This report ispart of the Work Package (WP) 1 of the PREVENTOMICS project. The aim of this report is to find out consumers’ opinions about and attitude towards personalizednutrition, the tools used to arrive at this personalisednutrition and the use of Apps and digital platforms. We will also study the requirements that an App or platform must meet to be in line with data protection regulations or the GDPR. The data protectionis ahighly relevant topic. And even more so when working with health data, personal data classified as highly sensitive.

D1.2 Consumers Report

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The scope of this deliverable is to describe the analysis conducted and the outputs obtained in the definition of the Minimum Viable Product (MVP). This report provides an overview of the main features of the PREVENTOMICS solution as well as provide actionable insights for PREVENTOMICS technological/service development phase. This document defines some of the fundamental assumptions on how PREVENTOMICS solution has to be developed according the user’s expectations and market’s needs.

First, this document describes the market research conducted among some of the project partners. Second, it shows, after having defined the target customers, hypothesis about what customers want and expect from the PREVENTOMICS solution. Third, it provides a framework for prioritising the project solution features. After having showed an overview of the market needs, the document describes the competitor analysis conducted to see what our competition looks like. Finally, the document describes how to address the real pain points that exist in the market and presents some of the learning cards collected so far.

The aim of this deliverable is to provide objective information on the actual diet of European consumers through the analysis of biomarkers of intake of food groups and specific foodstuffs. This information will be provided upon analysis of the samples provided by EURECAT and the samples of the 4 PREVENTOMICS intervention studies that will be conducted, once an adequate sample size has been achieved and the results have been validated. This deliverable highlights the utility of the developed methodological platform to reach an objective dietary assessment though biomarkers of food intake.

This deliverable includes a selection of the biomarkers of food intake that have to be further validated and eventually included in the final version of the PREVENTOMICS Decision Support System (DSS) to allow the identification of the dietary habits of the subjects involved in the 4 PREVENTOMICS RCTs. Therefore, all the operational and decision processes that lead to the list of candidate biomarkers of food intake are illustrated. The relation between food intake biomarkers and food categories is also explained.

The scope of the deliverable is to outline:
a) To determine the range of reference values for each classic biomarker on the basis of bibliographic data and own research.
b) Selection of complete set of classic biochemical variables related to health status which will be determined for the integration with metabolomics and genetics variables in individuals participating in PREVENTOMICS pilot studies.

In order to assess the ranges of classic clinical biomarkers associated with metabolic and inflammatory complications of obesity, a review of the literature was made. In addition, on the basis of research results obtained from earlier projects, ranges of standards for classic variables for the Polish, British and Spanish populations were estimated. Currently, EURECAT is analyzing the circulating levels of these biomarkers in blood and urine samples of about 200 non-obese healthy and 150 obese unhealthy volunteers Denmark (PROKA study) and The Netherlands (The Maastricht Study). Biomarker reference values are being estimated in metabolically healthy non-obese subjects as well as in metabolically healthy and metabolically unhealthy obese individuals. The deliverable 2.3 provides key output for WP3, WP4 and WP5 enabling the reasoning and decision support system. The protocols for the collection of biological material for laboratory determinations were agreed with the PREVENTOMICS partners. Biomarker determination methods have been developed and agreed by PREVENTOMICS partners also, which is reflected in the SOPs attached to the report.

Increasing evidence over the last decade has revealed the critical role of the gut microbiota in health and disease. Many chronic pathologies have been associated with gut microbiota imbalance in its composition, diversity and functional capacity, like obesity. 

Diet intervention are still the most effective way to prevent and treat obesity and overweight. Diet patters changes can modulate the gut microbiota as the diet is the primary driver affecting the microbiota composition. Therefore, weight loss responses could be in part affected by microbiota, in composition and in metabolic functions performed by intestinal bacteria such as colonic fermentation responses, energy extraction of food and production of microbial metabolites. 

