Multiclass Assays for Measuring Environmental Chemical Mixture Exposure: Analytical Methodologies and Applications in Exposomics Research

Background/Objectives: The exposome includes all environmental exposures throughout a lifetime and profoundly influences health and disease, reflecting the totality of environmental chemical exposures throughout an individual’s life, encompassing both natural and anthropogenic chemicals from external sources. Conventional methods for environmental chemical analysis have generally concentrated on individual representatives or substance classes; however, single analyte/class techniques are impractical for extensive epidemiological studies that require the analysis of thousands of samples, as anticipated for forthcoming exposome-wide association studies. This narrative review analyzes the evolution and implementation of multiclass assays for measuring ambient chemical exposure, emphasizing analytical techniques that provide the concurrent quantification of various chemical classes. Methods: This narrative review consolidates existing literature on multiclass analytical methodologies for measuring exposure to environmental chemical mixtures, encompassing mass spectrometry platforms, sample preparation techniques, chromatographic separation methods, and validation strategies for thorough exposure assessment in human biomonitoring research. The review includes liquid chromatography–mass spectrometry techniques, solid-phase extraction methods, and data analysis strategies for both targeted and non-targeted study. Results: Multi-class methodologies provide the concurrent quantification of compounds from many classes without the necessity for distinct conventional procedures, thus minimizing time, expense, and sample volume. The robustness of the method indicates appropriate extraction recovery and matrix effects between 60 and 130%, inter-/intra-day precision under 30%, and remarkable sensitivity with detection limits from 0.015 to 50 pg/mL for 60–80% of analytes in the examined human matrices. The methodology facilitates the concurrent identification of the endogenous metabolome, food-associated metabolites, medicines, home chemicals, environmental contaminants, and microbiota derivatives, including over 1000 chemicals and metabolites in total. Conclusions: These thorough analytical methods deliver the requisite performance for extensive exposome-wide association studies, yielding quantitative results and uncovering unforeseen exposures, thereby augmenting our comprehension of the chemical exposome, which is essential for advancing disease prevention in public health and personalized medicine.