Nutrition is not an exact science and still has a lot to be discovered. This is how it stands as we speak, and it is not great news. Due to the lack of precision, efficacy and impact we see in Nutrition today, we leave the doors open to anyone that has little understanding of the subject and a strong interest to be able to say their opinion, no matter how wrong that is. If a Doctor or a registered dietician is not able to give you the desired results where health improvements can be measured with clear KPIs, why should you listen to them more than your neighbor that managed to lose 20 kg in just 6 months changing diet? Or for the matter, why shouldn’t you just follow what your preferred influencer is saying?

Nutrition is still a very subjective matter and the causes of this are easy to identify: A. an inefficient scientific approach, B. lack of data and KPIs and C. Obsolete regulatory landscape.

    Due to the research approach mentioned above, it is not possible to create valuable data while other useful data are overlooked just because traditional research settings are not used. In addition, it is still unclear how to analyze the multifactorial interactions, as well as the misalignment in the scientific community on which data are valuable. Are genetics important? Should environmental factors impact nutritional needs? Is physical activity something to take into consideration? Is Keto safe? No-one can really make a definitive statement as research is frequently contradictory.


    The tables and research data that we are using to determine the nutritional daily requirement for individuals did a great job after the second world war, when people suffered from major nutritional issues, like scurvy. Today’s women and men are facing very different issues, such as overconsumption of macros and lack of micronutrients. While in the past we were dealing with lack of nutrients, today we are dealing with an abundancy of poorly nutritionally dense products. Creating a clear point of reference for pregnant women basing it on a study made in Indonesia in the 90’s is probably not the best way to state the needs of a women working 3 jobs in New York in 2020 during a virus pandemic.

    We cannot ask regulators to be innovative, at the end of the day they are working with a highly bureaucratical structure that wants a clear standard. Unfortunately, in Nutrition the One Size Fits All approach doesn’t work and we know it.


    The good news is that we are finally accepting that the methodology used so far is weak and a new paradigm is surfacing from the confusion around Nutrition – we are talking about Personalized nutrition.

    Personalized Nutrition is the exact opposite of the “One Size fits All” concept and states that we cannot all have the same nutritional target, and that those targets need to be adaptable not just based on our age but also on our genetic base and our lifestyle. In fact, if we don’t consider and merge these two macro areas into Nutrition, the benefits are sparse. Nutrition can only be personalized and slowly we will only speak about a Nutritious diet as a personalized one.

    This new paradigm will see a complete opposite flow of data. Today, the current approach is to apply the same nutrition rules to everyone, despite past research having a limited number of participants. Tomorrow, data will be collected from each individual to help us define nutrition rules. It is a humbling exercise that requires listening, rather than making hasty arguments why one hypothesis is better than another one. It will be, hopefully a wiser approach and for sure, result in a more knowledgeable world.


    In this new, wiser world, digitalization, artificial intelligence and machine learning will support the building of the new unbiased science. In this world data are king, and it is as much about small data aggregating into big data.

    Today we see the surge of hundreds of apps and digital services a. collecting your meals, b. suggesting diets that support your goals and preferences c. evaluating your sport performance and d. forecasting potential health issues. This list is partial, and it is here only as an example, that said all of them are trying to build suggestions or indicating to the individual, products that supposably are helping in achieving individual goals.

    This is good news, because those tools are fed by data and improve as the data flows into them. A starting model (the model that applies to the user at the beginning) will learn, change and improve, slowly becoming the best model that one can have.

    It is also good news that these models (call them AI, algorithm or as you prefer) work in a very meritocratic way: the more data are inserted the better they become. Where else in society you can find something more merit driven than that?

    For once data are used to help the overall health of individuals and not to feed their hunger to sell marketing campaign or products. Tools are never good or bad, they are just tools. The use we do with them makes the whole difference. Imagine what we could achieve if we were using the artificial intelligence at the base of Facebook and/or Google recommendations to make people better, not just in the knowledge of health but also in values like tolerance and inclusion.


    Athletes and sport are where the majority of innovation is coming when it comes to this topic. For an athlete, the possibility of obtaining marginal gains from nutrition makes the whole difference between winning the Tour de France or having a very bad day on the mountains due to a gastric crisis. The fact of not getting Covid-19 (or any other virus for the matter) because the immunity system is iron strong may make the difference between participating to an Olympiad or staying home and switching career.

    I have the pleasure of working on a daily basis with athletes and they are like everyone else: they enjoy their habits; they question headlines in nutrition science, and they don’t really want to waste time in nonsense. However, they have a stronger interest in trying for the above-mentioned reasons and once they see results, they keep pushing. Athletes (professional and amatorial one) are the early adopter and main driver of personalized nutrition. Long life to them.


    People like me, all over the planet are trying to create digital community driven by the same idea that improvement in humankind is still possible (and needed). We cannot just be healthier, quicker and stronger; we can also be wiser, open minded and inclusive if we drive our choices and development with objective data. In a Time where the world looks bigger and more divided than 4-5 years ago, could it be digitalization and Personalized Nutrition that will save us all?



    Altrove Innovation | Switzerland


    The scientific method and approach we use to validate the efficacy of a nutritional approach/diet/substance is the same used in pharma and health research. We check and validate efficacy through double blind clinical trials looking for objective sign of the theory we are trying to confirm. This approach, that works very well for blockbuster medicine and pharma molecules has very little impact with nutrition. Because nutrition is a multifactorial subject that requires to thoroughly isolate the specific factor we are studying (and this is extremely challenging using humans as study group) and because Nutrition has an effect on long term, the traditional approach to science is not working well in our beloved subject.