Artificial intelligence (AI) has burst onto the scene in recent years with a significant proportion of manufacturing and product-based industries now using it to optimise their workflows. This trend can certainly be seen in the nutraceutical space, as ingredient developers, supplement providers, marketers and quality testers have all begun to jump on the bandwagon to improve their operational functionality.

Because AI technologies are highly flexible, they can be used in a range of contexts. Therefore, companies should determine where this technology may benefit their business and how it might be incorporated to get the most out of it. To discover more about how AI can optimise the day-to-day activities of those working in the nutraceutical industry, Annabel Kartal-Allen spoke to PIPA’s VP of Science & Customer Success Catarina Aubreu, and LEHVOSS Nutrition’s Head of Brands and Marketing, Teresita Rudà.

AI … helps us to analyse vast datasets of ingredients and their properties

Creating specialist ingredient synergies

The nutraceutical market is highly saturated, so companies must push the boat out more than ever in terms of quality and formulation to create standout products. One way they can do this is by developing specialist or coactive ingredients that target popular health aspects, including cognition, gut and immune health. “AI — machine learning technologies, generative AI and natural language processing — helps us to analyse vast datasets of ingredients and their properties, as well as their bioactivity, molecular structure and any potential synergistic effects,” explains Catarina.

She continues: “This allows us to identify patterns and associations that we would otherwise miss if we were mining and analysing information manually. It can also predict which of these compounds will perform better, allowing researchers to identify promising ingredient combinations without extensive laboratory testing.” 

Teresita believes that AI can also be a great time-saving tool in this context: “When combining ingredients into a nutraceutical formulation, the chosen extracts must be carefully assessed — which often requires a lot of investment in terms of research and time. Utilising AI in this context allows a company to filter out a significant amount of work, while working more efficiently. This can help businesses to quickly understand what ingredients work better together; and, from there, more specific research can be done.”

Although AI can be a highly useful tool for nutraceutical developers, Teresita warns that “there will always be a point when humans will need to determine what’s best.” Essentially, identifying plant extracts or active ingredients from a huge database can advise nutraceutical developers in terms of which way they should take their research … and what they should be focusing on to best cater to their target audience.

Developing unique flavour combinations

As well as facilitating the development of unique and personalised nutraceutical formulations, AI can help researchers to produce novel and more innovative flavours for their supplements. “AI can improve the process efficiency of flavour development, potentially cutting the typical 50–150 iterations down to much fewer,” states Catarina. “By making the flavour development process less based on trial and error and more systematic, companies can tap into the consumer market via AI-collated preference data to provide tailored flavour recommendations for specific demographics.”

“Flavouring is very subjective,” Teresita adds, “but certain combinations will generally appeal to some populations more than others. AI can support the process of coming up with unique flavour combinations — possibly offering more than a team of developers might think of — all while considering the trends seen in specific consumer groups. It can also help product formulators to sift through vast amounts of data, using this to influence their approach to flavour development.”

AI can optimise time-consuming and effort-intensive use cases throughout the value chain

Mapping and predicting consumer trends and preferences

As personalised nutrition becomes a topic of increasing interest in the nutraceutical world, there is a strong incentive for companies to tap into this potential gold mine, details Catarina: “AI can optimise time-consuming and effort-intensive use cases throughout the value chain; a great example of this is in horizon scanning during R&D through formulation optimisation. Utilising real-time consumer data can allow organisations to access truly personalised recommendations for specific audiences based on evidence, not assumption.”

In terms of supplement formulation, predictive modelling and machine learning can rapidly analyse and augment vast amounts of data from multiple sources — including genetic information, health records, dietary habits, physical activity levels and gut microbiome characteristics. This allows for a comprehensive understanding of an individual’s unique nutritional needs and health status — informing dietary strategies for the management of specific health conditions or chronic diseases.

Streamlining ingredient and supplement R&D

Once a company has developed an appropriate formulation for an ingredient or dietary supplement, the priority becomes proving that the product does what it says on the tin; this is when research comes in. Teresita believes that AI plays a crucial role in running successful clinical trials and studies. “Research may be a big investment, but it can significantly enhance the credibility of a nutraceutical product or dietary supplement ingredient. When designing a study, AI can help researchers evaluate their previous findings and estimate a trial’s probability for success,  while also helping them to find the best way to conduct such investigations in future endeavours.” 

“It will also enable scientists to determine what kind of cohort needs to be recruited for a given study. Overall, this kind of technology can save them a lot of time and resources during the research process.” Catarina echoes this sentiment, stating: “There are millions of plant food compounds; yet we only know about a fraction of them (approximately 400,000 have been identified to date). AI technology enables companies to discover bioactive compounds much more quickly and efficiently than using a manual approach.”

“Machine learning can also be used to predict undiscovered health benefits that known functional ingredients may have, while uncovering unexpected ingredient associations much more quickly and accurately compared with using traditional methods.”

“AI can offer new market opportunities for nutraceutical developers and manufacturers; it allows them to reduce the cost of testing their functional ingredients while also slashing the time to commercialisation by enhancing a company’s predictive capabilities.”

Optimising quality control

Catarina also highlights that AI can play a key role in quality control: “Through the analysis of chemical interactions, potential synergies and dosage optimisation, AI can help companies to accelerate the discovery of effective and safe nutraceutical formulations.” She adds: “This technology can also indicate ways in which businesses can improve the bioavailability — and thus the absorption — of nutrients, bringing new, effective and clean-label products to market.”

