Seven pilot studies across four European countries are testing a Healthy Lifestyle Recommender System (HLRS) in 240 older adults with overweight BMI (25-29.9 kg/m²). The AI-driven platform generates personalized physical activity and meal recommendations while incorporating emotional well-being factors, monitored through smartwatches and accelerometers over three months. Two sites will additionally analyze blood, urine, stool, and saliva samples for inflammation markers, gut microbiome profiles, and circulating microRNAs. This represents a significant evolution in obesity intervention design, moving beyond one-size-fits-all approaches to truly individualized digital therapeutics. The timing is particularly relevant given that obesity rates in adults over 65 have tripled since 1980, yet most weight management tools ignore the unique metabolic, physical, and psychological challenges of aging. The multi-biomarker approach could reveal novel mechanistic insights linking personalized interventions to biological responses. However, the three-month timeframe limits assessment of long-term behavior change sustainability. If successful, this could establish the foundation for precision medicine approaches to obesity management in aging populations, potentially reducing healthcare costs and improving quality of life outcomes.