In the PREVENTOMICS project, three intervention studies in different locations have been carried out following the same experimental design. Volunteers were divided into three intervention groups: Control (CT), Personalized Nutrition (PN) and Personalized Plan (PP). The volunteer’s microbiota has been characterized at the start of the intervention (V1) and at the end of the intervention (V2). PP in Spanish pilot was the intervention which has led to major changes in the microbiota composition. Moreover, 9 bacterial genera were found to have a differential abundance in the PP group, most of them short chain fatty acids (SCFA) producers. Other differential abundance genera were found in the other groups, CT and PN. 

In addition, a faecal microbiota transplantation (FMT) in mice was performed with the aim to investigate whether the microbiota of post-intervention volunteers has the capacity to influence the phenotype, microbiota and metabolome of an overweighted humanized murine model. Significant changes were found in the metabolome of animals at the endpoint of the experiment but not significant differences in body weight loss was observed. 

The scope of the deliverable D2.5 is to assess the technical feasibility of analysing each of the biomarkers to establish the final set of biomarkers included in PREVENTOMICS model in WP3 and to be used for the pilots’ deployment in WP5. 

This report describes a preliminary version of the Decision Support System (DSS) designed to generate the personalized nutrition recommendations from users’ multi-level data. First, an overview of the DSS architecture and a detailed description of all its components is provided. Second, we present the data analysis conducted to define and validate, together with the expert’s knowledge, the DSS processes related to the assessment of a user metabolic health. Third, we specify the technologies used for the system development. Finally, final considerations and next steps are outlined

This report describes the consolidated version of the Decision Support System (DSS) designed to generate the personalized nutrition recommendations from users’ multi-level data and presented, in its preliminary version, in Deliverable 3.2.

First, an overview of the final DSS architecture and a description of all its components is provided. Second, we present the outcomes of the DSS model on a dataset from previous study. Third, we specify the technologies used to develop the system and its integration in the PREVENTOMICS Platform. Finally, final considerations and next steps are outlined.

The PREVENTOMICS Nutritional Recommender System (NRS) provides a holistic environment that integrates all required functionalities for managing PREVENTOMICS user data, processing and generating nutritional recommendations by leveraging the PREVENTOMICS DSS (Decision Support System) and communicating these recommendations to third party applications. The NRS provides a set of functionalities that allow: (i) nutritionists to register new users, fill in user data, as well as generate and view the nutritional recommendations; (ii) technicians/lab users to upload the results of urine/blood/saliva tests so that nutritional recommendations can be generated; (iii) end-users to view the data that are stored in the NRS as well as answer sets of PREVENTOMICS questionnaires which provide information related to their dietary habits, food restrictions, and information required to generate personalized behavioural change programs; (iv) third party apps to connect to the NRS system and fetch the nutritional recommendations generated by the PREVENTOMICS DSS through secure and well-defined programming interfaces. The apps can then use these recommendations to tailor for example foods (ALDI case), recipes (SimpleFeast case) and diets (MetaDieta case). This deliverable provides the details of the NRS functionalities and API interfaces.

The scope of this deliverable is to describe the outcomes of Task 4.2, named “PREVENTOMICS in retailer apps”. This deliverable provides the functional specifications of the main features of the PREVENTOMICS technological/service development phase. More specifically the deliverable provides the details on the final design of the solution developed by EURECAT as well as all the functionalities involved in this solution. The activities described in this deliverable have been focus on meet mainly the requirements illustrated on Task 1.3 “Minimum Viable Product” and Task 4.1 “PREVENTOMICS platform design and communication interfaces specification”.

Throughout the present document, the functional and technical aspects have been described. First, this document describes the ALDI microsite web and the developments carried out during Task 4.5.This document illustrates the ALDI microsite web system. Finally, a description of the tests and demonstrations performed is presented.

