Clinical trials

Breast cancer (BC) is the most commonly diagnosed cancer in women worldwide, with early-onset cases increasing due to genetic and lifestyle factors. Traditional prevention strategies have shown limited effectiveness, creating the need for innovative approaches. The MELIORA project develops an AI-driven digital tool, the Virtual Coach (VC), to promote sustainable behaviour change in physical activity, diet, and alcohol use. Three randomized-controlled studies will be conducted: MELIORA-HEALTHY (women at risk, n=1080 in Greece, Lithuania, Spain), MELIORA-PATIENTS (women undergoing treatment, n=400 in Lithuania, Spain), and MELIORA-SURVIVORS (post-treatment survivors, n=600 in Lithuania, Spain, Sweden). Participants across diverse regions and backgrounds will be randomized to standard lifestyle advice or the same advice plus the MELIORA VC app. Each study lasts 12 months, with outcomes assessed at baseline, 6, and 12 months. The primary outcome is physical activity, with secondary outcomes including sedentary behaviour, diet, alcohol use, and quality of life. If effective, the MELIORA VC could offer a scalable, cost-effective model for BC prevention and survivorship care, providing valuable evidence to guide public health strategies.

To support the development of the MELIORA digital app for the MELIORA main intervention, an initial pilot study (Data Collection Campaign, DCC) is being conducted with the three target participant groups: healthy women at increased risk of developing breast cancer (BC), BC patients, and BC survivors across the four intervention countries (Spain, Greece, Lithuania, Sweden). The planned sample size for each group is 156 healthy women at risk (defined as not meeting recommendations for a healthy lifestyle), 58 BC patients, and 86 BC survivors. Each participant is asked to test and evaluate a preliminary version of the MELIORA app over a 14-day period. The DCC takes place in the early stages of the project, as part of the intervention development phase, to inform the technical refinement and preliminary evaluation of the MELIORA digital app.

Chios mastic is a natural product with strong antimicrobial, anti-inflammatory and antioxidant properties, and well-established benefits for dyspeptic disorders. The aim of the present study is to investigate the effectiveness of a natural aqueous extract of Chios mastic (mastic water), a by-product of Chios mastic processing, in the management of dyspepsia. This will be a 3-month randomized double-blind controlled clinical trial in adults with dyspepsia. Participants will be blindly randomized to an intervention group, which will receive 600 mL/d of a carbonated beverage enriched with Chios mastic water (0.2%), or a control group, which will receive 600 mL/d of an identical placebo beverage with no active ingredients. Participants will be evaluated in terms of anthropometric indices, lifestyle habits, severity of dyspepsia-related gastrointestinal symptoms, quality of life, as well as biochemical markers, both pre- and post-intervention.

The BETTER4U project (Preventing obesity through Biologically and bEhaviorally Tailored inTERventions for you) is funded by the European Union (EU) and involves an international consortium consisting of 28 partners across Europe, Israel, and Australia. The project started in November 2023 and will run until October 2027. The main aim of BETTER4U is to improve weight management through a tailor-made intervention, the "BETTER4ALL personalized intervention", using modern monitoring tools and artificial intelligence (AI), including machine learning (ML) practices. In the context of the BETTER4U project, the present Pilot Study aims to a) evaluate the usability, feasibility and acceptability of the BETTER4U mobile application ("BETTER4U App") and Intervention Platform that will be used to monitor and collect data from participants in the BETTER4ALL personalized intervention (randomized controlled trial; RCT) and b) collect data to evaluate and improve the BETTER4U causal AI models for the prevention of weight gain, before deploying them at large scale, as well as test and identify the optimal ways of delivering the AI-based interventions to the participants. The study will be conducted in seven sites in Cyprus, France, Greece, Poland, Portugal, Spain, and Sweden. The BETTER4All Pilot Study will be a longitudinal, correlational, observational study, including a total of n=490 participants, equally distributed among the seven sites (i.e. n=70 per site). Specifically, n=60 (± 3-5) "general population" participants (henceforth: "end-users" of the wearables and the BETTER4U App) and n=10 (± 3-5) healthcare or other types of providers (henceforth: potential "implementers" of the BETTER4U intervention) will constitute each site's sample. The study will involve the following two components: a) the administration of the wearables (smartwatches) to the "end-users" and their registration to and training on the BETTER4U App, to be used for a total duration of three weeks (21 days). During this period, their lifestyle behaviours (i.e. "BETTER4U Core Behavioural Indicators - BCBIs", such as eating occasions, physical activity, sedentary time, sleep etc.) and "living environment indicators - LEIs"; (e.g. access to parks in your area, distance from your home to your work place etc.) will be recorded daily, either in an automated way via the wearables or self-reported by the end-users through the App; and b) the registration to and training on the BETTER4U Intervention Platform of the "implementers" for a total duration of one week (7 days), during which they will be asked to test the platform's functionalities using synthetic data. The implementers will also be provided with the wearables and the App (similarly to the end-users) for one week only to allow collection of additional data that will help verify the accuracy of the algorithms in the gathered data from the wearables/monitoring tools regarding BCBIs and LEIs. Overall, the outcomes and the findings of the Pilot Study will be used to further refine, optimize, and adjust the tools for the BETTER4ALL RCT, according to the feedback received by both end-users' and implementers' perspectives.

The BETTER4U (Preventing obesity through Biologically and bEhaviorally Tailored inTERventions for you) project, funded by the European Union, aims to address obesity through biologically and behaviourally tailored interventions. Obesity is a major public health issue influenced by genetic, metabolic, and lifestyle factors. Despite current weight management interventions, many individuals face challenges due to these varied influences. The BETTER4U project seeks to improve weight management by incorporating artificial intelligence (AI) and polygenic risk scores (PRS) to personalize interventions. The goal is to test the effectiveness of these personalized interventions in improving weight loss compared to standard care, using advanced monitoring tools and AI models. The BETTER4ALL personalized intervention is a multicentre, open-label, parallel-group randomized controlled trial (RCT) involving seven study sites across Cyprus, France, Greece, Poland, Portugal, Spain, and Sweden. A total of 1,022 participants with overweight or obesity (BMI ≥ 25 kg/m²), aged 18-65 years, will be enrolled. Participants will be randomized into two groups: an intervention group receiving personalized lifestyle recommendations based on AI and PRS, and a control group receiving standard care recommendations. The intervention will last six months, followed by a six-month follow-up assessment. The intervention's key aspects include wearable devices and a mobile application to monitor participants' behaviour, including physical activity, sleep, and eating habits. The intervention also integrates genetic, metabolic, and environmental data to provide tailored recommendations for weight loss. Participants' outcomes will be assessed regarding BMI, weight loss maintenance, changes in clinical biomarkers, body composition, and other lifestyle parameters. This RCT will provide valuable insights into the effectiveness of personalized weight management strategies. AI-driven personalized recommendations and real-time monitoring represent a significant shift from traditional, one-size-fits-all approaches. The results of this study could offer a more effective and sustainable model for obesity management, particularly by accounting for individual genetic predispositions and lifestyle factors. Furthermore, by evaluating the impact of the intervention on a wide range of health outcomes, including biomarkers and psychosocial factors, the study will provide a comprehensive understanding of how personalized interventions can improve overall health and weight management. In addition to contributing to the scientific understanding of obesity and its management, this project has the potential to influence public health strategies, offering a more personalized, data-driven approach to obesity prevention and treatment. By integrating genetic, environmental, and lifestyle factors, the BETTER4U intervention could pave the way for future innovations in digital health and obesity management.