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She also stresses that post-production quality control can specifically benefit from the technology: “With AI, you can directly enhance the quality control of nutraceutical production. By analysing data from various stages of the manufacturing process, this technology ensures that employees will be aware of when a process can be optimised, while also allowing consistency in product composition, adherence to guidelines and specifications, as well as compliance with regulatory standards.”

Although AI can’t replace every process in a company’s daily workflow, it can assist them by streamlining their efforts and enhancing the way they work. When used correctly, AI can be a highly useful tool that benefits both a company and its associates.

A recent study reveals that social isolation and loneliness are linked to lower intake of essential micronutrients in older adults, raising concerns about their impact on healthy aging and the need for targeted dietary interventions.

Study: Social isolation, loneliness and low dietary micronutrient intake amongst older people in England. Image Credit: De Visu / Shutterstock.com

A recent Age and Ageing study determines whether social isolation and loneliness are associated with lower micronutrient intake.

Micronutrient intake in older adults

Micronutrients are essential for multiple biological functions; therefore, their deficiency can affect the health of individuals of all age groups. For example, potassium, magnesium, calcium, and vitamin D play important roles in bone health.

Vitamin E, B, and folate deficiencies have been associated with an increased risk of cognitive decline and cardiovascular events. Likewise, inadequate iron intake can negatively affect physical capabilities.

Adequate dietary micronutrient intake is essential for healthy aging. However, multiple cross-sectional and longitudinal studies conducted in high-income countries have revealed that older adults, irrespective of gender, have considerable dietary micronutrient deficiencies, particularly iron in individuals 65 years of age and older, as well as folate, vitamins B6, C, and E, calcium, and magnesium.

It is crucial to identify the different factors that impact dietary micronutrient deficiencies in older populations. Previous studies have shown that lower socioeconomic status, depressed mood, advancing age, social isolation, and loneliness increase the risk of dietary micronutrient deficiencies.

Social isolation is often associated with limited community activities, living alone, and infrequent socialization. Thus, many of these individuals are lonely due to the lack of companionship, which may lead to depression, coronary heart disease, dementia, disability, and mortality.

Several behavioral and lifestyle factors, including smoking, poor adherence to medical advice, and physical inactivity, are associated with loneliness. A 2023 review also revealed that social isolation is consistently linked with poor fruit and vegetable intake.

About the study

The current study investigates whether loneliness and social isolation are associated with micronutrient intake below recommended levels among people 50 years of age and older. Nine micronutrient contents were evaluated, including magnesium, calcium, potassium, folate, and iron, as well as vitamins C, B6, B12, and E.

The English Longitudinal Study of Ageing (ELSA) started in 2002 and comprised 12,099 men and women between 50 and 90 years of age. In Wave 8 of ELSA, which involved 3,771 individuals, data on social isolation and loneliness measures were collected between 2016 and 2017.

Social isolation was measured using a scoring system ranging from zero to five, with higher scores indicating greater isolation. This index was also associated with unhealthy lifestyles, mortality, and disability.

Loneliness was measured using a scoring system, with scores ranging from three to nine, the latter reflecting greater loneliness. Diet was assessed using a questionnaire that included over 200 food and beverage items.

Wave 9 was conducted between 2018 and 2019 and focused on covariate factors, including age, gender, smoking status, education, marital status, and ethnicity, as well as nutrition assessments.

Study findings

A total of 2,024 women and 1,689 men with an average age of 68 years were included in the current study, most of whom were White, with a mean age of completing schooling being 16.8 years. Approximately 28% of the study cohort continued their education beyond 19 years of age.

About 6% of the study participants were smokers, whereas 17.2% reported impaired activities of daily living. The average daily calorie intake of the participants was 2,009 kilocalories (kcal).

Social isolation and loneliness were weakly correlated. After adjusting for age and gender, total energy intake was not associated with social isolation and was weakly negatively associated with loneliness.

Most study participants did not meet the recommended micronutrient levels. Furthermore, a limited number of participants consumed dietary supplements, as 4.2% and 13.7% took iron and vitamin C supplements, respectively.

Social isolation was associated with an increased risk of low consumption of five out of nine micronutrients, including vitamin B6, folate, magnesium, vitamin C, and potassium. A marginal association was identified between social isolation and iron intake.

Basic models that were adjusted for age, gender, and total energy revealed that loneliness was associated with folate, magnesium, iron, potassium, vitamin C, and vitamin E intake. However, none of these associations were observed following adjustment for physical activity education, ethnicity, marital status, and smoking. Sub-group analysis revealed an association between loneliness and vitamin C intake in the fully adjusted model in younger study participants.

Food insecurity and difficulty accessing stores to buy healthy food due to mobility issues were not associated with dietary micronutrient deficiency in older adults.

Conclusions

The current study indicated that the older population in England consumes dietary micronutrients in quantities lower than the recommended levels.

Social isolation also increased the risk of consuming low levels of magnesium, folate, potassium, and vitamins B6 and C. Marital status, smoking, educational attainment, and physical activity only contributed to micronutrient deficiency when they were included as covariates.

Taken together, these findings emphasize the need for targeted dietary strategies for men and women with minimal social contacts and limited involvement in community-based social activities.