The scope of this deliverable is to present and illustrate the outcome of deliverable D4.3, “Simple Feast’ server back-end integrating PREVENTOMICS”. This deliverable provides an overview of the main features of the recipe app and illustrates how easy a user integrates with the PREVENTOMICS platform.

The scope of this deliverable is to describe the outcomes of Task 4.4, named “PREVENTOMICS in software for professionals”. This deliverable provides the functional specifications of the main features   of the PREVENTOMICS technological/service development phase. More specifically the deliverable provides the details on the final design of the solution developed by METEDA as well as all the functionalities involved in this solution. The activities described in this deliverable have been focus on meet mainly the requirements illustrated on task 1.3 “Minimum Viable Product” and Task 4.1 “PREVENTOMICS platform design and communication interfaces specification”.

Throughout the present document, the functional and technical aspects have been described. First, this document describes the MetaDieta architecture and the developments carried out during Task 4.4.Once the interaction and communication mechanisms have been detailed, this  document illustrates  the  MetaDieta  software  and  MetaDieta  mobile  system.  Finally,  a description of the tests and demonstrations performed is presented.

This deliverable describes the tests carried out at different levels to validate that
PREVENTOMICS system works properly and performs as expected.

This report describes the consolidated version modelling the genotype variables through defined algorithms to identify the genetic susceptibility of individuals to the PREVENTOMICS health factors of interest. That is, taking into account the validated biomarkers (clinical, health status, nutritional…) and their relevance with the genetic background. Of particular interest are those gene-diet interactions that may have the potential to modulate phenotypic traits. This, in close connection with the DSS dataset, will contribute to a nutrigenetics model of the individuals and will provide the basis for personalised dietary advice. In this report, current scientific evidence concerning genetic variants and their potential impact on each metabolic risk clusterare analysed. Details about the process of elaboration, calculation of genetic risks and their integration with metabolic information are described.

The present deliverable is part of Work Package 5 – Consumer-centred interventions which objective is to carry out interventional studies with real end-users in a multi-cultural and multi-social environment in four different countries in Europe (UK, PL, DK, and ES) to demonstrate the efficiency and efficacy of the application of individual metabolomic signature to the personalization of nutrition. This document presents how the different pilot interventions have performed individually. 

The present deliverable includes the main findings that allow to assess the overall performance of the personalized nutrition system developed in the project. The main objective of PREVENTOMICS was “to improve health status of individuals through developing personalized nutrition plans that combines phenotypic characterization at the metabolomic level with consumers’ genotype, lifestyle, health status and preferences. PREVENTOMICS will translate this information into personalized dietetic advice for the user, automatically generated and efficiently delivered with the use of ICT technologies. 

This report is presenting necessary laws and regulations in order to tackle the food production instances both in Denmark and Spain. The work for deliverable 6.2 is taken into account when working with the Danish pilot within PREVENTOMICS.

This report is tightly connected to the WP 5 (Consumer-centred interventions). The objective of WP 5 is to carry out interventional studies with real end-users in a multi-cultural and multi-social environment to demonstrate the efficiency and efficacy of the application of individual metabolomic signature to the personalization of nutrition. More specifically, CARINSA will design and apply different food ingredients with functional capacity that could be used for the personalized food delivery in the Danish pilot by SIMPLE FEAST (in early 2021). What is more, this report will be used in WP 4 (PREVENTOMICS personalized nutrition integration). The goal of WP 4 is to integrate PREVENTOMICS DSS into the different platform and digital channels of the three companies (ALDI, SF and META) assuring the delivery of personalized recommendations. This includes creating the communication protocols and interfaces as well as assuring continuous validation.

This report is divided into three parts. Firstly, a list of EU food regulations is presented that are applicable both in Denmark and Spain. Secondly, an overview of food legislation regulatory in Denmark is presented. And lastly, the same overview is done for Spain. The presented regulations are important in the framework of PREVENTOMICS and will be taken into account by SF (Simple Feast) and CAR (Carinsa).

