Beyond Conventional Targets: Advancing Dietary Supplement Safety with LC-HRMS Suspect Screening and Non-Target Analysis Workflows
Introduction
The globalization of dietary supplement supply chains has introduced significant challenges in ensuring the safety, quality, and authenticity of products available on the market. With ingredients sourced from multiple regions and manufacturing processes varying widely, there is an increasing need for sophisticated analytical approaches to detect contaminants, adulterants, and other potentially harmful substances. Advanced analytical methods play a crucial role in identifying emerging contaminants, unexpected adulterants, food contact material migrants, and other unanticipated chemicals that may compromise regulatory compliance and consumer safety. As a result, suspect screening and non-target analysis workflows have become vital tools, providing robust methodologies to detect and identify both known and unknown compounds while offering a comprehensive characterization of the sample’s chemical fingerprint.
Overview
Traditional targeted analysis methods focus on detecting and quantifying a predefined set of analytes using reference standards, with detection parameters specifically optimized for these known substances. While highly effective for routine testing, targeted methods inherently limit the scope of analysis to known compounds and may overlook emerging contaminants or unexpected adulterants. In contrast, suspect screening enables the detection of a broad set of analytes that are potentially present or expected to be present in a sample, without requiring the use of reference standards. This approach significantly expands the range of detectable compounds and relies on advanced software tools, spectral libraries, and in-silico predictions to support identification. Compounds tentatively identified through suspect screening often require further verification using reference standards to confirm their identity. Taking an even broader approach, non-target analysis aims to detect and identify any unknown or unexpected compounds present in a sample without any prior knowledge. This powerful analytical strategy allows for the discovery of emerging contaminants, degradation products, novel adulterants or markers, but it also presents significant challenges due to the complexity of data and its interpretation. Advanced computational tools and statistical methods are necessary to process and analyze large datasets, making non-target analysis a sophisticated yet invaluable approach.
A variety of advanced analytical technologies support non-target analysis, including nuclear magnetic resonance (NMR), Fourier-transform infrared (FTIR) spectroscopy, gas chromatography-high resolution mass spectrometry (GC-HRMS), and liquid chromatography-high-resolution mass spectrometry (LC-HRMS). Mass spectrometry hyphenated to liquid chromatography is particularly useful in this field. State-of-the-art LC-HRMS instruments offer unparalleled sensitivity and selectivity, and the ability to analyze complex matrices, making it the gold standard for detecting non-volatile compounds in dietary supplement ingredients and finished products.
LC-HRMS Workflow
In a typical LC-MS workflow for suspect screening or non-target analysis, sample preparation involves a generic extraction process with minimal or no cleanup to preserve all potentially relevant sample components. A generic approach is applied in the chromatographic separation, where compounds are separated based on their physicochemical properties before being detected by the mass spectrometer. Slow elution gradients and chromatographic systems optimized for retaining compounds with different polarities enhance separation efficiency and coverage of the chemical space.
To maximize structural information for compound identification, MS data acquisition integrates full mass spectral data collection with fragmentation spectra generation. The combination of full-scan MS and data-dependent or data-independent MS/MS provides essential insights into the molecular composition and fragmentation behavior of each detected compound. Data processing is a critical and complex step that requires advanced software for deconvolution, feature alignment across multiple data sets, and normalization or scaling. Depending on the study’s objectives, statistical analyses, including univariate and multivariate approaches, can help highlight features of interest for further investigation.
The identification of detected compounds heavily depends on spectral libraries and extensive chemical databases containing data on thousands of known substances. Modern algorithms incorporated into data processing software allow for high-confidence elemental formula determination based on accurate mass measurements and isotope pattern analysis. These tools also facilitate automated searches of fragmentation records, enabling more precise compound identification.
The Schymanski scale is widely used to categorize identification confidence in non-target analysis. At the highest confidence level, a compound is confirmed when its exact mass, fragmentation pattern, and retention time match a reference standard. Probable structures can be proposed based on strong analytical evidence, such as spectral library matching, even in the absence of a reference standard. Tentative candidates are suggested when multiple possible structures fit the molecular formula and fragmentation pattern, but definitive confirmation is lacking. If only the molecular formula is determined, the structural identity remains uncertain, and at the lowest confidence level, only the exact mass of a detected feature is known without further structural details.
LC-HRMS Suspect Screening for Pharmaceutical Adulterants
The fraudulent practice of intentionally adding synthetic pharmaceuticals to dietary supplements for profit-driven enhancement of biological effects has become a growing concern. These adulterants may include prescription drugs, unapproved designer analogs, patented pharmaceuticals that never reached the market, or substances withdrawn due to severe side effects. While conventional screening methods target a relatively small number of known adulterants—such as phosphodiesterase type 5 (PDE-5) inhibitors, weight-loss drugs, anti-inflammatory agents, hypoglycemic compounds, or anabolic steroids—the scope of analysis remains limited.
By leveraging extensive spectral databases that contain information on thousands of therapeutic, counterfeit, and doping-related drugs, LC-HRMS-based suspect screening significantly expands the range of detectable adulterants. Additionally, this approach can uncover previously unrecognized structural analogs that may evade detection by traditional methods. With its ability to identify both known and unexpected pharmaceutical contaminants, LC-HRMS suspect screening represents a crucial tool in ensuring the safety and integrity of ingredients and dietary supplement finished products.
LC-HRMS Fingerprinting
LC-HRMS fingerprinting is a powerful tool for assessing the quality and authenticity of dietary supplements and their ingredients. This technique enables the comprehensive profiling of complex mixtures by capturing unique molecular fingerprints, which can be used to verify ingredient purity, detect adulterants, and ensure consistency across batches. By utilizing non-targeted metabolomics approaches, LC-MS can differentiate authentic botanical extracts from substituted or diluted products and identify synthetic additives. LC-MS fingerprinting relies on advanced statistical methods to interpret complex datasets. Univariate and multivariate statistical techniques, such as principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), are commonly used to distinguish authentic products from adulterated or low-quality supplements based on their metabolomic signatures. These methods help identify patterns, classify samples, and detect outliers that may indicate fraud or contamination.
Start the Conversation.
Reach out today to explore with our experts how LC-HRMS-based suspect screening and non-targeted analysis workflows can help to ensure the safety and authenticity of your dietary supplement ingredients and finished products.
Meet the Author
Dr. Lukas Vaclavik is a Technical Manager at Eurofins Food Chemistry Testing, specializing in contaminant and residue testing. In his current role, he leads initiatives to ensure the safety and quality of food products through advanced chemical analysis. Before joining Eurofins, he held a position at the Center for Food Safety and Applied Nutrition (CFSAN) at the U.S. Food and Drug Administration (FDA), where he contributed to regulatory science and research.
With a strong academic and professional background in chromatographic and mass spectrometric techniques, Dr. Vaclavik has authored or co-authored more than 40 peer-reviewed scientific publications. His research focuses on the detection and analysis of chemical residues, contaminants, and adulterants in food and related products.
Dr. Vaclavik holds a Ph.D. in Food Chemistry and Analysis from the University of Chemistry and Technology in Prague, Czech Republic.
