For decades, healthy eating recommendations have been designed for the population as a whole: what we should eat, how much and how often. These guidelines remain essential, but we now know that they do not tell the whole story. Two people can respond very differently to the same food or diet.
These responses are influenced by genetics, metabolism, gut microbiota, age, physical activity, sleep and even the presence of certain medical conditions. This is why one of the major advances in nutrition research involves taking individual variability into account in recommendations that, until now, have largely been based on population averages.
This is where precision nutrition comes in. At AZTI, we see biotechnology applied to health as a means of measuring the biological processes associated with nutrition, identifying relevant biomarkers and turning this information into tools for prevention, nutritional intervention and decision-making. Our distinctive strength lies in integrating the entire process: from biomarker identification and the design of human studies to the development and validation of nutritional solutions that can be applied in real-world settings.
At AZTI, we have been working in this field for more than a decade. We combine omics technologies, biomarkers, microbiome analysis, human intervention studies, artificial intelligence and digital tools to gain a better understanding of the relationship between diet and health. Our aim is to translate this knowledge into practical recommendations and solutions.
Understanding what happens inside the body
Personalising nutrition is not simply a matter of asking someone what they eat and adapting a diet to their preferences. The real breakthrough comes when we can objectively measure how their body is responding.
Omics technologies allow us to observe biological processes that, until relatively recently, remained hidden. Lipidomics studies the composition and function of lipids; metabolomics analyses the small molecules that reflect the body’s metabolic activity; and microbiome analysis allows us to characterise the communities of microorganisms living in our gut and understand how they influence health.
At AZTI, we integrate these approaches to build a more comprehensive picture of each person’s nutritional and metabolic status. One of our distinctive capabilities is erythrocyte membrane lipidomics – the analysis of red blood cell membranes – which we combine with metabolomics, microbiome analysis, clinical information, dietary data, lifestyle habits and data collected through digital tools, sensors and monitoring devices to develop a more accurate and personalised biological profile.
This approach has enabled us to identify different metabolic profiles even among people who might appear similar according to traditional indicators such as body mass index. This is because two individuals with the same clinical condition do not necessarily have the same underlying biological alterations or respond in the same way to a nutritional intervention.
This fundamentally changes how we approach conditions such as obesity. It is no longer simply a question of determining whether someone is overweight, but of understanding which metabolic characteristics define their condition and which nutritional or lifestyle strategy is likely to be most effective in each case.
The microbiome adds another piece to the puzzle
The microbiome is one of the fields that has most profoundly changed our understanding of the relationship between diet and health.
The microorganisms living in our gut help break down and transform nutrients, produce bioactive metabolites and interact with metabolic, immune and inflammatory processes. Both their composition and their activity also vary from person to person.
At AZTI, we combine microbiome analysis with lipidomics and metabolomics data, clinical information, and dietary and lifestyle data. The aim is not simply to collect more information, but to gain a more comprehensive understanding of each individual and identify which variables are genuinely useful for making better decisions.
After all, having more data does not necessarily mean knowing more. What matters is understanding how the different pieces of information relate to one another and what meaningful insights we can draw from them.
From observation to evidence: the value of intervention studies
Personalised nutrition is only meaningful if it is supported by scientific evidence.
That is why observational and human intervention studies are a fundamental part of our work. We carry out these studies in collaboration with hospitals, research centres, companies and sports organisations.
We have applied these methodologies in a wide range of fields, from obesity and oncology to healthy ageing and elite sport.
The SUMA project, for example, investigated precision nutrition in breast cancer survivors using lipidomics, nutrigenetics and gut microbiota analysis. As part of the project, we designed a nutritional intervention trial to assess how a personalised strategy could influence participants’ metabolic and nutritional status.
In professional sport, PIRESO combines membrane lipidomics, gut microbiota and microbial metabolites with information on the training and performance of Real Sociedad football players. The aim is to use biomarkers to tailor nutrition and supplementation to each player throughout the season.
These are very different contexts, but the underlying scientific approach is the same: measure, intervene, measure again and learn from each individual’s response.
Artificial intelligence to make sense of complexity
Precision nutrition generates vast amounts of information. Biomarkers, the microbiome, medical history, diet and lifestyle habits can produce thousands of variables for a single individual.
The real challenge is no longer collecting the data, but knowing how to interpret it.
This is where artificial intelligence plays a crucial role. Algorithms can identify patterns that are difficult to detect using conventional analytical methods, group people with similar characteristics, develop predictive models and integrate biological information with data from everyday life.
AZTI coordinates CoDiet, a European project exploring how artificial intelligence, dietary information, clinical data and multi-omics analysis can be combined to advance the prevention of diet-related non-communicable diseases.
Furthermore, infrastructures such as NutriHealth Corner make it possible to extend this approach by integrating omics technologies, digital tools, portable sensors and wearable devices, bringing precision nutrition closer to real-world applications beyond strictly research-based settings.
The next challenge: making personalised nutrition accessible
For years, one of the main questions surrounding precision nutrition has been whether it could move beyond highly controlled research projects and become an accessible tool that could be applied on a larger scale.
Today, that barrier is beginning to come down. The emergence of minimally invasive sampling methods, portable devices, the gradual reduction in the cost of omics technologies and advances in artificial intelligence are making it increasingly easy to obtain higher-quality information with less effort required from individuals.
At AZTI, we are working to integrate biomarkers, omics technologies, artificial intelligence, digital tools and monitoring systems to transform complex data into actionable knowledge. This enables us not only to develop nutritional recommendations, but also to identify patterns that can support the development of foods, services and health strategies for broader population groups.
The future of nutrition is not about replacing general dietary recommendations, which will continue to form the basis of healthy eating advice. The challenge is to introduce precision where it can deliver genuine benefits, helping to identify which interventions are most appropriate for each individual or population group.
Because the question is no longer simply which foods are healthy. We are learning to answer something far more complex: for whom, at what stage and under which circumstances can they help improve health?