Personalized nutrition is nowadays a well-known term, but little is known about the (cost-) effectiveness and preferences regarding personalized nutrition. This report describes the studies that were done to fill this gap. The specific aim of this report is to show the results of the studies done in volunteers, which all started with a systematic literature review. This review gave insight in the (cost-) effectiveness of personalized nutrition interventions, including a critical view on the quality of life of people who participated in personalized nutrition interventions. Insights from this systematic review resulted in the need to interview the general population (volunteers) about the preferences regarding personalized nutrition interventions.  

From the systematic literature review, we found that most interventions tend to have positive effects on quality of life or clinical outcomes; in most cases, the increase in costs were considered acceptable. However, it was also observed that most studies only focussed on psychological aspects of personalized nutrition instead of an integrated approach where biological and psychological concepts are combined (as is done in PREVENTOMICS). Moreover, it was found that very few studies had investigated the preferences and willingness-to-pay of people regarding these personalized interventions. Therefore, focus group sessions were conducted to understand the preferences of the general population, which resulted in the identification of different important characteristics of personalized nutrition interventions that might influence the willingness to use a certain intervention (e.g. price and time).

This deliverable describes the results of a series of cost-effectiveness analyses relating to personalized nutrition interventions. In these analyses, we used the effectiveness and cost data collected during the different pilots to estimate the both the short-term and long-term cost-effectiveness. In the short-term analyses, the trial’s follow-up period was used as the time horizon of the analysis. We therefore used the actual trial results for various outcomes such as BMI (body mass index), body weight, quality of life, diet satisfaction and expenditure on food. In the long-term analyses, we transformed the observed results regarding BMI seen in the pilot studies into estimates of quality-adjusted life-years (QALY), or healthy life-years, costs and cost-effectiveness over an entire lifetime. These analyses were performed using a Markov model consisting of different health states: No diabetes/no IHD/no stroke, IHD, diabetes, stroke and death. The primary outcome of this model was the incremental costs per quality-adjusted life-year (QALY) gained.  

This deliverable describes the results that are part of the health technology assessment (HTA) done regarding the PREVENTOMICS project. This assessment made use of the HTA core model, that consists of nine different domains. These domains are: Health problem and current use of technology (CUR), Description and technical characteristics of technology (TEC), Safety (SAF), Clinical effectiveness (EFF), Costs and economic evaluation (ECO), Ethical analysis (ETH), Organisational aspects (ORG), Patients and Social aspects (SOC) and Legal aspects (LEG).

The aim of this HTA was to collect and analyse the information on the different interventions from different angles to support developers. This was done to provide a foundation for local considerations and informed decisions. We use results from previous deliverables, literature, additional questionnaire analyses (from a discrete choice experiment) and information from partners to describe all different domains.

Although, the first results of the PREVENTOMICS pilots might be promising, there is still uncertainty related to the interventions. It is clear that people, and especially people with obesity, need help. Nowadays, there is still a gap in solving the obesity problem and personalised nutrition might be part of the solution to fill this gap. The PREVENTOMICS solutions are quite accessible for different populations. They can be considered very safe, since only minor safety hazards related to the puncture sites or incorrect categorization can occur. The first results on the effects of the different pilots can be considered slightly positive related to the personalization of the interventions in Denmark and Spain. Only very first results in the UK also show positive effects of the personalised approach compared to the control group (these are not shown in this deliverable), but the results from Poland were in contrast to the results in the UK, not that promising.

When the results were extrapolated over a longer time horizon (i.e., lifetime horizon), we see that it can reduce long-term healthcare costs by reducing the risk of obesity related diseases. However, there is a downside in the fact that people live longer and will eventually incur other healthcare costs. In the end, long-term savings may not be achievable. If the increase in effects outsets the increase in costs, then the interventions can still be considered cost-effective.

