A New Era in Dietary Supplement Regulation: Sustainable Chemometric Approach for Quality Control of Four Dietary Ingredients in Slimming Preparations

Hassan, Said A; Abdelaal, Sarah H; El-Kosasy, Amira M; Morsy, Noha Fathy Elazab;

Abstract


By the end of 2024, the largest reorganization in the modern history of the U.S. FDA took effect. This overhaul included the establishment of the Office of Food Chemical Safety, Dietary Supplements, and Innovation (OFCSDSI), underscoring the growing need for stringent oversight of the dietary supplement (DS) industry. Phenethylamines stimulants are on regulatory monitoring lists, yet they remain available in the DS market. With this reshaping of the regulatory framework of DS, there is an increasing demand for specific and sensitive analytical methods to monitor and control such dietary ingredients. This study introduces chemometrics as a pivotal tool in the enhanced regulatory oversight of DS. Advanced spectrophotometric techniques, coupled with chemometric models, were employed for the simultaneous quantitation of 2-Phenethylamine, caffeine, p-Hordenine, and p Synephrine in complex slimming supplement formulations. Three multivariate models—Partial Least Squares-1 (PLS-1), Genetic Algorithm-Partial Least Squares (GA-PLS), and Genetic Algorithm-Artificial Neural Networks (GA-ANN)—were evaluated. Notably, the GA-based models (GA-ANN) outperformed PLS-1 in resolving spectral overlap without preliminary separation steps, even in the presence of formulation additives. These findings demonstrate the potential of chemometrics as viable eco-friendly alternative for chromatography in routine quality control of DS under the FDA’s new regulatory paradigm.


Other data

Title A New Era in Dietary Supplement Regulation: Sustainable Chemometric Approach for Quality Control of Four Dietary Ingredients in Slimming Preparations
Authors Hassan, Said A; Abdelaal, Sarah H; El-Kosasy, Amira M; Morsy, Noha Fathy Elazab 
Keywords Artificial Neural Networks;Caffeine;Dietary Supplements;Genetic algorithm;Partial Least Squares;Phenethylamines
Issue Date 2025
Publisher Elsevier
Journal Journal of Food Composition and Analysis 
Volume 148
DOI 10.1016/j.jfca.2025.108619

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