# Analytical Methods for Melatonin Quantification: Advances, Challenges, and Clinical Applications

## TL;DR

This paper reviews methods for measuring melatonin in biological samples, comparing their accuracy, cost, and suitability for clinical use.

## Contribution

The paper provides a comprehensive comparative analysis of melatonin quantification techniques, highlighting new developments and guiding method selection.

## Key findings

- LC–MS/MS is the most accurate but costly method for melatonin detection.
- Emerging biosensors and hybrid platforms offer promising alternatives for portable and sustainable analysis.
- Immunoenzymatic methods are suitable for large-scale studies but lack precision.

## Abstract

Melatonin, an indoleamine crucial for regulating circadian rhythms, sleep–wake cycles, and immune–endocrine homeostasis, is present in biological fluids at extremely low concentrations, making its quantification analytically challenging. This narrative review provides a critical comparative assessment of current methodologies for melatonin determination across various biological matrices—plasma, urine, saliva, breast milk, and hair. The discussed techniques include immunoassays, colorimetric and spectrophotometric methods, chromatographic–mass spectrometric platforms (LC–MS/MS, UHPLC–MS/MS), and emerging biosensors. Each approach is evaluated regarding analytical sensitivity, specificity, reproducibility, cost, and clinical applicability. While immunoenzymatic and colorimetric techniques offer accessible, low-cost solutions for large-scale or preliminary studies, LC–MS/MS remains the benchmark for reference analysis, providing sub-picogram detection limits and multiplexing capability. However, its high cost, procedural complexity, and inter-laboratory variability limit routine implementation. New developments, including molecularly imprinted polymers, dispersive microextraction, and nanomaterial-based biosensors, suggest a shift toward hybrid, sustainable, and portable analytical platforms. By synthesizing recent methodological advances and identifying key limitations, this review aims to guide researchers and clinicians in selecting the most appropriate analytical approach for clinical, pharmacological, and circadian biomonitoring applications.