During the pilots, it was made sure that all ethical standards were met, by an ethics board. The autonomy of patients will be respected at all times. PREVENTOMICS can be seen as a supplement in daily practice, and not much education and training of staff is expected. Some shortcomings of the PREVENTOMICS interventions were experienced by the participants, however these are solved. For the future, it might be good to centralize all analyses as much as possible.

Overall, participants accept the PREVENTOMICS technologies. However, it remains important to convince people that PREVENTOMICS is not just another tool that will be on the market. Moreover, it is important to pay attention to the fact that participants state that relative to other attributes, the total expenditure on nutrition was seen as most important. Moreover, there are no important legal issues that need to be resolved to use, reimburse or apply personalised nutrition on a wide scale.

The idea of the PREVENTOMICS is that it could be used for all type of populations as a preventive mode, healthy and less healthy. It can be concluded that if might be a reliable tool for the general population, as the Spanish pilot shows, but also for a specific overweight/obesity population as done in the other pilots. However, more research is needed to establish these conclusions. This HTA serves as a good foundation for future research.

This deliverable is the initial version of the project’s DataManagement Plan and explains the proposed actions for the overall control of PREVENTOMICS’s data and publications. The deliverable embarks with a summarisation of thetypes and sources of data and continues with the description of the practices for safeguarding that the PREVENTOMICS research data are findable, accessible, interoperable and re-usable (FAIR). An account of the allocated resources for data management is included. The deliverable concludes with an appreciation of the data security and ethical considerations principles to be adopted.

This deliverable details the communication materials that have been prepared from M1-M12 and the plans for the following months.

D7.3 Public Communication Materials

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PREVENTOMICS project shows an enormous potential as combines metabolomics sciences and information communications technology to make a significant step forward in the empowerment of citizens and in promoting a long-lasting personalized nutrition.

The success of PREVENTOMICS and the realisation of its maximum impact will be achieved via the direct exploitation of the main expected result: a novel mFood platform and its derived modular technologies. The mFood platform developed during the PREVENTOMICS project includes the dynamic software platform and algorithms, the pre-required analytics services (combination of genetic, biological, nutritional and psychological) and the derived dataset combining all the anonymized data gathered from the conducted tests. This unique-in-its-kind service is interoperable with existing software applications related to health status monitoring and dietary guidance and opens the door to the personalization of any type of nutrition advice and health treatment.

PREVENTOMICS envisaged exploitation routes; including efficient technology transfer to strategic future rollout and commercialisation agents as well as integration into existing business cases from consortium SMEs well-positioned in the food manufacturing and nutrition services; grants a smooth transition from R&I to scale-up and market adoption.

The present deliverable presents the definition and steps made towards execution of well-coordinated exploitation and dissemination activities (WP7) aligned with all other tasks developed in the project.

PREVENTOMICS project shows an enormous potential as combines metabolomics sciences and ICT to make a significant step forward in the empowerment of citizens and in promoting a long-lasting personalized nutrition. The success of PREVENTOMICS and the realisation of its maximum impact will be achieved via the direct exploitation of the main expected result: a novel mFood platform and its derived modular technologies. The mFood platform developed during the PREVENTOMICS project includes the dynamic software platform and algorithms, the pre-required analytics services (combination of genetic, biological, nutritional,and psychological) and the derived dataset combining all the anonymized data gathered from the conducted tests. This unique-in-its-kind service is interoperable with existing software applications related to health status monitoring and dietary guidanceand opens the door to the personalization of any type of nutrition advice and health treatment.

PREVENTOMICS envisaged several exploitations routes; including efficient technology transfer to strategic future rollout, tobrokering to commercialisation agents as well as integration into existing business cases from consortium SMEs well-positioned in the food manufacturing and nutrition services. The objective is to grant a smooth transition from R&D to scale-up and market adoption. The present deliverable presents the definition and steps made towards execution of well-coordinated exploitation and dissemination activities (WP7) aligned with all other tasks developed in the project. It also presents the current results that have been disseminated and the coming ones with the dedicated dissemination strategy. Targets, channels, formats and timeline are presented in the Dissemination part of the PUDR.

