toxicological and clinical assessments.
- It offers reduced endogenous interferents and easier sample collection.
- Advanced techniques enhance drug isolation, metabolite detection, and biomarker identification in sweat.
Purpose of the Study:
- To provide an overview of sweat as a diagnostic and monitoring biofluid.
- To highlight recent advancements in sweat biomarker detection.
- To evaluate sweat's potential for real-time physiological monitoring.
Main Methods:
- Review of traditional clinical and forensic applications of sweat analysis.
- Discussion of recent advancements in sweat biomarker detection technologies.
- Evaluation of emerging trends in wearable biosensors and AI for sweat analysis.
Main Results:
- Sweat analysis capabilities have expanded with advanced techniques for sensitive and accurate detection.
- Artificial intelligence (AI) and wearable biosensor technology are poised to revolutionize sweat analysis.
- Integration of AI with miniaturized electronics and wireless connectivity promises enhanced physiological monitoring.
Conclusions:
- Sweat analysis is a promising biofluid for diagnostics and monitoring.
- Wearable biosensors combined with AI will significantly impact personalized medicine and health monitoring.
- Further research into real-time sweat analysis holds potential for broader clinical applications.
