A new review in the Journal of Pharmaceutical Analysis summarizes recent progress in using human sweat as a diagnostic biofluid. Sweat collection is noninvasive, accessible, and associated with fewer naturally occurring contaminants than blood or urine. Furthermore, technological advances are expanding the types of biomarkers that can be detected in this matrix.
Sweat testing is already established for cystic fibrosis (CF). The review notes that pilocarpine iontophoresis remains the standard method for stimulating sweat and measuring chloride, with concentrations above 60 mmol/L considered diagnostic. Newer iontophoresis platforms and Macroduct®-style devices aim to simplify sweat collection and improve consistency, particularly for infants and young children.
Beyond CF, several analytes commonly used in clinical practice can be detected in sweat. The review lists biomarkers such as glucose, β-hydroxybutyrate, electrolytes, inflammatory cytokines, and drug metabolites, along with their detection ranges and representative sensing platforms. Studies have shown a strong correlation between sweat glucose and blood glucose when proper sampling controls are applied, suggesting potential use for noninvasive diabetes monitoring. Wearable electrochemical sensors have also been developed to measure β-hydroxybutyrate, relevant for assessing diabetic ketoacidosis.
Sweat proteomics and metabolomics are emerging as additional diagnostic avenues. For example, proteomic analysis of sweat from individuals with active tuberculosis identified 26 proteins unique to TB patients, supporting the possibility of non-sputum-based biomarker discovery. Similar studies have reported sweat-derived protein differences in autoimmune and inflammatory conditions, indicating that eccrine gland secretions may reflect systemic disease processes.
However, several analytical challenges remain. Sweat contains relatively low analyte concentrations, and composition varies with skin site, hydration, environmental conditions, and sweat rate. Contamination from skin lipids or topical products can also affect results. Normalization of sweat volume – important for quantifying analytes – is still under development, with sodium currently investigated as a possible internal reference.
The review highlights ongoing advances in microfluidics, wearable electronics, and machine-learning-driven data interpretation. These technologies aim to move sweat testing from laboratory-based, endpoint measurements toward continuous, wearable sensing that could support point-of-care diagnostics and longitudinal monitoring.
Overall, the article concludes that sweat is gaining attention as a complementary diagnostic matrix. While technical obstacles remain, expanding biomarker detection and improvements in sensor platforms suggest increasing future relevance for metabolic, infectious, and inflammatory disease assessment.
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