The present deliverable presents the definition and steps made towards the development of a set of practical abstracts presenting to the general public the main results of the project. The abstracts have been designed following a template and EIP-AGRI Common format for interactive innovation projectsand are availablein the PREVENTOMICS website.

D7.6 Practical Abstracts

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The Spanish Association for Standardization (UNE), as a European Standardization Body, is a partner in the PREVENTOMICS project to provide support regarding the standardization tasks included in the project (WP 7 “Market Impact Management and Dissemination”). 

To fulfil this commitment, this deliverable D7.7 “Report on the contribution to standardization” has been prepared to provide the actions performed to promote the consideration of the results and approach of the project in future standardization works.  

D7.7 includes the actions, justification and results obtained including an analysis of the possibilities to further interaction with the standardization system. Additionally, the document identifies the most suitable CEN-CENELEC document to the nature of the project results and the path to be followed to submit a standardization proposal.  

This deliverable provides all project partners with a summary of the main project procedures (project monitoring, reporting, financial management, etc.) It contains documentation and communication standards in order to enable good communication within the consortium. This document also describes the quality plan.

The PREVENTOMICS project (GA 818318), aims to ‘Empower consumers to PREVENT diet-related diseases through OMICS sciences’. The PREVENTOMICS project aims to build a science-based app to support consumers in food choices. Health-biomarkers based on omics sciences constitute the basis of the app. As the project is constituted by different building blocks with its intrinsic challenges (e.g. health-biomarkers; building an app-platform, setting up analytical methods for circulating marker; human interventions; bioinformatical analysis; business models …)  identification of risk-areas and anticipation of possible future risks that may rise from project execution is of utmost importance. This deliverable reviews the risks anticipated during proposal stage as well as includes new ones as a result of project development.

The PREVENTOMICS project (GA 818318), aims to ‘Empower consumers to PREVENT dietrelated diseases through OMICS sciences. The PREVENTOMICS project aims to build a science based app to support consumers in food choices. Health-biomarkers based on omics sciences constitute the basis of the app. As the project is constituted by different building blocks with its intrinsic challenges (e.g. health-biomarkers; building an app-platform, setting up analytical methods for circulating marker; human interventions; bioinformatical analysis; business models …) identification of risk-areas and anticipation of possible future risks that may rise from project execution is of high importance. This deliverable reviews the risks anticipated during proposal stage as well as includes new ones because of project development.

Aiming to explore and exploit the potential benefits posed by an efficient management of PREVENTOMICS innovation procedures, one specific task in the project is dedicated towards innovation management (Task 8.4). Namely, the purpose of this task is to ensure that the project research activities and achievements are properly managed throughout the project. At the same time, the task aimed to advice and support participating enterprises (particularly SMEs) in implementing successful innovation strategies beyond the project’s framework.  

The innovation management efforts have been mainly carried out under the lead of an innovation expert from EURECAT consultancy department. The present deliverable describes key activities conducted as part of the Innovation Management task during the three year of project development (M1-M36). Concretely, a description of the main activities is included and have consisted in the partner assessment (evaluation aimed to determine what is the situation of consortium partners with respect to its ability to innovate). Based on the information gathered in the questionnaires, EUT undertook the initial diagnosis. This diagnosis identified several opportunities to improve existing innovation management practices within the consortium and was conducted to tailor project innovation management workshops towards partners’ specific needs. 

Additionally, the first section of this deliverable briefly introduces what is innovation management as well as the approach followed for the management of the task. Lastly, several innovation management supporting tools and methodologies (e.g. Stage gate model, R-W-W Screen, Monnier’s Innovation Matrix, Innovation radar, etc) are also presented and included in the annexes