Artificial intelligence to detect unknown stimulants from scientific literature and media reports

Anand K Gavai,Lennert F.D Van Overbeeke,Ningjing Liu,Yamine Bouzembrak,Leonieke M Van Den Bulk,Hans Mol,Hans J.P Marvin,Lukas J Van Den Heuvel

doi:10.1016/j.foodcont.2021.108360

Anand K Gavai, Lennert F.D Van Overbeeke + Show 6 more

Open Access

https://doi.org/10.1016/j.foodcont.2021.108360

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Journal: Food Control	Publication Date: Dec 1, 2021
Citations: 5	License type: cc-by

Affiliation: Wageningen University & Research

Abstract

The world market for food supplements is large and is driven by the claims of these products to, for example, treat obesity, increase focus and alertness, decrease appetite, decrease the need for sleep or reduce impulsivity. The use of illegal compounds in food supplements is a continuous threat, certainly because these compounds and products have not been tested for safety by competent authorities. It is therefore of the utmost importance for the competent authorities to know when new products are being marketed and to warn users against potential health risks. In this study, an approach is presented to detect new and unknown stimulants in food supplements using machine learning. Twenty new stimulants were identified from two different data sources, namely scientific literature applying word embedding on > 2 million abstracts and articles from formal and social media on the world wide web using text mining. The results show that the developed approach may be suitable to detect “unknowns” in the emerging risk identification activities performed by the competent authorities, which is currently a major hurdle.

Highlights

The global dietary supplements market size was estimated at USD 140.3 billion in 2020 and is expected to expand at an annual growth rate of 8.6% from 2021 to 2028.1 Factors, such as rising health concerns and the changing lifestyle and dietary habits have been driving this growth in demand.1 Consumers find supplements attractive to compensate for imbalances of nutrients in their diet or unhealthy lifestyle, and to pre vent chronic diseases, among others (Biesterbos et al, 2019)
The approach developed for the identification of unknown stimulant compounds in food supplements consisted of i) “word embedding” of the relevant scientific literature complemented with ii) text mining the world wide web using the MedISys infrastructure
Since this study focused on finding stimulants, all words that were not chemical compounds were removed from the collected set by checking the words against the PubChem database

Summary

Introduction

The global dietary supplements market size was estimated at USD 140.3 billion in 2020 and is expected to expand at an annual growth rate of 8.6% from 2021 to 2028.1 Factors, such as rising health concerns and the changing lifestyle and dietary habits have been driving this growth in demand. Consumers find supplements attractive to compensate for imbalances of nutrients in their diet or unhealthy lifestyle, and to pre vent chronic diseases, among others (Biesterbos et al, 2019). A subgroup of food supplements are stimulants, which are agents (e.g., drugs) that produce a temporary increase of the functional activity or efficiency of an organism. Often in the consumer market they are used to treat obesity, increase focus and alertness, decrease appetite or decrease need for sleep (Carroll et al, 2006). These compounds are le gally regulated, illegal compounds are sold as food stimulants, such as the banned substance 1,3-DMAA in sport supplements being mar keted as an extract of Aconitum kusnezoffii (Cohen et al, 2018). Well-known enhancers are illegally added to supple ments, but experimental or even prohibited substances may be used (Cohen et al, 2018)

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