The growth of the personalized nutrition market has been powered by the growing consumer interests in individualized products and services, and recent advances in diagnostics and tracking, which allow individuals to discover information about their key health and wellness markers. This information can be used to help create personal recommendations for diet and supplement plans, and lifestyle coaching, rather than relying only on generic population-based guidelines to improve health benefit outcomes for individuals.
For businesses looking to break into the personalized nutrition space, navigating the considerations around developing targeted solutions can be challenging. As personalized nutrition gains wider acceptance, it’s important that the development of related nutrition products and services follow evidence-based science. Only then can personalized nutrition fulfil its potential to have a positive impact on a large scale. Until now, the lack of a well-accepted definition or guidelines for working within personalized nutrition has created barriers for establishing its credibility and efficacy, making it harder for businesses to gain traction for their solutions in the market.1
To help establish a clear way forward for personalized nutrition, a panel of multidisciplinary scientists has developed a set of suggested guidelines that focus on the quality of data and diagnostic methods used in personalized nutrition approaches.
The starting point involved proposing a cleardefinition of personalized nutrition on which the guidelines can be based:
“Personalized nutrition uses individual-specific information, founded in evidence-based science, to promote dietary behavior change that may result in measurable health benefits.”1
Nate Matusheski, Ph.D., Lead Scientist, Personalized Nutrition & Dietary Supplements at DSM Nutrition Science & Advocacy, was involved in the development of the guidelines. In our latest ask-the-expert interview, he discusses the importance of the new guidelines and how they can support the development of commercially available solutions.
The health and wellness needs of the target audience should be closely evaluated before the implementation of any personalized approach. It’s also important to consider ways to make personalized nutrition more accessible and affordable to achieve a wide-reaching positive change.
Diagnostic measures should follow scientific best practices and validated against reference methods or established as relevant to a specific health benefit.
Reasonable data quality parameters should be established from the outset of any research. For subjective data, or in cases where the individual is contributing their own observations or information, data need to meet a high quality standard to be included in any reference set used for wider applications.
Any intended effect should have a plausible biological explanation and therefore be accurately validated. Predictive models must also be validated and be able to demonstrate acceptable predictive performance before being widely used.
Studies that account for variable biological factors such as the gender and physical behaviors of participants have a greater potential to detect effects on an individual level and therefore a greater understanding of the potential for personalized nutrition.
Any claims about the effects of personalized nutrition should be based on scientific and peer-reviewed evidence.
To support the adoption of personalized nutrition on a wider scale, diagnostic tools should be appropriate for the user’s capability and level of understanding. If tests are too complicated, the data quality and accuracy may be affected. For example, self-reporting portion size for a nutrition assessment may be skewed by the individual’s own perception of what constitutes a portion.
Advice or dietary changes recommended to healthy users should still fall within (and not contradict) generally accepted guidelines, such as Dietary Guidelines for Americans or Food-Based Dietary Guidelines for the EU.
The outcome of any personalized nutrition approach should not be over or understated and any recommended measures should only be made if there is clear evidence of the benefits to the user.
Any data collected as part of a personalized nutrition program should be stored, used and processed responsibly. The security, anonymity and transparency of data usage is critical, and it should always be made clear to the individual how their data should be used exactly.
To read more about the guidelines, download the paper: ‘Guiding Principles for the Implementation of Personalized Nutrition Approaches That Benefit Health and Function’.
As well as providing assurances to consumers following personalized nutrition programs, the guiding principles provide the foundations of a sound business model for companies looking to enter the personalized nutrition space. As consumers increasingly expect nutrition products that are tailored to their unique needs, DSM is committed to powering the development of personalized nutrition solutions from concept development and nutrient premixes through to turnkey solutions including individualized product manufacturing.
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