AI revolutionizing precision nutrition for women can be effectively addressed with the adoption of its discovery
A significant barrier to personalized AI revolutionizing precision nutrition for women is that when we learn the effects of a diet, we do not know to whom these results apply. Using artificial intelligence and machine learning will try to better understand the relationship between nutrition and an individual’s biological, cultural, and economic profiles.
AI revolutionizing precision nutrition for women is an emerging area aimed at better tailoring diets to different people’s characteristics and circumstances to achieve better health outcomes. There is no “one-size-fits-all” approach when it comes to proper nutrition. Diet affects individuals or women in different ways. If one person eats a cookie, their blood glucose may spike. If another person eats that same cookie, their blood glucose may stay flat.
The various project will look at characteristics such as genetics, microbiome, blood profile, culture, geographical location, and socioeconomic status, among other variables, separately and in combination, to find out why everyone doesn’t react the same way to the same food choices.
These causal relationships that will analyze women, may not only help tailor diets to specific individuals based on their profile but may not only help tailor diets to specific individuals based on their profile but may also help individuals stick to certain diets long term, prevent chronic disease, and improve overall health in different populations.
Nutrition is fundamental to preventing chronic diseases like diabetes and obesity and to maintaining health. Yet changing guidance, such as on how egg consumption influences cholesterol and if salt intake leads to hypertension, makes it difficult for individuals to know how to act and for governments to create policies that can improve population health.
Scientific research consistently demonstrates that diseases may be delayed, treated, or even prevented and, thereby, health may be maintained with health-promoting functional food ingredients (FFIs). Consumers are increasingly demanding sound information about food, nutrition, nutrients, and their associated health benefits.
Consequently, AI revolutionizing precision nutrition for women is being formed around natural foods and FFIs, the economic growth of which is increasingly driven by consumer decisions. Information technology, in particular artificial intelligence (AI), is primed to vastly expand the pool of characterized and annotated FFIs available to consumers, by systematically discovering and characterizing natural, efficacious, and safe bioactive ingredients (bioactive) that address specific health needs.
However, FFI-producing companies are lagging in adopting AI revolutionizing precision nutrition for women for their ingredient development pipelines for several reasons, resulting in a lack of efficient means for large-scale and high-throughput molecular and functional ingredient characterization.
The arrival of the AI-led technological revolution allows for the comprehensive characterization and understanding of the universe of FFI molecules, enabling the mining of the food and natural product space in an unprecedented manner. In turn, this expansion of bioactive dramatically increases the repertoire of FFIs available to the consumer, ultimately resulting in bioactive being specifically developed to target unmet health needs.
With the recent exponential surge in information technology advancements, today’s consumers demand instant access to deeper product understanding unlike any generation before. For the food and nutrition market, this means that the next wave of economic growth will be driven by nutrition-based technology that empowers consumers to take better control of their health by accessing validated information about the beneficial effects of natural ingredients and supplements for various conditions.
Customarily, characterization comes after the identification of an FFI and encompasses the determination and description of biochemical, biophysical, and biological properties of the active molecule(s) with all of these, and especially the latter, allowing for assignment of health benefits to FFIs. Such characterization is usually performed with bioanalytical methods in the “wet laboratory” and provided information about key properties of FFIs when administered as a dietary component or as a supplement.
These properties concern safety profile, stability after (oral) ingestion and across gastrointestinal digestion, amenability to active or passive transport from the gut lumen across the brush border membrane into the bloodstream (systemic bioavailability), and availability in the target tissue (local bioavailability). Ultimately, this information provides a comprehensive understanding of mechanism-of-action, overall bioavailability, bio-efficacy, and therefore dosage of FFIs.
In particular, there is a need for standardization and transparency when it comes to health claims for additives produced by food and nutrition companies. Ultimately, consumers are currently pushing for more natural products, as some of the additives used in food processing and preservation have raised health concerns and triggered negative consumer perceptions.